* All config now nested.
- Use default config from model field default values. If providers
should be enabled by default, non-empty default config file could
be provided again.
- Environment variable support with EOS_ prefix and __ between levels,
e.g. EOS_SERVER__EOS_SERVER_PORT=8503 where all values are case
insensitive.
For more information see:
https://docs.pydantic.dev/latest/concepts/pydantic_settings/#parsing-environment-variable-values
- Use devices as registry for configured devices. DeviceBase as base
class with for now just initializion support (in the future expand
to operations during optimization).
- Strip down ConfigEOS to the only configuration instance. Reload
from file or reset to defaults is possible.
* Fix multi-initialization of derived SingletonMixin classes.
* Cleanup: parameters: extra=forbid, optimize: battery, inverter optional
* Don't allow extra fields for parameters/REST-API (at least for now while
changing API).
* Allow both battery and inverter to be set optionally (atm optional
battery not implemented, no API constraints).
* inverter: Remove default max_power_wh
* single_test_optimization: Add more cli-parameters
* Workflow docker-build: Don't try to authenticate for PRs
* Secrets are not available anyway for forks.
Add documentation that covers:
- configuration
- prediction
Add Python scripts that support automatic documentation generation for
configuration data defined with pydantic.
Adapt EOS configuration to provide more methods for REST API and
automatic documentation generation.
Adapt REST API to allow for EOS configuration file load and save.
Sort REST API on generation of openapi markdown for docs.
Move logutil to core/logging to allow configuration of logging by standard config.
Make Akkudoktor predictions always start extraction of prediction data at start of day.
Previously extraction started at actual hour. This is to support the code that assumes
prediction data to start at start of day.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* Inverter: Self consumption interpolator for better discharge_hour results
* Small penalty when EV 100% and charge >0
* Price Forceast (use mean of last 7 days instead of repeat)
* Price Prediction as JSON simulation output, config fixed electricty fees configurable + MyPy & Ruff
* Update utilities in utils submodule.
* Add base configuration modules.
* Add server base configuration modules.
* Add devices base configuration modules.
* Add optimization base configuration modules.
* Add utils base configuration modules.
* Add prediction abstract and base classes plus tests.
* Add PV forecast to prediction submodule.
The PV forecast modules are adapted from the class_pvforecast module and
replace it.
* Add weather forecast to prediction submodule.
The modules provide classes and methods to retrieve, manage, and process weather forecast data
from various sources. Includes are structured representations of weather data and utilities
for fetching forecasts for specific locations and time ranges.
BrightSky and ClearOutside are currently supported.
* Add electricity price forecast to prediction submodule.
* Adapt fastapi server to base config and add fasthtml server.
* Add ems to core submodule.
* Adapt genetic to config.
* Adapt visualize to config.
* Adapt common test fixtures to config.
* Add load forecast to prediction submodule.
* Add core abstract and base classes.
* Adapt single test optimization to config.
* Adapt devices to config.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
