5 Commits

Include renames

Author	SHA1	Message	Date
Bobby NoelteandGitHub	1905682113	chore: adapt pdf visualization (#1205) ... Change PDF visualization to be created on demand and per optimization algorithm. The PDF for the GENETIC0 optimization is provided by the /visualization_results.pdf endpoint. There is no change in the interface. By this the optimization algorithm is offloaded from the PDF generation which spares some time. To cope with several users may call the /visualization_results.pdf endpoint at the same time the PDF is generated on the fly without any intermediate file taking the stored GENETIC0 solution as an input. SVG picture generation is removed as this would again create intermediate files. Chart pictures can easily be taken from the PDF. To allow on demand creation of the optimization results visualization the optimisation solution stored is extended by several new attributes. To keep the deprecated /optimize endpoint compatible the optimization solution is stripped to the legacy content before returned. Due to the extension of the solution the optimization tests were adapted to cover the extended content. The optimization tests are adapted to test the generated visualization report by the pypdf reader. Pypdf is added to the development dependencies. Besides the adaptation several fixes and improvements are added: * feat: extend /v1/prediction/series endpoint by resampling and filling Add parameters for resampling and filling. Add the processing parameter to control wether raw data or resampled data shall be returned. * feat: extend /v1/measurement/series endpoint by resampling and filling Add parameters for resampling and filling: Add the processing parameter to control wether raw data or resampled data shall be returned. * feat: standardize and improve API error response Use FASTApi exception handlers to provide a standardized API exception handling. All exceptions are logged. Exception traces are only returned if the new logging configuration parameter logging.api_logging_level is set to "DEBUG" or "TRACE". Avoids unwanted leackage of server internals on exceptions. * fix: align to intervall when resampling Ensure resampling is aligned to interval also when the buckets are shifted due to the align_to_intervall parameter is set. * chore: make dropna mandatory and default to True * chore: refactor key_to_xxx data management methods Make key_to_series the central method for data resampling and fill. Add a new key_to_raw_series to retrieve the data as it is stored (without resampling and filling). Users of key_to_series were mostly moved to key_to_raw_series as this resembles the former interface. Especially in predictions and tests this was done. * chore: create test data sub-directory for each optimization algorithm To prevent cluttering the test data directory and ease test data management for optimization algorithms each algorithm got it's own sub-directory. The current test data was moved to these sub-directories. * chore: update version Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>	2026-08-01 12:45:19 +02:00
Bobby NoelteandGitHub	8344974c16	chore: adapt deprecated endpoints to 15-minutes predictions (#1195) ... Ensure the deprecated endpoints get /strompreis, post /gesamtlast, get /gesamtlast_simple, get /pvforecast to work on 1-hour intervalls even if the prediction provides 15-minutes intervall data. This keeps the interface compliant to the legacy functionality. Besides this adaptations several other improvements and fixes are included in this PR. * feat: extend data management method key_to array by resample_method One can now define the resample method on how to aggregate the values in an interval for resampling. Three methods are provided: - "first": Use the first value in each interval. - "mean": Compute the arithmetic mean of all samples in each interval. - "interval_mean": Compute the time-weighted mean assuming each value remains valid until the next timestamp (piecewise-constant signal). * feat: extend the get /v1/prediction/dataframe endpoint with resampling parameters Make all parameters for resampling available at the endpoint. * feat: extend the get /v1/prediction/list endpoint with resampling parameters Make all parameters for resampling available at the endpoint. * feat: add new delete /v1/prediction/range endpoint The endpoint allows to delete prediction values for a given time span. * fix: adapt for PVForecastAkkudoktor server side cache handling /api.akkudoktor/forecast does it's own caching on requests. Call it with slightly randomized request values to avoid getting cached values in the case we need fresh data. The requests are anyway rate limited to one request per hour on our side. * chore: add core.types This module centralizes reusable type definitions shared across multiple packages. Defining common types here avoids duplication of complex type annotations (such as Literal aliases), ensures consistent typing across the code base, and helps prevent circular import dependencies between modules. * chore: extend cache testing * chore: add system test for deprecated /strompreis endpoint * chore: add unit test module for server endpoints Add a new test module to do unit tests on server endpoints. First test added for deprecated get /strompreis endpoint. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>	2026-07-30 19:54:05 +02:00
Bobby NoelteandGitHub	eb9e966de9	fix: move data management to async (#1015) ... FAstAPI is an async framework. Data may be imported and exported, load and save, set and get asynchronously. Prevent interleaving data operations to corrupt the data. In the previous design sync and async data access was intermixed leading to data corruption. The basic data classes DataSequence and DataContainer and the derived classes like Provider and Measurement now are async. Data access is protected by several async locks. To support the async design of the data classes the database interface became async. The energy management is also adapted to the new async design. Optimization is still off-loaded to another thread, but the prepration for the optimization and the post optimization actions now follow the async design. Adapter operations are now also protected by async locks. Tests were adapted to the async design and new tests were created. Besides this major fix several other improvements and fixes are included in this PR. * fix: key_to_dict/list/array only regard data records with key value set. Before the exclusion of no value data records was only done if the dropna flag was set. * fix: test for visual result pdf generation Due to updates in the library the generated charts text was a little bit different. Adapt the test to create the comaprison pdf in the test data durectory and update the reference pdf. * chore: Remove MutableMapping from DataSequence and DataContainer. Mutable Mapping does not fit to the now async design. * chore: Add NoDB database backend This backend implements the full database backend interface but performs no actual persistence. It is intended for configurations where database persistence is disabled (`provider=None`). * chore: Improve measurement data import testing with real world scenarios. Added two new endpoints to support testing. * chore: Add mermaid to supported documentation tools * chore: Add documentation about async design * chore: Add documentation about generic data handling Covers the basics of measurement and prediction time series data handling. * chore: Add empty lines around markdown lists. * chore: sync pre-commit config to updated package versions Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>	2026-07-15 16:38:53 +02:00
Bobby NoelteandGitHub	32e690becf	fix: EOS run asynchronous tasks (#904) ... Startup retention manager for asynchronous tasks. Handle gracefully exceptions in these tasks or the configuration for them. Remove tasks.py as repeated tasks are now handled by the retention manager. When running on GitHub, only the version date file is checked. The development tag is merely a label, so any date set during development suffices. The test_doc is also skipped on GitHub actions.	2026-02-24 23:17:11 +01:00
Bobby NoelteandGitHub	6498c7dc32	Add database support for measurements and historic prediction data. (#848) ... The database supports backend selection, compression, incremental data load, automatic data saving to storage, automatic vaccum and compaction. Make SQLite3 and LMDB database backends available. Update tests for new interface conventions regarding data sequences, data containers, data providers. This includes the measurements provider and the prediction providers. Add database documentation. The fix includes several bug fixes that are not directly related to the database implementation but are necessary to keep EOS running properly and to test and document the changes. * fix: config eos test setup Make the config_eos fixture generate a new instance of the config_eos singleton. Use correct env names to setup data folder path. * fix: startup with no config Make cache and measurements complain about missing data path configuration but do not bail out. * fix: soc data preparation and usage for genetic optimization. Search for soc measurments 48 hours around the optimization start time. Only clamp soc to maximum in battery device simulation. * fix: dashboard bailout on zero value solution display Do not use zero values to calculate the chart values adjustment for display. * fix: openapi generation script Make the script also replace data_folder_path and data_output_path to hide real (test) environment pathes. * feat: add make repeated task function make_repeated_task allows to wrap a function to be repeated cyclically. * chore: removed index based data sequence access Index based data sequence access does not make sense as the sequence can be backed by the database. The sequence is now purely time series data. * chore: refactor eos startup to avoid module import startup Avoid module import initialisation expecially of the EOS configuration. Config mutation, singleton initialization, logging setup, argparse parsing, background task definitions depending on config and environment-dependent behavior is now done at function startup. * chore: introduce retention manager A single long-running background task that owns the scheduling of all periodic server-maintenance jobs (cache cleanup, DB autosave, …) * chore: canonicalize timezone name for UTC Timezone names that are semantically identical to UTC are canonicalized to UTC. * chore: extend config file migration for default value handling Extend the config file migration handling values None or nonexisting values that will invoke a default value generation in the new config file. Also adapt test to handle this situation. * chore: extend datetime util test cases * chore: make version test check for untracked files Check for files that are not tracked by git. Version calculation will be wrong if these files will not be commited. * chore: bump pandas to 3.0.0 Pandas 3.0 now performs inference on the appropriate resolution (a.k.a. unit) for the output dtype which may become datetime64[us] (before it was ns). Also numeric dtype detection is now more strict which needs a different detection for numerics. * chore: bump pydantic-settings to 2.12.0 pydantic-settings 2.12.0 under pytest creates a different behaviour. The tests were adapted and a workaround was introduced. Also ConfigEOS was adapted to allow for fine grain initialization control to be able to switch off certain settings such as file settings during test. * chore: remove sci learn kit from dependencies The sci learn kit is not strictly necessary as long as we have scipy. * chore: add documentation mode guarding for sphinx autosummary Sphinx autosummary excecutes functions. Prevent exceptions in case of pure doc mode. * chore: adapt docker-build CI workflow to stricter GitHub handling Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>	2026-02-22 14:12:42 +01:00