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EOS/src/akkudoktoreos/utils/datetimeutil.py

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fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
"""Utility module for date, time, and timezone handling.
This module provides a unified interface for working with dates, times, durations, and timezones.
It leverages the `pendulum` library to simplify conversions between string representations,
native `datetime`/`date`/`timedelta` types, Unix timestamps, and timezone-aware types.
Features:
---------
- Parse and normalize various date or timestamp formats into a `pendulum.DateTime`.
- Convert durations from strings or numerics into `pendulum.Duration`.
- Infer timezone from UTC offset or geolocation.
- Support for custom output formats (ISO 8601, UTC normalized, or user-specified formats).
- Makes pendulum types usable in pydantic models using `pydantic_extra_types.pendulum_dt`
and the `Time` class.
Types:
------
- `Time`: Pendulum's time type with timezone awareness.
- `DateTime`: Pendulum's timezone-aware datetime type.
- `Date`: Pendulum's date type.
- `Duration`: Pendulum's representation of a time delta.
- `TimeWindow`: Daily or specific date time window with optional localization support.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Functions:
----------
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
- `to_time`: Convert diverse time inputs into a `Time` or formatted string.
- `to_datetime`: Convert diverse date/time inputs into a `DateTime` or formatted string.
- `to_duration`: Convert strings or numerics into a `Duration`.
- `to_timezone`: Convert a UTC offset or geographic coordinate into a `Timezone` or its name.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
Usage Examples:
---------------
>>> to_time("15:30:00", in_timezone="Europe/Berlin")
Time(17, 30, 0, tzinfo=Timezone('Europe/Berlin'))
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
>>> to_datetime("2024-10-13T15:30:00", in_timezone="Europe/Berlin")
DateTime(2024, 10, 13, 17, 30, 0, tzinfo=Timezone('Europe/Berlin'))
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
>>> to_duration("2 days 5 hours")
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
Duration(days=2, hours=5)
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
>>> to_timezone(location=(40.7128, -74.0060), as_string=True)
'America/New_York'
See each function's docstring for detailed argument options and examples.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
"""
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
import calendar
import datetime
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
import re
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
from typing import Any, Iterator, List, Literal, Optional, Tuple, Union, overload
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
import pendulum
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
from babel.dates import get_day_names
from loguru import logger
from pendulum.tz.timezone import Timezone
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
from pydantic import (
BaseModel,
Field,
GetCoreSchemaHandler,
field_serializer,
field_validator,
model_validator,
)
from pydantic_core import core_schema
from pydantic_extra_types.pendulum_dt import ( # make pendulum types pydantic
Date,
DateTime,
Duration,
)
from tzfpy import get_tz
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
MAX_DURATION_STRING_LENGTH = 350
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
class Time(pendulum.Time):
"""A timezone-aware Time class derived from pendulum.Time.
Provides methods to get hour information for specific timezones
with local timezone as default.
Makes Time handled by pydantic.
"""
def __new__(
cls,
*args: Any,
tzinfo: Optional[Union[datetime.tzinfo, pendulum.Timezone, str]] = None,
**kwargs: Any,
) -> "Time":
"""Create a new Time instance with optional tzinfo parameter.
Args:
*args: Positional arguments passed to pendulum.Time
tzinfo: Optional timezone information - can be:
- datetime.tzinfo object
- pendulum.Timezone object
- string (timezone name like 'UTC', 'Europe/Berlin')
**kwargs: Keyword arguments passed to pendulum.Time
"""
# Extract tzinfo from args if one of them is a Time-like object
for arg in args:
if isinstance(arg, (pendulum.Time, Time)) and arg.tzinfo:
tzinfo = tzinfo or arg.tzinfo
# Check if tzinfo is already in kwargs, use it if our tzinfo param is None
existing_tzinfo = kwargs.pop("tzinfo", None)
if tzinfo is None and existing_tzinfo is not None:
tzinfo = existing_tzinfo
# Create the base instance without tzinfo (pendulum.Time does not understand),
# but with pydantic validation
instance = super().__new__(cls, *args, **kwargs)
if tzinfo is not None:
# Convert string timezone names to pendulum timezone
if isinstance(tzinfo, str):
tzinfo = pendulum.timezone(tzinfo)
# Convert datetime.tzinfo to pendulum timezone if needed
elif isinstance(tzinfo, datetime.tzinfo) and not isinstance(tzinfo, pendulum.Timezone):
# For standard datetime tzinfo, we need to handle conversion
# This is a simplified approach - you might need more sophisticated handling
tzinfo = pendulum.timezone(str(tzinfo))
# Use pendulum.Time.replace() directly to avoid recursive pydantic validation
pend_instance = pendulum.Time(*args, **kwargs)
pend_instance = pend_instance.replace(tzinfo=tzinfo)
# Create Time instance from pendulum Time instance to avoid recursive pydantic validation
instance = cls._create_from_pendulum_time(pend_instance)
return instance
@classmethod
def __get_pydantic_core_schema__(
cls, source_type: type, handler: GetCoreSchemaHandler
) -> core_schema.CoreSchema:
return core_schema.no_info_after_validator_function(
cls._validate,
core_schema.any_schema(), # Accept any input, let _validate handle the logic
serialization=core_schema.plain_serializer_function_ser_schema(
cls._serialize,
return_schema=core_schema.str_schema(),
),
)
@classmethod
def _validate(cls, value: Any) -> "Time":
"""Validate input value and convert to Time instance using to_time function."""
if isinstance(value, cls):
return value
# Handle None values explicitly
if value is None:
raise ValueError("Time value cannot be None")
try:
# Use to_time function to convert the value
time_obj = to_time(value, to_naive=False)
# If to_time returned a string (shouldn't happen)
if isinstance(time_obj, str):
raise ValueError(f"Unexpected string result from to_time: {time_obj}")
# If it's already our custom Time class, return it
if isinstance(time_obj, cls):
return time_obj
# Convert pendulum.Time to our custom Time class
if isinstance(time_obj, pendulum.Time):
# Convert to our custom class without triggering validation
return cls._create_from_pendulum_time(time_obj)
raise ValueError(f"Cannot convert {type(time_obj)} to Time")
except Exception as e:
raise ValueError(f"Invalid time value: {value}") from e
@classmethod
def _create_from_pendulum_time(cls, pend_time: pendulum.Time) -> "Time":
"""Create a Time instance from a pendulum.Time object.
This bypasses Pydantic validation and ensures proper internal state.
"""
# Construct a new pendulum.Time instance explicitly
time_obj = pendulum.Time(
pend_time.hour,
pend_time.minute,
pend_time.second,
pend_time.microsecond,
)
time_obj = time_obj.replace(tzinfo=pend_time.tzinfo)
# Bypass __init__ and __new__ by directly casting the type
time_obj.__class__ = cls # This is safe since Time inherits from pendulum.Time
return time_obj
@classmethod
def _serialize(cls, value: Optional["Time"]) -> str:
"""Serialize Time instance to string.
Returns timezone-aware format if timezone info is present,
otherwise returns naive format.
"""
if value is None:
return ""
tz = value.tzinfo
if tz is None:
return value.format("HH:mm:ss.SSSSSS")
tz_str = str(tz)
if tz_str in ("UTC", "Etc/UTC"):
return f"{value.format('HH:mm:ss.SSSSSS')} UTC"
if re.match(r"[+-]\d{2}:?\d{2}", tz_str):
return value.format("HH:mm:ss.SSSSSSZZ")
return f"{value.format('HH:mm:ss.SSSSSS')} {tz_str}"
def __repr__(self) -> str:
"""Enhanced repr with more detailed information."""
tz_info = f", tzinfo={self.tzinfo}" if self.tzinfo else ""
return f"Time({self.hour}, {self.minute}, {self.second}, {self.microsecond}{tz_info})"
def __str__(self) -> str:
"""String representation for user-friendly display."""
return self._serialize(self)
def __eq__(self, other: Any) -> bool:
"""Enhanced equality comparison that handles timezone conversion."""
if not isinstance(other, (pendulum.Time, Time)):
return False
# If both have timezone info, compare in UTC
if self.tzinfo and other.tzinfo:
# Convert both to UTC for comparison
self_utc = self.in_timezone("UTC")
other_utc = other.in_timezone("UTC")
return (self_utc.hour, self_utc.minute, self_utc.second, self_utc.microsecond) == (
other_utc.hour,
other_utc.minute,
other_utc.second,
other_utc.microsecond,
)
# If neither has timezone info, compare directly
if not self.tzinfo and not other.tzinfo:
return super().__eq__(other)
# Mixed timezone/naive comparison - only equal if times are exactly the same
return super().__eq__(other)
def __hash__(self) -> int:
"""Hash function that considers timezone."""
if self.tzinfo:
# Hash based on UTC time
utc_time = self.in_timezone("UTC")
return hash(
(utc_time.hour, utc_time.minute, utc_time.second, utc_time.microsecond, "UTC")
)
return hash((self.hour, self.minute, self.second, self.microsecond, None))
def to_local(self) -> "Time":
"""Convert to local timezone."""
if not self.tzinfo:
return self # Already naive, assume local
return self.in_timezone(pendulum.local_timezone())
def to_utc(self) -> "Time":
"""Convert to UTC timezone."""
return self.in_timezone("UTC")
def in_timezone(self, timezone: Union[str, pendulum.Timezone]) -> "Time":
"""Convert to specified timezone."""
if isinstance(timezone, str):
timezone = pendulum.timezone(timezone)
if self.is_aware():
# For timezone conversion, we need a reference date
# Use today's date as reference
today = pendulum.today(self.tzinfo)
dt = today.at(self.hour, self.minute, self.second, self.microsecond)
dt = dt.in_timezone(timezone) # Convert to target timezone
t = dt.time() # Extract naiv time component
t = t.replace(tzinfo=timezone) # Add target timezone
time_obj = self._create_from_pendulum_time(t)
else:
# Assume current time is in local timezone
time_obj = self.replace(tzinfo=pendulum.local_timezone())
return time_obj
def is_naive(self) -> bool:
"""Check if time is timezone-naive."""
return self.tzinfo is None
def is_aware(self) -> bool:
"""Check if time is timezone-aware."""
return self.tzinfo is not None
def replace_timezone(self, tz: Union[str, pendulum.Timezone, None]) -> "Time":
"""Replace timezone without converting the time value."""
if isinstance(tz, str):
tz = pendulum.timezone(tz)
return self.replace(tzinfo=tz)
def format_user_friendly(
self, include_seconds: bool = False, include_timezone: Optional[bool] = None
) -> str:
"""Format time in a user-friendly way.
Args:
include_seconds: Whether to include seconds in the output
include_timezone: Whether to include timezone info (auto-detected if None)
"""
if include_timezone is None:
include_timezone = self.tzinfo is not None
if include_seconds:
time_format = "HH:mm:ss"
else:
time_format = "HH:mm"
if include_timezone and self.tzinfo:
time_format += " ZZ"
return self.format(time_format)
@classmethod
def now(cls, tz: Union[str, pendulum.Timezone] = None) -> "Time":
"""Get current time with optional timezone."""
if tz:
if isinstance(tz, str):
tz = pendulum.timezone(tz)
now = pendulum.now(tz)
else:
now = pendulum.now()
return cls(now.hour, now.minute, now.second, now.microsecond, tzinfo=now.tzinfo)
@classmethod
def parse(cls, time_string: str) -> "Time":
"""Parse time string using your enhanced parser."""
parsed = _parse_time_string(time_string)
return cls(
parsed.hour, parsed.minute, parsed.second, parsed.microsecond, tzinfo=parsed.tzinfo
)
def _parse_time_string(time_str: str, default_date: pendulum.Date = None) -> pendulum.Time:
"""Parse various time string formats with comprehensive patterns and timezone support.
Supports a wide variety of time formats including:
Basic 24-hour formats:
- "14:30" - Standard HH:MM format
- "14:30:45" - HH:MM:SS format
- "14:30:45.123456" - HH:MM:SS with microseconds
- "1430" - Compact HHMM format
- "143045" - Compact HHMMSS format
- "930" - Short format (9:30)
- "14" - Hour only
- "14.5" - Decimal time (14:30)
- "14h30" - European format with 'h'
- "14-30" - With dash separator
- "14 30" - With space separator
12-hour AM/PM formats:
- "2:30 PM" - Standard 12-hour with seconds
- "2:30:45 PM" - 12-hour with seconds
- "2PM" - Short AM/PM format
- "11AM" - Short AM/PM format
Timezone formats:
- "14:30 UTC" - With UTC timezone
- "14:30 GMT" - With GMT timezone
- "2:30 PM EST" - 12-hour with timezone abbreviation
- "14:30 +05:30" - With offset timezone
- "14:30 -0800" - With compact offset
- "930 PST" - Any format can have timezone
- "14h30 America/New_York" - With full timezone name
Args:
time_str: The time string to parse
default_date: Default date to use when timezone is present (defaults to today)
Returns:
pendulum.Time object, optionally with timezone information attached
Raises:
ValueError: If the time string cannot be parsed or contains invalid time components
"""
time_str = time_str.strip()
original_str = time_str
# Validate basic format first
if not time_str:
raise ValueError("Empty time string")
# Extract timezone information first
timezone_info = None
time_part = time_str
# Pattern for timezone at the end: +HH:MM, -HH:MM, +HHMM, -HHMM, UTC, GMT, EST, PST, etc.
tz_pattern = re.compile(
r"(.+?)\s*([+-]\d{2}:?\d{2}|UTC[+-]?\d{0,2}:?\d{0,2}|GMT[+-]?\d{0,2}:?\d{0,2}|[A-Z]{3,4}|[A-Za-z_]+/[A-Za-z_]+)$",
re.IGNORECASE,
)
tz_match = tz_pattern.match(time_str)
if tz_match:
time_part = tz_match.group(1).strip()
timezone_str = tz_match.group(2).strip()
# Parse timezone
if timezone_str.upper() in ["UTC", "GMT"]:
timezone_info = pendulum.timezone("UTC")
elif timezone_str.upper() in ["EST", "EDT"]:
timezone_info = pendulum.timezone("America/New_York")
elif timezone_str.upper() in ["CST", "CDT"]:
timezone_info = pendulum.timezone("America/Chicago")
elif timezone_str.upper() in ["MST", "MDT"]:
timezone_info = pendulum.timezone("America/Denver")
elif timezone_str.upper() in ["PST", "PDT"]:
timezone_info = pendulum.timezone("America/Los_Angeles")
elif re.match(r"[A-Za-z_]+/[A-Za-z_]+", timezone_str):
# Try to parse as a standard timezone name
try:
timezone_info = pendulum.timezone(timezone_str)
except:
raise ValueError(f"Unknown timezone: {timezone_str}")
elif re.match(r"[+-]\d{2}:?\d{2}", timezone_str):
# Handle offset format like +05:30, -08:00, +0530, -0800
clean_tz = timezone_str.replace(":", "")
if len(clean_tz) == 5: # +HHMM or -HHMM
sign = clean_tz[0]
hours = int(clean_tz[1:3])
minutes = int(clean_tz[3:5])
offset_minutes = hours * 60 + minutes
if sign == "-":
offset_minutes = -offset_minutes
timezone_info = pendulum.tz.timezone.FixedTimezone(offset_minutes * 60)
else:
raise ValueError(f"Unknown timezone: {timezone_str}")
# Now parse the time part (convert to uppercase for AM/PM matching)
time_part_upper = time_part.upper()
# Pattern 1: HH:MM:SS.microseconds format
pattern1 = re.compile(r"^(\d{1,2}):(\d{2}):(\d{2})(?:\.(\d{1,6}))?$")
match = pattern1.match(time_part_upper)
if match:
hour, minute, second = int(match.group(1)), int(match.group(2)), int(match.group(3))
microsecond = int((match.group(4) or "0").ljust(6, "0")[:6])
if hour > 23 or minute > 59 or second > 59:
raise ValueError(f"Invalid time components: {hour}:{minute}:{second}")
time_obj = pendulum.time(hour, minute, second, microsecond)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
# Pattern 2: HH:MM format
pattern2 = re.compile(r"^(\d{1,2}):(\d{2})$")
match = pattern2.match(time_part_upper)
if match:
hour, minute = int(match.group(1)), int(match.group(2))
if hour > 23 or minute > 59:
raise ValueError(f"Invalid time components: {hour}:{minute}")
time_obj = pendulum.time(hour, minute)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
# Pattern 3: 12-hour format with AM/PM (HH:MM:SS AM/PM or HH:MM AM/PM)
pattern3 = re.compile(r"^(\d{1,2}):(\d{2})(?::(\d{2}))?\s*(AM|PM)$")
match = pattern3.match(time_part_upper)
if match:
hour, minute = int(match.group(1)), int(match.group(2))
second = int(match.group(3)) if match.group(3) else 0
am_pm = match.group(4)
if hour > 12 or hour < 1 or minute > 59 or second > 59:
raise ValueError(f"Invalid 12-hour time: {original_str}")
# Convert to 24-hour format
if am_pm == "AM":
if hour == 12:
hour = 0
else: # PM
if hour != 12:
hour += 12
time_obj = pendulum.time(hour, minute, second)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
# Pattern 4: Short AM/PM format (e.g., "2PM", "11AM")
pattern4 = re.compile(r"^(\d{1,2})\s*(AM|PM)$")
match = pattern4.match(time_part_upper)
if match:
hour = int(match.group(1))
am_pm = match.group(2)
if hour > 12 or hour < 1:
raise ValueError(f"Invalid 12-hour time: {original_str}")
# Convert to 24-hour format
if am_pm == "AM":
if hour == 12:
hour = 0
else: # PM
if hour != 12:
hour += 12
time_obj = pendulum.time(hour, 0)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
# Pattern 5: European format with 'h' (e.g., "14h30", "9h15")
pattern5 = re.compile(r"^(\d{1,2})H(\d{2})$")
match = pattern5.match(time_part_upper)
if match:
hour, minute = int(match.group(1)), int(match.group(2))
if hour > 23 or minute > 59:
raise ValueError(f"Invalid time components: {hour}:{minute}")
time_obj = pendulum.time(hour, minute)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
# Pattern 6: Compact format (HHMM, HHMMSS)
if time_part_upper.isdigit():
if len(time_part_upper) == 4:
hour, minute = int(time_part_upper[:2]), int(time_part_upper[2:])
if hour > 23 or minute > 59:
raise ValueError(f"Invalid time components: {hour}:{minute}")
time_obj = pendulum.time(hour, minute)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
elif len(time_part_upper) == 6:
hour, minute, second = (
int(time_part_upper[:2]),
int(time_part_upper[2:4]),
int(time_part_upper[4:6]),
)
if hour > 23 or minute > 59 or second > 59:
raise ValueError(f"Invalid time components: {hour}:{minute}:{second}")
time_obj = pendulum.time(hour, minute, second)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
elif len(time_part_upper) == 3:
# Handle formats like "930" as 9:30
hour, minute = int(time_part_upper[0]), int(time_part_upper[1:])
if hour > 23 or minute > 59:
raise ValueError(f"Invalid time components: {hour}:{minute}")
time_obj = pendulum.time(hour, minute)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
elif len(time_part_upper) == 1 or len(time_part_upper) == 2:
# Handle single/double digit hours
hour = int(time_part_upper)
if hour > 23:
raise ValueError(f"Invalid hour: {hour}")
time_obj = pendulum.time(hour, 0)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
# Pattern 7: Decimal time (e.g., "14.5" as 14:30)
try:
if "." in time_part and time_part.replace(".", "").isdigit():
float_val = float(time_part)
if float_val < 0 or float_val >= 24:
raise ValueError(f"Hour must be between 0 and 23.999..., got {float_val}")
hour = int(float_val)
minutes = int((float_val - hour) * 60)
seconds = int(((float_val - hour) * 60 - minutes) * 60)
time_obj = pendulum.time(hour, minutes, seconds)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
except ValueError:
pass
# Pattern 8: Handle various separators (but be careful with dots)
separators = ["-", " "] # Removed '.' to avoid conflict with decimal times
for sep in separators:
if sep in time_part:
parts = time_part.split(sep)
if len(parts) >= 2 and all(part.isdigit() for part in parts[:3]):
hour = int(parts[0])
minute = int(parts[1])
second = int(parts[2]) if len(parts) > 2 else 0
if hour > 23 or minute > 59 or second > 59:
raise ValueError(f"Invalid time components: {hour}:{minute}:{second}")
time_obj = pendulum.time(hour, minute, second)
if timezone_info:
return time_obj.replace(tzinfo=timezone_info)
return time_obj
raise ValueError(f"Unable to parse time string: '{original_str}'")
TimeLike = Union[
str,
int,
float,
Tuple[int, ...],
Time,
datetime.time,
datetime.datetime,
pendulum.Time,
DateTime,
]
# Overload 1: Returns Time
@overload
def to_time(
value: TimeLike,
in_timezone: Union[str, pendulum.tz.Timezone, None] = ...,
to_naive: bool = ...,
as_string: Literal[False, None] = ...,
) -> Time: ...
# Overload 2: Returns str
@overload
def to_time(
value: TimeLike,
in_timezone: Union[str, pendulum.tz.Timezone, None] = ...,
to_naive: bool = ...,
as_string: Union[str, Literal[True]] = ...,
) -> str: ...
# Implementation that satisfies both
def to_time(
value: TimeLike,
in_timezone: Union[str, pendulum.tz.Timezone, None] = None,
to_naive: bool = False,
as_string: Union[str, bool, None] = None,
) -> Union[Time, str]:
"""Convert a time-like value into a timezone-aware Time object or formatted string.
Args:
value: A time representation. Supports:
- Time
- pendulum.Time or pendulum.DateTime
- datetime.time or datetime.datetime
- strings like "14:30", "2:30 PM", "1430", "14:30:00.123", "2PM", "14h30"
- int (e.g. 14 14:00)
- float (e.g. 14.5 14:30)
- tuple like (14,), (14, 30), (14, 30, 15)
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
in_timezone: Optional timezone name or object (e.g., "Europe/Berlin").
Defaults to the local timezone.
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
to_naive: If True, return a timezone-naive Time object.
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
as_string: If True, return time as "HH:mm:ss ZZ".
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
If a format string is provided, it's passed to `pendulum.Time.format()`.
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
Returns:
Time or str: A time object or its formatted string.
Raises:
ValueError: If the input cannot be interpreted as a valid time.
TypeError: If timezone is not a valid type.
"""
# Validate and set timezone
try:
if in_timezone is None:
timezone = pendulum.local_timezone()
if isinstance(timezone, str):
timezone = pendulum.timezone(timezone)
elif isinstance(in_timezone, str):
timezone = pendulum.timezone(in_timezone)
elif isinstance(in_timezone, pendulum.tz.Timezone):
timezone = in_timezone
else:
raise TypeError(f"Invalid timezone type: {type(in_timezone)}")
if not isinstance(timezone, Timezone):
# Should never happen
raise TypeError(f"Invalid timezone conversion to type: {type(timezone)} ({timezone})")
except Exception as e:
raise ValueError(f"Invalid timezone: {in_timezone}") from e
def finalize(t: pendulum.Time) -> Union[Time, str]:
"""Finalize the time object with timezone and formatting."""
nonlocal timezone, in_timezone
try:
if to_naive:
t = t.replace(tzinfo=None)
# Apply timezone if not naive
elif t.tzinfo:
if in_timezone is not None and t.tzinfo != timezone:
# Convert from original timezone to selected timezone
# For timezone conversion, we need a reference date
# Use today's date as reference
today = pendulum.today(t.tzinfo)
dt = today.at(t.hour, t.minute, t.second, t.microsecond)
dt = dt.in_timezone(timezone) # Convert to target timezone
t = dt.time() # Extract time component (always naive)
t = t.replace(tzinfo=timezone) # Add timezone to naive time
else:
# Just set the timezone
t = t.replace(tzinfo=timezone)
if as_string:
if isinstance(as_string, str):
return t.format(as_string)
elif t.tzinfo is not None:
return t.format("HH:mm:ss ZZ")
else:
return t.format("HH:mm:ss")
return Time(t.hour, t.minute, t.second, t.microsecond, tzinfo=t.tzinfo)
except Exception as e:
raise ValueError(f"Failed to finalize time object: {t}") from e
# Handle different input types
try:
if isinstance(value, Time):
return finalize(value)
if isinstance(value, pendulum.Time):
return finalize(value)
# Handle DateTime class if it exists
if hasattr(value, "in_tz") and hasattr(value, "time"):
return finalize(value.in_tz(timezone).time())
if isinstance(value, datetime.time):
base = pendulum.time(value.hour, value.minute, value.second, value.microsecond)
return finalize(base)
if isinstance(value, datetime.datetime):
if value.tzinfo:
# Convert tzinfo to a string (name or offset)
tz_name = value.tzinfo.tzname(value)
# Safely get Pendulum timezone
try:
timezone = pendulum.timezone(tz_name)
except Exception:
# fallback to fixed offset if tz_name is something like 'UTC+02:00'
utc_offset = value.tzinfo.utcoffset(value)
if utc_offset is None:
utc_offset_total_seconds = 0.0
else:
utc_offset_total_seconds = utc_offset.total_seconds()
timezone = pendulum.FixedTimezone(utc_offset_total_seconds // 60)
pdt = pendulum.instance(value).in_tz(timezone)
return finalize(pdt.time())
if isinstance(value, tuple):
if not value:
raise ValueError("Empty tuple provided")
# Pad tuple with zeros if needed
padded = tuple(list(value) + [0] * (4 - len(value)))[:4]
base = pendulum.time(*padded)
return finalize(base)
if isinstance(value, int):
if value < 0 or value > 23:
raise ValueError(f"Hour must be between 0 and 23, got {value}")
base = pendulum.time(value, 0)
return finalize(base)
if isinstance(value, float):
if value < 0 or value >= 24:
raise ValueError(f"Hour must be between 0 and 23.999..., got {value}")
hour = int(value)
minutes = int((value - hour) * 60)
seconds = int(((value - hour) * 60 - minutes) * 60)
microseconds = int(((((value - hour) * 60 - minutes) * 60 - seconds) * 1_000_000))
base = pendulum.time(hour, minutes, seconds, microseconds)
return finalize(base)
if isinstance(value, str):
# Try our comprehensive string parser first
try:
parsed_time = _parse_time_string(value)
return finalize(parsed_time)
except ValueError as e:
logger.trace(f"Custom parser failed for: {value} - {e}")
# Fallback to pendulum's parser
try:
dt = pendulum.parse(value, strict=False).in_tz(timezone)
return finalize(dt.time())
except Exception as e:
logger.trace(f"Pendulum parser failed for '{value}': {e}")
# Try parsing with ISO time prefix
try:
dt = pendulum.parse(f"T{value}", strict=False).in_tz(timezone)
return finalize(dt.time())
except Exception as e:
logger.trace(f"ISO time parser failed for 'T{value}': {e}")
# Try parsing as part of a full datetime
try:
dt = pendulum.parse(f"2000-01-01 {value}", strict=False).in_tz(timezone)
return finalize(dt.time())
except Exception as e:
logger.trace(f"Full datetime parser failed for '2000-01-01 {value}': {e}")
# If all parsing attempts fail, raise a more specific error
raise ValueError(f"Unable to parse time string: '{value}'")
raise ValueError(f"Unsupported type: {type(value)}")
except ValueError:
raise
except Exception as e:
raise ValueError(f"Invalid time value: {value!r} of type: {type(value)}") from e
class TimeWindow(BaseModel):
"""Model defining a daily or specific date time window with optional localization support.
Represents a time interval starting at `start_time` and lasting for `duration`.
Can restrict applicability to a specific day of the week or a specific calendar date.
Supports day names in multiple languages via locale-aware parsing.
"""
start_time: Time = Field(
..., json_schema_extra={"description": "Start time of the time window (time of day)."}
)
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
duration: Duration = Field(
...,
json_schema_extra={
"description": "Duration of the time window starting from `start_time`."
},
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
)
day_of_week: Optional[Union[int, str]] = Field(
default=None,
json_schema_extra={
"description": (
"Optional day of the week restriction. "
"Can be specified as integer (0=Monday to 6=Sunday) or localized weekday name. "
"If None, applies every day unless `date` is set."
)
},
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
)
date: Optional[Date] = Field(
default=None,
json_schema_extra={
"description": (
"Optional specific calendar date for the time window. Overrides `day_of_week` if set."
)
},
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
)
locale: Optional[str] = Field(
default=None,
json_schema_extra={
"description": (
"Locale used to parse weekday names in `day_of_week` when given as string. "
"If not set, Pendulum's default locale is used. "
"Examples: 'en', 'de', 'fr', etc."
)
},
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
)
@field_validator("duration", mode="before")
@classmethod
def transform_to_duration(cls, value: Any) -> Duration:
"""Converts various duration formats into Duration.
Args:
value: The value to convert to Duration.
Returns:
Duration: The converted Duration object.
"""
return to_duration(value)
@model_validator(mode="after")
def validate_day_of_week_with_locale(self) -> "TimeWindow":
"""Validates and normalizes the `day_of_week` field using the specified locale.
This method supports both integer (06) and string inputs for `day_of_week`.
String inputs are matched first against English weekday names (case-insensitive),
and then against localized weekday names using the provided `locale`.
If a valid match is found, `day_of_week` is converted to its corresponding
integer value (0 for Monday through 6 for Sunday).
Returns:
TimeWindow: The validated instance with `day_of_week` normalized to an integer.
Raises:
ValueError: If `day_of_week` is an invalid integer (not in 06),
or an unrecognized string (not matching English or localized names),
or of an unsupported type.
"""
if self.day_of_week is None:
return self
if isinstance(self.day_of_week, int):
if not 0 <= self.day_of_week <= 6:
raise ValueError("day_of_week must be in 0 (Monday) to 6 (Sunday)")
return self
if isinstance(self.day_of_week, str):
# Try matching against English names first (lowercase)
english_days = {name.lower(): i for i, name in enumerate(calendar.day_name)}
lowercase_value = self.day_of_week.lower()
if lowercase_value in english_days:
self.day_of_week = english_days[lowercase_value]
return self
# Try localized names
if self.locale:
localized_days = {
get_day_names("wide", locale=self.locale)[i].lower(): i for i in range(7)
}
if lowercase_value in localized_days:
self.day_of_week = localized_days[lowercase_value]
return self
raise ValueError(
f"Invalid weekday name '{self.day_of_week}' for locale '{self.locale}'. "
f"Expected English names (mondaysunday) or localized names."
)
raise ValueError(f"Invalid type for day_of_week: {type(self.day_of_week)}")
@field_serializer("duration")
def serialize_duration(self, value: Duration) -> str:
"""Serialize duration to string."""
return str(value)
def _window_start_end(self, reference_date: DateTime) -> tuple[DateTime, DateTime]:
"""Get the actual start and end datetimes for the time window on a given date.
This method computes the concrete start and end datetimes of the configured
time window for a specific date, taking into account timezone information.
Handles timezone-aware and naive `DateTime` and `Time` objects:
- If both `reference_date` and `start_time` have timezones but differ,
`start_time` is converted to the timezone of `reference_date`.
- If only one has a timezone, the other inherits it.
- If both are naive, UTC is assumed for both.
Args:
reference_date: The reference date on which to calculate the window.
Returns:
tuple[DateTime, DateTime]: A tuple containing the start and end datetimes
for the time window, both timezone-aware.
"""
ref_tz = reference_date.timezone
start_tz = self.start_time.tzinfo
# --- Timezone resolution logic ---
if ref_tz and start_tz:
# Both aware: align start_time to reference_date's tz
if ref_tz != start_tz:
start_time = self.start_time.in_timezone(ref_tz)
else:
start_time = self.start_time
elif ref_tz and not start_tz:
# Only reference_date aware → assume same tz for time
start_time = self.start_time.replace_timezone(ref_tz)
elif not ref_tz and start_tz:
# Only start_time aware → apply its tz to reference_date
reference_date = reference_date.replace(tzinfo=start_tz)
start_time = self.start_time
else:
# Both naive → default to UTC
reference_date = reference_date.replace(tzinfo="UTC")
start_time = self.start_time.replace_timezone("UTC")
# --- Build window start ---
start = reference_date.replace(
hour=start_time.hour,
minute=start_time.minute,
second=start_time.second,
microsecond=start_time.microsecond,
)
# --- Compute window end ---
end = start + self.duration
return start, end
def contains(self, date_time: DateTime, duration: Optional[Duration] = None) -> bool:
"""Check whether a datetime (and optional duration) fits within the time window.
This method checks if a given datetime `date_time` lies within the start time and duration
defined by the `TimeWindow`. If `duration` is provided, it also ensures that
the full duration starting at `date_time` ends before or at the end of the time window.
Handles timezone-aware and naive datetimes:
- If both `date_time` and `start_time` are timezone-aware but differ align `start_time`
to `date_time`s timezone.
- If only one has a timezone assign it to the other.
- If both are naive assume UTC for both.
If `day_of_week` or `date` are specified in the time window, the method will also
ensure that `date_time` falls on the correct day or matches the exact date.
Args:
date_time: The datetime to test.
duration: An optional duration that must fit entirely within the time window
starting from `date_time`.
Returns:
bool: True if the datetime (and optional duration) is fully contained in the
time window, False otherwise.
"""
start_time = self.start_time # work on a local copy to avoid mutating self
start_tz = getattr(start_time, "tzinfo", None)
ref_tz = date_time.timezone
# --- Handle timezone logic ---
if ref_tz and start_tz:
# Both aware but different → align start_time to date_time's timezone
if ref_tz != start_tz:
start_time = start_time.in_timezone(ref_tz)
elif ref_tz and not start_tz:
# Only date_time aware → assign its timezone to start_time
start_time = start_time.replace_timezone(ref_tz)
elif not ref_tz and start_tz:
# Only start_time aware → assign its timezone to date_time
date_time = date_time.replace(tzinfo=start_tz)
else:
# Both naive → assume UTC
date_time = date_time.replace(tzinfo="UTC")
start_time = start_time.replace_timezone("UTC")
# --- Date and weekday constraints ---
if self.date and date_time.date() != self.date:
return False
if self.day_of_week is not None and date_time.day_of_week != self.day_of_week:
return False
# --- Compute window start and end for this date ---
start, end = self._window_start_end(date_time)
# --- Check containment ---
if not (start <= date_time < end):
return False
if duration is not None:
date_time_end = date_time + duration
return date_time_end <= end
return True
def earliest_start_time(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> Optional[DateTime]:
"""Get the earliest datetime that allows a duration to fit within the time window.
Args:
duration: The duration that needs to fit within the window.
reference_date: The date to check for the time window. Defaults to today.
Returns:
The earliest start time for the duration, or None if it doesn't fit.
"""
if reference_date is None:
reference_date = pendulum.today()
# Check if the reference date matches our constraints
if self.date and reference_date.date() != self.date:
return None
if self.day_of_week is not None and reference_date.day_of_week != self.day_of_week:
return None
# Check if the duration can fit within the time window
if duration > self.duration:
return None
window_start, window_end = self._window_start_end(reference_date)
# The earliest start time is simply the window start time
return window_start
def latest_start_time(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> Optional[DateTime]:
"""Get the latest datetime that allows a duration to fit within the time window.
Args:
duration: The duration that needs to fit within the window.
reference_date: The date to check for the time window. Defaults to today.
Returns:
The latest start time for the duration, or None if it doesn't fit.
"""
if reference_date is None:
reference_date = pendulum.today()
# Check if the reference date matches our constraints
if self.date and reference_date.date() != self.date:
return None
if self.day_of_week is not None and reference_date.day_of_week != self.day_of_week:
return None
# Check if the duration can fit within the time window
if duration > self.duration:
return None
window_start, window_end = self._window_start_end(reference_date)
# The latest start time is the window end minus the duration
latest_start = window_end - duration
# Ensure the latest start time is not before the window start
if latest_start < window_start:
return None
return latest_start
def can_fit_duration(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> bool:
"""Check if a duration can fit within the time window on a given date.
Args:
duration: The duration to check.
reference_date: The date to check for the time window. Defaults to today.
Returns:
bool: True if the duration can fit, False otherwise.
"""
return self.earliest_start_time(duration, reference_date) is not None
def available_duration(self, reference_date: Optional[DateTime] = None) -> Optional[Duration]:
"""Get the total available duration for the time window on a given date.
Args:
reference_date: The date to check for the time window. Defaults to today.
Returns:
The available duration, or None if the date doesn't match constraints.
"""
if reference_date is None:
reference_date = pendulum.today()
if self.date and reference_date.date() != self.date:
return None
if self.day_of_week is not None and reference_date.day_of_week != self.day_of_week:
return None
return self.duration
class TimeWindowSequence(BaseModel):
"""Model representing a sequence of time windows with collective operations.
Manages multiple TimeWindow objects and provides methods to work with them
as a cohesive unit for scheduling and availability checking.
"""
windows: Optional[list[TimeWindow]] = Field(
default_factory=list,
json_schema_extra={"description": "List of TimeWindow objects that make up this sequence."},
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
)
@field_validator("windows")
@classmethod
def validate_windows(cls, v: Optional[list[TimeWindow]]) -> list[TimeWindow]:
"""Validate windows and convert None to empty list."""
if v is None:
return []
return v
def model_post_init(self, __context: Any) -> None:
"""Ensure windows is always a list after initialization."""
if self.windows is None:
self.windows = []
def __iter__(self) -> Iterator[TimeWindow]:
"""Allow iteration over the time windows."""
return iter(self.windows or [])
def __len__(self) -> int:
"""Return the number of time windows in the sequence."""
return len(self.windows or [])
def __getitem__(self, index: int) -> TimeWindow:
"""Allow indexing into the time windows."""
if not self.windows:
raise IndexError("list index out of range")
return self.windows[index]
def contains(self, date_time: DateTime, duration: Optional[Duration] = None) -> bool:
"""Check if any time window in the sequence contains the given datetime and duration.
Args:
date_time: The datetime to test.
duration: An optional duration that must fit entirely within one of the time windows.
Returns:
bool: True if any time window contains the datetime (and optional duration), False if no windows.
"""
if not self.windows:
return False
return any(window.contains(date_time, duration) for window in self.windows)
def earliest_start_time(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> Optional[DateTime]:
"""Get the earliest datetime across all windows that allows a duration to fit.
Args:
duration: The duration that needs to fit within a window.
reference_date: The date to check for the time windows. Defaults to today.
Returns:
The earliest start time across all windows, or None if no window can fit the duration.
"""
if not self.windows:
return None
if reference_date is None:
reference_date = pendulum.today()
earliest_times = []
for window in self.windows:
earliest = window.earliest_start_time(duration, reference_date)
if earliest is not None:
earliest_times.append(earliest)
return min(earliest_times) if earliest_times else None
def latest_start_time(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> Optional[DateTime]:
"""Get the latest datetime across all windows that allows a duration to fit.
Args:
duration: The duration that needs to fit within a window.
reference_date: The date to check for the time windows. Defaults to today.
Returns:
The latest start time across all windows, or None if no window can fit the duration.
"""
if not self.windows:
return None
if reference_date is None:
reference_date = pendulum.today()
latest_times = []
for window in self.windows:
latest = window.latest_start_time(duration, reference_date)
if latest is not None:
latest_times.append(latest)
return max(latest_times) if latest_times else None
def can_fit_duration(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> bool:
"""Check if the duration can fit within any time window in the sequence.
Args:
duration: The duration to check.
reference_date: The date to check for the time windows. Defaults to today.
Returns:
bool: True if any window can fit the duration, False if no windows.
"""
if not self.windows:
return False
return any(window.can_fit_duration(duration, reference_date) for window in self.windows)
def available_duration(self, reference_date: Optional[DateTime] = None) -> Optional[Duration]:
"""Get the total available duration across all applicable windows.
Args:
reference_date: The date to check for the time windows. Defaults to today.
Returns:
The sum of available durations from all applicable windows, or None if no windows apply.
"""
if not self.windows:
return None
if reference_date is None:
reference_date = pendulum.today()
total_duration = Duration()
has_applicable_windows = False
for window in self.windows:
window_duration = window.available_duration(reference_date)
if window_duration is not None:
total_duration += window_duration
has_applicable_windows = True
return total_duration if has_applicable_windows else None
def get_applicable_windows(self, reference_date: Optional[DateTime] = None) -> list[TimeWindow]:
"""Get all windows that apply to the given reference date.
Args:
reference_date: The date to check for the time windows. Defaults to today.
Returns:
List of TimeWindow objects that apply to the reference date.
"""
if not self.windows:
return []
if reference_date is None:
reference_date = pendulum.today()
applicable_windows = []
for window in self.windows:
if window.available_duration(reference_date) is not None:
applicable_windows.append(window)
return applicable_windows
def find_windows_for_duration(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> list[TimeWindow]:
"""Find all windows that can accommodate the given duration.
Args:
duration: The duration that needs to fit.
reference_date: The date to check for the time windows. Defaults to today.
Returns:
List of TimeWindow objects that can fit the duration.
"""
if not self.windows:
return []
if reference_date is None:
reference_date = pendulum.today()
fitting_windows = []
for window in self.windows:
if window.can_fit_duration(duration, reference_date):
fitting_windows.append(window)
return fitting_windows
def get_all_possible_start_times(
self, duration: Duration, reference_date: Optional[DateTime] = None
) -> list[tuple[DateTime, DateTime, TimeWindow]]:
"""Get all possible start time ranges for a duration across all windows.
Args:
duration: The duration that needs to fit.
reference_date: The date to check for the time windows. Defaults to today.
Returns:
List of tuples containing (earliest_start, latest_start, window) for each
window that can accommodate the duration.
"""
if not self.windows:
return []
if reference_date is None:
reference_date = pendulum.today()
possible_times = []
for window in self.windows:
earliest = window.earliest_start_time(duration, reference_date)
latest = window.latest_start_time(duration, reference_date)
if earliest is not None and latest is not None:
possible_times.append((earliest, latest, window))
return possible_times
def add_window(self, window: TimeWindow) -> None:
"""Add a new time window to the sequence.
Args:
window: The TimeWindow to add.
"""
if self.windows is None:
self.windows = []
self.windows.append(window)
def remove_window(self, index: int) -> TimeWindow:
"""Remove a time window from the sequence by index.
Args:
index: The index of the window to remove.
Returns:
The removed TimeWindow.
Raises:
IndexError: If the index is out of range.
"""
if not self.windows:
raise IndexError("pop from empty list")
return self.windows.pop(index)
def clear_windows(self) -> None:
"""Remove all windows from the sequence."""
if self.windows is not None:
self.windows.clear()
def sort_windows_by_start_time(self, reference_date: Optional[DateTime] = None) -> None:
"""Sort the windows by their start time on the given reference date.
Windows that don't apply to the reference date are placed at the end.
Args:
reference_date: The date to use for sorting. Defaults to today.
"""
if not self.windows:
return
if reference_date is None:
reference_date = pendulum.today()
def sort_key(window: TimeWindow) -> tuple[int, DateTime]:
"""Sort key: (priority, start_time) where priority 0 = applicable, 1 = not applicable."""
start_time = window.earliest_start_time(Duration(), reference_date)
if start_time is None:
# Non-applicable windows get a high priority (sorted last) and a dummy time
return (1, reference_date)
return (0, start_time)
self.windows.sort(key=sort_key)
@overload
def to_datetime(
date_input: Optional[Any] = None,
as_string: Literal[False] | None = None,
in_timezone: Optional[Union[str, Timezone]] = None,
to_naiv: Optional[bool] = None,
to_maxtime: Optional[bool] = None,
) -> DateTime: ...
@overload
def to_datetime(
date_input: Optional[Any] = None,
as_string: str | Literal[True] = True,
in_timezone: Optional[Union[str, Timezone]] = None,
to_naiv: Optional[bool] = None,
to_maxtime: Optional[bool] = None,
) -> str: ...
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
def to_datetime(
date_input: Optional[Any] = None,
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
as_string: Optional[Union[str, bool]] = None,
in_timezone: Optional[Union[str, Timezone]] = None,
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
to_naiv: Optional[bool] = None,
to_maxtime: Optional[bool] = None,
) -> Union[DateTime, str]:
"""Convert a date input into a Pendulum DateTime object or a formatted string, with optional timezone handling.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
This function handles various date input formats, adjusts for timezones, and provides flexibility for formatting and time adjustments. For date strings without explicit timezone information, the local timezone is assumed. Be aware that Pendulum DateTime objects created without a timezone default to UTC.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Args:
date_input (Optional[Any]): The date input to convert. Supported types include:
- `str`: A date string in various formats (e.g., "2024-10-13", "13 Oct 2024").
- `pendulum.DateTime`: A Pendulum DateTime object.
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
- `pendulum.Date`: A Pendulum Date object, which will be converted to a datetime at the start or end of the day.
- `datetime.datetime`: A standard Python datetime object.
- `datetime.date`: A date object, which will be converted to a datetime at the start or end of the day.
- `int` or `float`: A Unix timestamp, interpreted as seconds since the epoch (UTC).
- `None`: Defaults to the current date and time, adjusted to the start or end of the day based on `to_maxtime`.
as_string (Optional[Union[str, bool]]): Determines the output format:
- `True`: Returns the datetime in ISO 8601 string format.
- `"UTC"` or `"utc"`: Returns the datetime normalized to UTC as an ISO 8601 string.
- `str`: A custom date format string for the output (e.g., "YYYY-MM-DD HH:mm:ss").
- `False` or `None` (default): Returns a `pendulum.DateTime` object.
in_timezone (Optional[Union[str, Timezone]]): Specifies the target timezone for the result.
- Can be a timezone string (e.g., "UTC", "Europe/Berlin") or a `pendulum.Timezone` object.
- Defaults to the local timezone if not provided.
to_naiv (Optional[bool]): If `True`, removes timezone information from the resulting datetime object.
- Defaults to `False`.
to_maxtime (Optional[bool]): Determines the time portion of the resulting datetime for date inputs:
- `True`: Sets the time to the end of the day (23:59:59).
- `False` or `None`: Sets the time to the start of the day (00:00:00).
- Ignored if `date_input` includes an explicit time or if the input is a timestamp.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Returns:
pendulum.DateTime or str:
- A timezone-aware Pendulum DateTime object by default.
- A string representation if `as_string` is specified.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Raises:
ValueError: If `date_input` is not a valid or supported type, or if the date string cannot be parsed.
Examples:
>>> to_datetime("2024-10-13", as_string=True, in_timezone="UTC")
'2024-10-13T00:00:00+00:00'
>>> to_datetime("2024-10-13T15:30:00", in_timezone="Europe/Berlin")
DateTime(2024, 10, 13, 17, 30, 0, tzinfo=Timezone('Europe/Berlin'))
>>> to_datetime(date(2024, 10, 13), to_maxtime=True)
DateTime(2024, 10, 13, 23, 59, 59, tzinfo=Timezone('Local'))
>>> to_datetime(1698784800, as_string="YYYY-MM-DD HH:mm:ss", in_timezone="UTC")
'2024-10-31 12:00:00'
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
"""
# Timezone to convert to
if in_timezone is None:
in_timezone = pendulum.local_timezone()
elif not isinstance(in_timezone, Timezone):
in_timezone = pendulum.timezone(in_timezone)
if isinstance(date_input, DateTime):
dt = date_input
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
elif isinstance(date_input, Date):
dt = pendulum.datetime(
year=date_input.year, month=date_input.month, day=date_input.day, tz=in_timezone
)
if to_maxtime:
dt = dt.end_of("day")
else:
dt = dt.start_of("day")
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
elif isinstance(date_input, str):
# Convert to timezone aware datetime
dt = None
formats = [
"YYYY-MM-DD", # Format: 2024-10-13
"DD/MM/YY", # Format: 13/10/24
"DD/MM/YYYY", # Format: 13/10/2024
"MM-DD-YYYY", # Format: 10-13-2024
"D.M.YYYY", # Format: 1.7.2024
"YYYY.MM.DD", # Format: 2024.10.13
"D MMM YYYY", # Format: 13 Oct 2024
"D MMMM YYYY", # Format: 13 October 2024
"YYYY-MM-DD HH:mm:ss", # Format: 2024-10-13 15:30:00
"YYYY-MM-DDTHH:mm:ss", # Format: 2024-10-13T15:30:00
]
for fmt in formats:
# DateTime input without timezone info
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
try:
fmt_tz = f"{fmt} z"
dt_tz = f"{date_input} {in_timezone}"
dt = pendulum.from_format(dt_tz, fmt_tz)
logger.trace(
f"Str Fmt converted: {dt}, tz={dt.tz} from {date_input}, tz={in_timezone}"
)
break
except ValueError as e:
logger.trace(f"{date_input}, {fmt}, {e}")
dt = None
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
else:
# DateTime input with timezone info
try:
dt = pendulum.parse(date_input)
logger.trace(
f"Pendulum Fmt converted: {dt}, tz={dt.tz} from {date_input}, tz={in_timezone}"
)
except pendulum.parsing.exceptions.ParserError as e:
logger.trace(f"Date string {date_input} does not match any Pendulum formats: {e}")
dt = None
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
if dt is None:
# Some special values
if date_input.lower() == "infinity":
# Subtract one year from max as max datetime will create an overflow error in certain context.
dt = DateTime.max.subtract(years=1)
if dt is None:
try:
timestamp = float(date_input)
dt = pendulum.from_timestamp(timestamp, tz="UTC")
except (ValueError, TypeError) as e:
logger.trace(f"Date string {date_input} does not match timestamp format: {e}")
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
dt = None
if dt is None:
raise ValueError(f"Date string {date_input} does not match any known formats.")
elif date_input is None:
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
dt = pendulum.now(tz=in_timezone)
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
elif isinstance(date_input, datetime.datetime):
dt = pendulum.instance(date_input)
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
elif isinstance(date_input, datetime.date):
dt = pendulum.instance(
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
datetime.datetime.combine(
date_input,
datetime.datetime.max.time() if to_maxtime else datetime.datetime.min.time(),
)
)
elif isinstance(date_input, (int, float)):
dt = pendulum.from_timestamp(date_input, tz="UTC")
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
else:
error_msg = f"Unsupported date input type: {type(date_input)}"
logger.error(error_msg)
raise ValueError(error_msg)
# Represent in target timezone
dt_in_tz = dt.in_timezone(in_timezone)
logger.trace(
f"\nTimezone adapted to: {in_timezone}\nfrom: {dt} tz={dt.timezone}\nto: {dt_in_tz} tz={dt_in_tz.tz}"
)
dt = dt_in_tz
# Remove timezone info if specified
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
if to_naiv:
dt = dt.naive()
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
# Return as formatted string if specified
if isinstance(as_string, str):
if as_string.lower() == "utc":
return dt.in_timezone("UTC").to_iso8601_string()
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
else:
return dt.format(as_string)
if isinstance(as_string, bool) and as_string is True:
return dt.to_iso8601_string()
return dt
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
# to duration helper
def duration_to_iso8601(duration: pendulum.Duration) -> str:
"""Convert pendulum.Duration to ISO-8601 duration string."""
total_seconds = int(duration.total_seconds())
days, rem = divmod(total_seconds, 86400)
hours, rem = divmod(rem, 3600)
minutes, seconds = divmod(rem, 60)
parts = ["P"]
if days:
parts.append(f"{days}D")
time_parts = []
if hours:
time_parts.append(f"{hours}H")
if minutes:
time_parts.append(f"{minutes}M")
if seconds:
time_parts.append(f"{seconds}S")
if time_parts:
parts.append("T")
parts.extend(time_parts)
elif len(parts) == 1: # zero duration
parts.append("T0S")
return "".join(parts)
@overload
def to_duration(
input_value: Union[
Duration, datetime.timedelta, str, int, float, Tuple[int, int, int, int], List[int]
],
as_string: Literal[False] | None = None,
) -> Duration: ...
@overload
def to_duration(
input_value: Union[
Duration, datetime.timedelta, str, int, float, Tuple[int, int, int, int], List[int]
],
as_string: str | Literal[True] = True,
) -> str: ...
def to_duration(
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
input_value: Union[
Duration, datetime.timedelta, str, int, float, Tuple[int, int, int, int], List[int]
],
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
as_string: Optional[Union[str, bool]] = None,
) -> Union[Duration, str]:
"""Converts various input types into a `pendulum.Duration` or a formatted duration string.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Args:
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
input_value (Union[Duration, timedelta, str, int, float, tuple, list]):
The input value to convert into a duration.
Supported types include:
- `pendulum.Duration`: Returned unchanged unless formatting is requested.
- `datetime.timedelta`: Converted based on total seconds.
- `str`: A duration expression (e.g., `"15 minutes"`, `"2 hours"`),
or a string parsed by Pendulum.
- `int` or `float`: Interpreted as a number of seconds.
- `tuple` or `list`: Must be `(days, hours, minutes, seconds)`.
as_string (Optional[Union[str, bool]]):
Controls the output format of the returned duration:
- `None` or `False` (default):
Returns a `pendulum.Duration` object.
- `True`:
Returns an ISO-8601 duration string (e.g., `"PT15M"`).
- `"human"`:
Returns a human-readable form (e.g., `"15 minutes"`).
- `"pandas"`:
Returns a Pandas frequency string such as:
- `"1h"` for 1 hour
- `"15min"` for 15 minutes
- `"900s"` for 900 seconds
- `str`:
A custom format pattern. The following format tokens are supported:
- `{S}` total seconds
- `{M}` total minutes (integer)
- `{H}` total hours (integer)
- `{f}` human-friendly representation (Pendulum `in_words()`)
Example:
`"Duration: {M} minutes"` `"Duration: 15 minutes"`
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Returns:
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
Union[Duration, str]:
- A `pendulum.Duration` if no formatting is requested.
- A formatted string depending on the `as_string` option.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Raises:
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
ValueError:
- If the input type is unsupported.
- If a duration string cannot be parsed.
- If `as_string` contains an unsupported format option.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Examples:
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
>>> to_duration("15 minutes")
<Duration [900 seconds]>
>>> to_duration("15 minutes", as_string=True)
'PT15M'
>>> to_duration("15 minutes", as_string="human")
'15 minutes'
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
>>> to_duration("90 seconds", as_string="pandas")
'90S'
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
>>> to_duration("15 minutes", as_string="{M}m")
'15m'
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
"""
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
# ---- normalize to pendulum.Duration ----
duration = None
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
if isinstance(input_value, Duration):
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
duration = input_value
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
elif isinstance(input_value, datetime.timedelta):
duration = pendulum.duration(seconds=input_value.total_seconds())
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
elif isinstance(input_value, (int, float)):
duration = pendulum.duration(seconds=input_value)
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
elif isinstance(input_value, (tuple, list)):
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
if len(input_value) != 4:
error_msg = f"Expected tuple/list length 4, got {len(input_value)}"
logger.error(error_msg)
raise ValueError(error_msg)
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
days, hours, minutes, seconds = input_value
duration = pendulum.duration(days=days, hours=hours, minutes=minutes, seconds=seconds)
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
elif isinstance(input_value, str):
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
# first try pendulum.parse
try:
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
parsed = pendulum.parse(input_value)
if isinstance(parsed, pendulum.Duration):
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
duration = parsed # Already a duration
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
else:
# It's a DateTime, calculate duration from start of day
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
duration = parsed - parsed.start_of("day")
except pendulum.parsing.exceptions.ParserError as e:
logger.trace(f"Invalid Pendulum time string format '{input_value}': {e}")
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
# Mitigate ReDoS vulnerability (#494) by checking input string length.
if len(input_value) > MAX_DURATION_STRING_LENGTH:
error_msg = (
f"Input string exceeds maximum allowed length ({MAX_DURATION_STRING_LENGTH})."
)
logger.error(error_msg)
raise ValueError(error_msg)
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
# Handle strings like "2 days 5 hours 30 minutes"
matches = re.findall(r"(\d+)\s*(days?|hours?|minutes?|seconds?)", input_value)
if not matches:
error_msg = f"Invalid time string format '{input_value}'"
logger.error(error_msg)
raise ValueError(error_msg)
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
total_seconds = 0
time_units = {
"day": 86400,
"hour": 3600,
"minute": 60,
"second": 1,
}
for value, unit in matches:
unit = unit.lower().rstrip("s") # Normalize unit
if unit in time_units:
total_seconds += int(value) * time_units[unit]
else:
error_msg = f"Unsupported time unit: {unit}"
logger.error(error_msg)
raise ValueError(error_msg)
duration = pendulum.duration(seconds=total_seconds)
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
else:
error_msg = f"Unsupported input type: {type(input_value)}"
logger.error(error_msg)
raise ValueError(error_msg)
feat: add Home Assistant and NodeRED adapters (#764) Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. The fix includes several bug fixes that are not directly related to the adapter implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: development version scheme The development versioning scheme is adaptet to fit to docker and home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>. Hash is only digits as expected by home assistant. Development version is appended by .dev as expected by docker. * fix: use mean value in interval on resampling for array When downsampling data use the mean value of all values within the new sampling interval. * fix: default battery ev soc and appliance wh Make the genetic simulation return default values for the battery SoC, electric vehicle SoC and appliance load if these assets are not used. * fix: import json string Strip outer quotes from JSON strings on import to be compliant to json.loads() expectation. * fix: default interval definition for import data Default interval must be defined in lowercase human definition to be accepted by pendulum. * fix: clearoutside schema change * feat: add adapters for integrations Adapters for Home Assistant and NodeRED integration are added. Akkudoktor-EOS can now be run as Home Assistant add-on and standalone. As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard in Home Assistant. * feat: allow eos to be started with root permissions and drop priviledges Home assistant starts all add-ons with root permissions. Eos now drops root permissions if an applicable user is defined by paramter --run_as_user. The docker image defines the user eos to be used. * feat: make eos supervise and monitor EOSdash Eos now not only starts EOSdash but also monitors EOSdash during runtime and restarts EOSdash on fault. EOSdash logging is captured by EOS and forwarded to the EOS log to provide better visibility. * feat: add duration to string conversion Make to_duration to also return the duration as string on request. * chore: Use info logging to report missing optimization parameters In parameter preparation for automatic optimization an error was logged for missing paramters. Log is now down using the info level. * chore: make EOSdash use the EOS data directory for file import/ export EOSdash use the EOS data directory for file import/ export by default. This allows to use the configuration import/ export function also within docker images. * chore: improve EOSdash config tab display Improve display of JSON code and add more forms for config value update. * chore: make docker image file system layout similar to home assistant Only use /data directory for persistent data. This is handled as a docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos if using docker compose. * chore: add home assistant add-on development environment Add VSCode devcontainer and task definition for home assistant add-on development. * chore: improve documentation
2025-12-30 22:08:21 +01:00
# ---- now apply as_string rules ----
if not as_string:
return duration
total_seconds = int(duration.total_seconds())
# Boolean True → ISO-8601
if as_string is True:
return duration_to_iso8601(duration)
# Human-readable
if as_string == "human":
return duration.in_words()
# Pandas frequency
if as_string == "pandas":
# hours?
if total_seconds % 3600 == 0:
return f"{total_seconds // 3600}h"
# minutes?
if total_seconds % 60 == 0:
return f"{total_seconds // 60}min"
# else seconds (fallback)
return f"{total_seconds}s"
# Custom format string
if isinstance(as_string, str):
return as_string.format(
S=total_seconds,
M=total_seconds // 60,
H=total_seconds // 3600,
f=duration.in_words(),
)
error_msg = f"Unsupported as_string value: {as_string}"
logger.error(error_msg)
raise ValueError(error_msg)
@overload
def to_timezone(
utc_offset: Optional[float] = None,
location: Optional[Tuple[float, float]] = None,
as_string: Literal[True] = True,
) -> str: ...
@overload
def to_timezone(
utc_offset: Optional[float] = None,
location: Optional[Tuple[float, float]] = None,
as_string: Literal[False] | None = None,
) -> Timezone: ...
def to_timezone(
utc_offset: Optional[float] = None,
location: Optional[Tuple[float, float]] = None,
as_string: Optional[bool] = False,
) -> Union[Timezone, str]:
"""Determines the timezone either by UTC offset, geographic location, or local system timezone.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
By default, it returns a `Timezone` object representing the timezone.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
If `as_string` is set to `True`, the function returns the timezone name as a string instead.
Args:
utc_offset (Optional[float]): UTC offset in hours. Positive for UTC+, negative for UTC-.
location (Optional[Tuple[float,float]]): A tuple containing latitude and longitude as floats.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
as_string (Optional[bool]):
- If `True`, returns the timezone as a string (e.g., "America/New_York").
- If `False` or not provided, returns a `Timezone` object for the timezone.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Returns:
Union[Timezone, str]:
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
- A timezone name as a string (e.g., "America/New_York") if `as_string` is `True`.
- A `Timezone` object if `as_string` is `False` or not provided.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Raises:
ValueError: If invalid inputs are provided.
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Example:
>>> to_timezone(utc_offset=5.5, as_string=True)
'UTC+05:30'
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
Fix2 config and predictions revamp. (#281) measurement: - Add new measurement class to hold real world measurements. - Handles load meter readings, grid import and export meter readings. - Aggregates load meter readings aka. measurements to total load. - Can import measurements from files, pandas datetime series, pandas datetime dataframes, simple daetime arrays and programmatically. - Maybe expanded to other measurement values. - Should be used for load prediction adaptions by real world measurements. core/coreabc: - Add mixin class to access measurements core/pydantic: - Add pydantic models for pandas datetime series and dataframes. - Add pydantic models for simple datetime array core/dataabc: - Provide DataImport mixin class for generic import handling. Imports from JSON string and files. Imports from pandas datetime dataframes and simple datetime arrays. Signature of import method changed to allow import datetimes to be given programmatically and by data content. - Use pydantic models for datetime series, dataframes, arrays - Validate generic imports by pydantic models - Provide new attributes min_datetime and max_datetime for DataSequence. - Add parameter dropna to drop NAN/ None values when creating lists, pandas series or numpy array from DataSequence. config/config: - Add common settings for the measurement module. predictions/elecpriceakkudoktor: - Use mean values of last 7 days to fill prediction values not provided by akkudoktor.net (only provides 24 values). prediction/loadabc: - Extend the generic prediction keys by 'load_total_adjusted' for load predictions that adjust the predicted total load by measured load values. prediction/loadakkudoktor: - Extend the Akkudoktor load prediction by load adjustment using measured load values. prediction/load_aggregator: - Module removed. Load aggregation is now handled by the measurement module. prediction/load_corrector: - Module removed. Load correction (aka. adjustment of load prediction by measured load energy) is handled by the LoadAkkudoktor prediction and the generic 'load_mean_adjusted' prediction key. prediction/load_forecast: - Module removed. Functionality now completely handled by the LoadAkkudoktor prediction. utils/cacheutil: - Use pydantic. - Fix potential bug in ttl (time to live) duration handling. utils/datetimeutil: - Added missing handling of pendulum.DateTime and pendulum.Duration instances as input. Handled before as datetime.datetime and datetime.timedelta. utils/visualize: - Move main to generate_example_report() for better testing support. server/server: - Added new configuration option server_fastapi_startup_server_fasthtml to make startup of FastHTML server by FastAPI server conditional. server/fastapi_server: - Add APIs for measurements - Improve APIs to provide or take pandas datetime series and datetime dataframes controlled by pydantic model. - Improve APIs to provide or take simple datetime data arrays controlled by pydantic model. - Move fastAPI server API to v1 for new APIs. - Update pre v1 endpoints to use new prediction and measurement capabilities. - Only start FastHTML server if 'server_fastapi_startup_server_fasthtml' config option is set. tests: - Adapt import tests to changed import method signature - Adapt server test to use the v1 API - Extend the dataabc test to test for array generation from data with several data interval scenarios. - Extend the datetimeutil test to also test for correct handling of to_datetime() providing now(). - Adapt LoadAkkudoktor test for new adjustment calculation. - Adapt visualization test to use example report function instead of visualize.py run as process. - Removed test_load_aggregator. Functionality is now tested in test_measurement. - Added tests for measurement module docs: - Remove sphinxcontrib-openapi as it prevents build of documentation. "site-packages/sphinxcontrib/openapi/openapi31.py", line 305, in _get_type_from_schema for t in schema["anyOf"]: KeyError: 'anyOf'" Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2024-12-29 18:42:49 +01:00
>>> to_timezone(location=(40.7128, -74.0060))
<Timezone [America/New_York]>
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
>>> to_timezone()
<Timezone [America/New_York]> # Returns local timezone
"""
if utc_offset is not None:
if not isinstance(utc_offset, (int, float)):
raise ValueError("UTC offset must be an integer or float representing hours.")
if not -24 <= utc_offset <= 24:
raise ValueError("UTC offset must be within the range -24 to +24 hours.")
# Convert UTC offset to an Etc/GMT-compatible format
hours = int(utc_offset)
minutes = int((abs(utc_offset) - abs(hours)) * 60)
sign = "-" if utc_offset >= 0 else "+"
offset_str = f"Etc/GMT{sign}{abs(hours)}"
if minutes > 0:
offset_str += f":{minutes:02}"
if as_string:
return offset_str
return pendulum.timezone(offset_str)
# Handle location-based lookup
if location is not None:
try:
lat, lon = location
if not (-90 <= lat <= 90 and -180 <= lon <= 180):
raise ValueError(f"Invalid latitude/longitude: {lat}, {lon}")
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
tz_name = get_tz(lon, lat)
if not tz_name:
raise ValueError(
f"No timezone found for coordinates: latitude {lat}, longitude {lon}"
)
except Exception as e:
raise ValueError(f"Error determining timezone for location {location}: {e}") from e
if as_string:
return tz_name
return pendulum.timezone(tz_name)
# Fallback to local timezone
local_tz = pendulum.local_timezone()
fix: automatic optimization (#596) This fix implements the long term goal to have the EOS server run optimization (or energy management) on regular intervals automatically. Thus clients can request the current energy management plan at any time and it is updated on regular intervals without interaction by the client. This fix started out to "only" make automatic optimization (or energy management) runs working. It turned out there are several endpoints that in some way update predictions or run the optimization. To lock against such concurrent attempts the code had to be refactored to allow control of execution. During refactoring it became clear that some classes and files are named without a proper reference to their usage. Thus not only refactoring but also renaming became necessary. The names are still not the best, but I hope they are more intuitive. The fix includes several bug fixes that are not directly related to the automatic optimization but are necessary to keep EOS running properly to do the automatic optimization and to test and document the changes. This is a breaking change as the configuration structure changed once again and the server API was also enhanced and streamlined. The server API that is used by Andreas and Jörg in their videos has not changed. * fix: automatic optimization Allow optimization to automatically run on configured intervals gathering all optimization parameters from configuration and predictions. The automatic run can be configured to only run prediction updates skipping the optimization. Extend documentaion to also cover automatic optimization. Lock automatic runs against runs initiated by the /optimize or other endpoints. Provide new endpoints to retrieve the energy management plan and the genetic solution of the latest automatic optimization run. Offload energy management to thread pool executor to keep the app more responsive during the CPU heavy optimization run. * fix: EOS servers recognize environment variables on startup Force initialisation of EOS configuration on server startup to assure all sources of EOS configuration are properly set up and read. Adapt server tests and configuration tests to also test for environment variable configuration. * fix: Remove 0.0.0.0 to localhost translation under Windows EOS imposed a 0.0.0.0 to localhost translation under Windows for convenience. This caused some trouble in user configurations. Now, as the default IP address configuration is 127.0.0.1, the user is responsible for to set up the correct Windows compliant IP address. * fix: allow names for hosts additional to IP addresses * fix: access pydantic model fields by class Access by instance is deprecated. * fix: down sampling key_to_array * fix: make cache clear endpoint clear all cache files Make /v1/admin/cache/clear clear all cache files. Before it only cleared expired cache files by default. Add new endpoint /v1/admin/clear-expired to only clear expired cache files. * fix: timezonefinder returns Europe/Paris instead of Europe/Berlin timezonefinder 8.10 got more inaccurate for timezones in europe as there is a common timezone. Use new package tzfpy instead which is still returning Europe/Berlin if you are in Germany. tzfpy also claims to be faster than timezonefinder. * fix: provider settings configuration Provider configuration used to be a union holding the settings for several providers. Pydantic union handling does not always find the correct type for a provider setting. This led to exceptions in specific configurations. Now provider settings are explicit comfiguration items for each possible provider. This is a breaking change as the configuration structure was changed. * fix: ClearOutside weather prediction irradiance calculation Pvlib needs a pandas time index. Convert time index. * fix: test config file priority Do not use config_eos fixture as this fixture already creates a config file. * fix: optimization sample request documentation Provide all data in documentation of optimization sample request. * fix: gitlint blocking pip dependency resolution Replace gitlint by commitizen. Gitlint is not actively maintained anymore. Gitlint dependencies blocked pip from dependency resolution. * fix: sync pre-commit config to actual dependency requirements .pre-commit-config.yaml was out of sync, also requirements-dev.txt. * fix: missing babel in requirements.txt Add babel to requirements.txt * feat: setup default device configuration for automatic optimization In case the parameters for automatic optimization are not fully defined a default configuration is setup to allow the automatic energy management run. The default configuration may help the user to correctly define the device configuration. * feat: allow configuration of genetic algorithm parameters The genetic algorithm parameters for number of individuals, number of generations, the seed and penalty function parameters are now avaliable as configuration options. * feat: allow configuration of home appliance time windows The time windows a home appliance is allowed to run are now configurable by the configuration (for /v1 API) and also by the home appliance parameters (for the classic /optimize API). If there is no such configuration the time window defaults to optimization hours, which was the standard before the change. Documentation on how to configure time windows is added. * feat: standardize mesaurement keys for battery/ ev SoC measurements The standardized measurement keys to report battery SoC to the device simulations can now be retrieved from the device configuration as a read-only config option. * feat: feed in tariff prediction Add feed in tarif predictions needed for automatic optimization. The feed in tariff can be retrieved as fixed feed in tarif or can be imported. Also add tests for the different feed in tariff providers. Extend documentation to cover the feed in tariff providers. * feat: add energy management plan based on S2 standard instructions EOS can generate an energy management plan as a list of simple instructions. May be retrieved by the /v1/energy-management/plan endpoint. The instructions loosely follow the S2 energy management standard. * feat: make measurement keys configurable by EOS configuration. The fixed measurement keys are replaced by configurable measurement keys. * feat: make pendulum DateTime, Date, Duration types usable for pydantic models Use pydantic_extra_types.pendulum_dt to get pydantic pendulum types. Types are added to the datetimeutil utility. Remove custom made pendulum adaptations from EOS pydantic module. Make EOS modules use the pydantic pendulum types managed by the datetimeutil module instead of the core pendulum types. * feat: Add Time, TimeWindow, TimeWindowSequence and to_time to datetimeutil. The time windows are are added to support home appliance time window configuration. All time classes are also pydantic models. Time is the base class for time definition derived from pendulum.Time. * feat: Extend DataRecord by configurable field like data. Configurable field like data was added to support the configuration of measurement records. * feat: Add additional information to health information Version information is added to the health endpoints of eos and eosDash. The start time of the last optimization and the latest run time of the energy management is added to the EOS health information. * feat: add pydantic merge model tests * feat: add plan tab to EOSdash The plan tab displays the current energy management instructions. * feat: add predictions tab to EOSdash The predictions tab displays the current predictions. * feat: add cache management to EOSdash admin tab The admin tab is extended by a section for cache management. It allows to clear the cache. * feat: add about tab to EOSdash The about tab resembles the former hello tab and provides extra information. * feat: Adapt changelog and prepare for release management Release management using commitizen is added. The changelog file is adapted and teh changelog and a description for release management is added in the documentation. * feat(doc): Improve install and devlopment documentation Provide a more concise installation description in Readme.md and add extra installation page and development page to documentation. * chore: Use memory cache for interpolation instead of dict in inverter Decorate calculate_self_consumption() with @cachemethod_until_update to cache results in memory during an energy management/ optimization run. Replacement of dict type caching in inverter is now possible because all optimization runs are properly locked and the memory cache CacheUntilUpdateStore is properly cleared at the start of any energy management/ optimization operation. * chore: refactor genetic Refactor the genetic algorithm modules for enhanced module structure and better readability. Removed unnecessary and overcomplex devices singleton. Also split devices configuration from genetic algorithm parameters to allow further development independently from genetic algorithm parameter format. Move charge rates configuration for electric vehicles from optimization to devices configuration to allow to have different charge rates for different cars in the future. * chore: Rename memory cache to CacheEnergyManagementStore The name better resembles the task of the cache to chache function and method results for an energy management run. Also the decorator functions are renamed accordingly: cachemethod_energy_management, cache_energy_management * chore: use class properties for config/ems/prediction mixin classes * chore: skip debug logs from mathplotlib Mathplotlib is very noisy in debug mode. * chore: automatically sync bokeh js to bokeh python package bokeh was updated to 3.8.0, make JS CDN automatically follow the package version. * chore: rename hello.py to about.py Make hello.py the adapted EOSdash about page. * chore: remove demo page from EOSdash As no the plan and prediction pages are working without configuration, the demo page is no longer necessary * chore: split test_server.py for system test Split test_server.py to create explicit test_system.py for system tests. * chore: move doc utils to generate_config_md.py The doc utils are only used in scripts/generate_config_md.py. Move it there to attribute for strong cohesion. * chore: improve pydantic merge model documentation * chore: remove pendulum warning from readme * chore: remove GitHub discussions from contributing documentation Github discussions is to be replaced by Akkudoktor.net. * chore(release): bump version to 0.1.0+dev for development * build(deps): bump fastapi[standard] from 0.115.14 to 0.117.1 bump fastapi and make coverage version (for pytest-cov) explicit to avoid pip break. * build(deps): bump uvicorn from 0.36.0 to 0.37.0 BREAKING CHANGE: EOS configuration changed. V1 API changed. - The available_charge_rates_percent configuration is removed from optimization. Use the new charge_rate configuration for the electric vehicle - Optimization configuration parameter hours renamed to horizon_hours - Device configuration now has to provide the number of devices and device properties per device. - Specific prediction provider configuration to be provided by explicit configuration item (no union for all providers). - Measurement keys to be provided as a list. - New feed in tariff providers have to be configured. - /v1/measurement/loadxxx endpoints are removed. Use generic mesaurement endpoints. - /v1/admin/cache/clear now clears all cache files. Use /v1/admin/cache/clear-expired to only clear all expired cache files. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-10-28 02:50:31 +01:00
if isinstance(local_tz, str):
local_tz = pendulum.timezone(local_tz)
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
if as_string:
return local_tz.name
return local_tz
def hours_in_day(dt: Optional[DateTime] = None) -> int:
"""Returns the number of hours in the given date's day, considering DST transitions.
Args:
dt (Optional[pendulum.DateTime]): The date to check (no time component).
Returns:
int: The number of hours in the day (23, 24, or 25).
"""
if dt is None:
dt = to_datetime()
# Start and end of the day in the local timezone
start_of_day = pendulum.datetime(dt.year, dt.month, dt.day, 0, 0, 0, tz=dt.timezone)
end_of_day = start_of_day.add(days=1)
# Calculate the difference in hours between the two
duration = end_of_day - start_of_day
return int(duration.total_hours())
class DatetimesComparisonResult:
"""Encapsulates the result of comparing two Pendulum DateTime objects.
Attributes:
equal (bool): Indicates whether the two datetimes are exactly equal
(including timezone and DST state).
same_instant (bool): Indicates whether the two datetimes represent the same
point in time, regardless of their timezones.
time_diff (float): The time difference between the two datetimes in seconds.
timezone_diff (bool): Indicates whether the timezones of the two datetimes are different.
dst_diff (bool): Indicates whether the two datetimes differ in their DST states.
approximately_equal (bool): Indicates whether the time difference between the
two datetimes is within the specified tolerance.
ge (bool): True if `dt1` is greater than or equal to `dt2`.
gt (bool): True if `dt1` is strictly greater than `dt2`.
le (bool): True if `dt1` is less than or equal to `dt2`.
lt (bool): True if `dt1` is strictly less than `dt2`.
"""
def __init__(
self,
equal: bool,
same_instant: bool,
time_diff: float,
timezone_diff: bool,
dst_diff: bool,
approximately_equal: bool,
):
self.equal = equal
self.same_instant = same_instant
self.time_diff = time_diff
self.timezone_diff = timezone_diff
self.dst_diff = dst_diff
self.approximately_equal = approximately_equal
@property
def ge(self) -> bool:
"""Greater than or equal: True if `dt1` >= `dt2`."""
return self.equal or self.time_diff > 0
@property
def gt(self) -> bool:
"""Strictly greater than: True if `dt1` > `dt2`."""
return not self.equal and self.time_diff > 0
@property
def le(self) -> bool:
"""Less than or equal: True if `dt1` <= `dt2`."""
return self.equal or self.time_diff < 0
@property
def lt(self) -> bool:
"""Strictly less than: True if `dt1` < `dt2`."""
return not self.equal and self.time_diff < 0
def __repr__(self) -> str:
return (
f"ComparisonResult(equal={self.equal}, "
f"same_instant={self.same_instant}, "
f"time_diff={self.time_diff}, "
f"timezone_diff={self.timezone_diff}, "
f"dst_diff={self.dst_diff}, "
f"approximately_equal={self.approximately_equal}, "
f"ge={self.ge}, gt={self.gt}, le={self.le}, lt={self.lt})"
)
def compare_datetimes(
dt1: DateTime,
dt2: DateTime,
tolerance: Optional[Union[int, pendulum.Duration]] = None,
) -> DatetimesComparisonResult:
"""Compares two Pendulum DateTime objects with precision, including DST and timezones.
This function evaluates various aspects of the relationship between two datetime objects:
- Exact equality, including timezone and DST state.
- Whether they represent the same instant in time (ignoring timezones).
- The absolute time difference in seconds.
- Differences in timezone and DST state.
- Approximate equality based on a specified tolerance.
- Greater or lesser comparisons.
Args:
dt1 (pendulum.DateTime): The first datetime object to compare.
dt2 (pendulum.DateTime): The second datetime object to compare.
tolerance (Optional[Union[int, pendulum.Duration]]): An optional tolerance for comparison.
- If an integer is provided, it is interpreted as seconds.
- If a `pendulum.Duration` is provided, its total seconds are used.
- If not provided, no tolerance is applied.
Returns:
DatetimesComparisonResult: An object containing the results of the comparison, including:
- `equal`: Whether the datetimes are exactly equal.
- `same_instant`: Whether the datetimes represent the same instant.
- `time_diff`: The time difference in seconds.
- `timezone_diff`: Whether the timezones differ.
- `dst_diff`: Whether the DST states differ.
- `approximately_equal`: Whether the time difference is within the tolerance.
- `ge`, `gt`, `le`, `lt`: Relational comparisons between the two datetimes.
Examples:
Compare two datetimes exactly:
>>> dt1 = pendulum.datetime(2023, 7, 1, 12, tz='Europe/Berlin')
>>> dt2 = pendulum.datetime(2023, 7, 1, 12, tz='UTC')
>>> compare_datetimes(dt1, dt2)
DatetimesComparisonResult(equal=False, same_instant=True, time_diff=7200, timezone_diff=True, dst_diff=False, approximately_equal=False, ge=False, gt=False, le=True, lt=True)
Compare with a tolerance:
>>> compare_datetimes(dt1, dt2, tolerance=7200)
DatetimesComparisonResult(equal=False, same_instant=True, time_diff=7200, timezone_diff=True, dst_diff=False, approximately_equal=True, ge=False, gt=False, le=True, lt=True)
"""
# Normalize tolerance to seconds
if tolerance is None:
tolerance_seconds = 0
elif isinstance(tolerance, pendulum.Duration):
tolerance_seconds = tolerance.total_seconds()
else:
tolerance_seconds = int(tolerance)
# Strict equality check (includes timezone and DST)
is_equal = dt1.in_tz("UTC") == dt2.in_tz("UTC")
# Instant comparison (point in time, might be in different timezones)
is_same_instant = dt1.int_timestamp == dt2.int_timestamp
# Time difference calculation. Throws exception if diverging timezone awareness.
time_diff = dt1.int_timestamp - dt2.int_timestamp
# Timezone comparison
timezone_diff = dt1.timezone_name != dt2.timezone_name
# DST state comparison
dst_diff = dt1.is_dst() != dt2.is_dst()
# Tolerance-based approximate equality
is_approximately_equal = time_diff <= tolerance_seconds
Add test to PVForecast (#174) * Add documentation to class_pv_forecast.py. Added documentation. Beware mostly generated by ChatGPT. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add CacheFileStore, datetime and logger utilities. The `CacheFileStore` class is a singleton-based, thread-safe key-value store for managing temporary file objects, allowing the creation, retrieval, and management of cache files. The utility modules offer a flexible logging setup (`get_logger`) and utilities to handle different date-time formats (`to_datetime`, `to_timestamp`) and timezone detection (`to_timezone). - Cache files are automatically valid for the the current date unless specified otherwise. This is to mimic the current behaviour used in several classes. - The logger supports rotating log files to prevent excessive log file size. - The `to_datetime` and `to_timestamp`functions support a wide variety of input types and formats. They provide the time conversion that is e.g. used in PVForecast. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Improve testability of PVForecast Improvements for testing of PVForecast - Use common utility functions to allow for general testing at one spot. - to_datetime - CacheFileStore - Use logging instead of print to easily capture in testing. - Add validation of the json schema for Akkudoktor PV forecast data. - Allow to create an empty PVForecast instance as base instance for testing. - Make process_data() complete for filling a PVForecast instance for testing. - Normalize forecast datetime to timezone of system given in loaded data. - Do not print report but provide report for test checks. - Get rid of cache file path using the CachFileStore to automate cache file usage. - Improved module documentation. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> * Add test for PVForecast and newly extracted utility modules. - Add test for PVForecast - Add test for CacheFileStore in the new cachefilestore module - Add test for to_datetime, to_timestamp, to_timezone in the new datetimeutil module - Add test for get_logger in the new logutil module Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> --------- Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com> Co-authored-by: Normann <github@koldrack.com>
2024-11-10 23:49:10 +01:00
return DatetimesComparisonResult(
equal=is_equal,
same_instant=is_same_instant,
time_diff=time_diff,
timezone_diff=timezone_diff,
dst_diff=dst_diff,
approximately_equal=is_approximately_equal,
)