Files
EOS/tests/test_elecpriceakkudoktor.py

229 lines
8.2 KiB
Python
Raw Normal View History

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
import asyncio
import json
from pathlib import Path
from unittest.mock import Mock, patch
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
import numpy as np
import pytest
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
import requests
from loguru import logger
Improve caching. (#431) * Move the caching module to core. Add an in memory cache that for caching function and method results during an energy management run (optimization run). Two decorators are provided for methods and functions. * Improve the file cache store by load and save functions. Make EOS load the cache file store on startup and save it on shutdown. Add a cyclic task that cleans the cache file store from outdated cache files. * Improve startup of EOSdash by EOS Make EOS starting EOSdash adhere to path configuration given in EOS. The whole environment from EOS is now passed to EOSdash. Should also prevent test errors due to unwanted/ wrong config file creation. Both servers now provide a health endpoint that can be used to detect whether the server is running. This is also used for testing now. * Improve startup of EOS EOS now has got an energy management task that runs shortly after startup. It tries to execute energy management runs with predictions newly fetched or initialized from cached data on first run. * Improve shutdown of EOS EOS has now a shutdown task that shuts EOS down gracefully with some time delay to allow REST API requests for shutdwon or restart to be fully serviced. * Improve EMS Add energy management task for repeated energy management controlled by startup delay and interval configuration parameters. Translate EnergieManagementSystem to english EnergyManagement. * Add administration endpoints - endpoints to control caching from REST API. - endpoints to control server restart (will not work on Windows) and shutdown from REST API * Improve doc generation Use "\n" linenend convention also on Windows when generating doc files. Replace Windows specific 127.0.0.1 address by standard 0.0.0.0. * Improve test support (to be able to test caching) - Add system test option to pytest for running tests with "real" resources - Add new test fixture to start server for test class and test function - Make kill signal adapt to Windows/ Linux - Use consistently "\n" for lineends when writing text files in doc test - Fix test_logging under Windows - Fix conftest config_default_dirs test fixture under Windows From @Lasall * Improve Windows support - Use 127.0.0.1 as default config host (model defaults) and addionally redirect 0.0.0.0 to localhost on Windows (because default config file still has 0.0.0.0). - Update install/startup instructions as package installation is required atm. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-02-12 21:35:51 +01:00
from akkudoktoreos.core.cache import CacheFileStore
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
from akkudoktoreos.core.coreabc import get_ems
from akkudoktoreos.prediction.elecpriceakkudoktor import (
AkkudoktorElecPrice,
AkkudoktorElecPriceValue,
ElecPriceAkkudoktor,
)
from akkudoktoreos.utils.datetimeutil import to_datetime
DIR_TESTDATA = Path(__file__).absolute().parent.joinpath("testdata")
FILE_TESTDATA_ELECPRICEAKKUDOKTOR_1_JSON = DIR_TESTDATA.joinpath(
"elecpriceforecast_akkudoktor_1.json"
)
@pytest.fixture
def provider(monkeypatch, config_eos):
"""Fixture to create a ElecPriceProvider instance."""
monkeypatch.setenv("EOS_ELECPRICE__ELECPRICE_PROVIDER", "ElecPriceAkkudoktor")
config_eos.reset_settings()
return ElecPriceAkkudoktor()
@pytest.fixture
def sample_akkudoktor_1_json():
"""Fixture that returns sample forecast data report."""
Improve caching. (#431) * Move the caching module to core. Add an in memory cache that for caching function and method results during an energy management run (optimization run). Two decorators are provided for methods and functions. * Improve the file cache store by load and save functions. Make EOS load the cache file store on startup and save it on shutdown. Add a cyclic task that cleans the cache file store from outdated cache files. * Improve startup of EOSdash by EOS Make EOS starting EOSdash adhere to path configuration given in EOS. The whole environment from EOS is now passed to EOSdash. Should also prevent test errors due to unwanted/ wrong config file creation. Both servers now provide a health endpoint that can be used to detect whether the server is running. This is also used for testing now. * Improve startup of EOS EOS now has got an energy management task that runs shortly after startup. It tries to execute energy management runs with predictions newly fetched or initialized from cached data on first run. * Improve shutdown of EOS EOS has now a shutdown task that shuts EOS down gracefully with some time delay to allow REST API requests for shutdwon or restart to be fully serviced. * Improve EMS Add energy management task for repeated energy management controlled by startup delay and interval configuration parameters. Translate EnergieManagementSystem to english EnergyManagement. * Add administration endpoints - endpoints to control caching from REST API. - endpoints to control server restart (will not work on Windows) and shutdown from REST API * Improve doc generation Use "\n" linenend convention also on Windows when generating doc files. Replace Windows specific 127.0.0.1 address by standard 0.0.0.0. * Improve test support (to be able to test caching) - Add system test option to pytest for running tests with "real" resources - Add new test fixture to start server for test class and test function - Make kill signal adapt to Windows/ Linux - Use consistently "\n" for lineends when writing text files in doc test - Fix test_logging under Windows - Fix conftest config_default_dirs test fixture under Windows From @Lasall * Improve Windows support - Use 127.0.0.1 as default config host (model defaults) and addionally redirect 0.0.0.0 to localhost on Windows (because default config file still has 0.0.0.0). - Update install/startup instructions as package installation is required atm. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
2025-02-12 21:35:51 +01:00
with FILE_TESTDATA_ELECPRICEAKKUDOKTOR_1_JSON.open(
"r", encoding="utf-8", newline=None
) as f_res:
input_data = json.load(f_res)
return input_data
@pytest.fixture
def cache_store():
"""A pytest fixture that creates a new CacheFileStore instance for testing."""
return CacheFileStore()
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
class TestElecPriceAkkudokor:
# ------------------------------------------------
# General forecast
# ------------------------------------------------
def test_singleton_instance(self, provider):
"""Test that ElecPriceForecast behaves as a singleton."""
another_instance = ElecPriceAkkudoktor()
assert provider is another_instance
def test_invalid_provider(self, provider, monkeypatch):
"""Test requesting an unsupported provider."""
monkeypatch.setenv("EOS_ELECPRICE__ELECPRICE_PROVIDER", "<invalid>")
provider.config.reset_settings()
assert not provider.enabled()
# ------------------------------------------------
# Akkudoktor
# ------------------------------------------------
@patch("akkudoktoreos.prediction.elecpriceakkudoktor.logger.error")
def test_validate_data_invalid_format(self, mock_logger, provider):
"""Test validation for invalid Akkudoktor data."""
invalid_data = '{"invalid": "data"}'
with pytest.raises(ValueError):
provider._validate_data(invalid_data)
mock_logger.assert_called_once_with(mock_logger.call_args[0][0])
@patch("requests.get")
def test_request_forecast(self, mock_get, provider, sample_akkudoktor_1_json):
"""Test requesting forecast from Akkudoktor."""
# Mock response object
mock_response = Mock()
mock_response.status_code = 200
mock_response.content = json.dumps(sample_akkudoktor_1_json)
mock_get.return_value = mock_response
# Test function
akkudoktor_data = provider._request_forecast()
assert isinstance(akkudoktor_data, AkkudoktorElecPrice)
assert akkudoktor_data.values[0].model_dump() == AkkudoktorElecPriceValue(
start_timestamp=1733785200000,
end_timestamp=1733788800000,
start="2024-12-09T23:00:00.000Z",
end="2024-12-10T00:00:00.000Z",
marketprice=92.85,
unit="Eur/MWh",
marketpriceEurocentPerKWh=9.29,
).model_dump()
@pytest.mark.asyncio
@patch("requests.get")
async def test_update_data(self, mock_get, provider, sample_akkudoktor_1_json, cache_store):
"""Test fetching forecast from Akkudoktor."""
# Mock response object
mock_response = Mock()
mock_response.status_code = 200
mock_response.content = json.dumps(sample_akkudoktor_1_json)
mock_get.return_value = mock_response
cache_store.clear(clear_all=True)
# Call the method
ems_eos = get_ems()
ems_eos.set_start_datetime(to_datetime("2024-12-11 00:00:00", in_timezone="Europe/Berlin"))
await provider.update_data(force_enable=True, force_update=True)
# Assert: Verify the result is as expected
mock_get.assert_called_once()
assert (
len(provider) == 73
) # we have 48 datasets in the api response, we want to know 48h into the future. The data we get has already 23h into the future so we need only 25h more. 48+25=73
# Assert we get hours prioce values by resampling
np_price_array = await provider.key_to_array(
key="elecprice_marketprice_wh",
start_datetime=provider.ems_start_datetime,
end_datetime=provider.end_datetime,
)
assert len(np_price_array) == provider.total_hours
# with open(FILE_TESTDATA_ELECPRICEAKKUDOKTOR_2_JSON, "w") as f_out:
# f_out.write(provider.to_json())
@pytest.mark.asyncio
@patch("requests.get")
async def test_update_data_with_incomplete_forecast(self, mock_get, provider):
"""Test `_update_data` with incomplete or missing forecast data."""
incomplete_data: dict = {"meta": {}, "values": []}
mock_response = Mock()
mock_response.status_code = 200
mock_response.content = json.dumps(incomplete_data)
mock_get.return_value = mock_response
logger.info("The following errors are intentional and part of the test.")
with pytest.raises(ValueError):
await provider._update_data(force_update=True)
@pytest.mark.parametrize(
"status_code, exception",
[(400, requests.exceptions.HTTPError), (500, requests.exceptions.HTTPError), (200, None)],
)
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
@patch("requests.get")
def test_request_forecast_status_codes(
self, mock_get, provider, sample_akkudoktor_1_json, status_code, exception
):
"""Test handling of various API status codes."""
mock_response = Mock()
mock_response.status_code = status_code
mock_response.content = json.dumps(sample_akkudoktor_1_json)
mock_response.raise_for_status.side_effect = (
requests.exceptions.HTTPError if exception else None
)
mock_get.return_value = mock_response
if exception:
with pytest.raises(exception):
provider._request_forecast()
else:
provider._request_forecast()
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
@pytest.mark.asyncio
@patch("requests.get")
@patch("akkudoktoreos.core.cache.CacheFileStore")
async def test_cache_integration(self, mock_cache, mock_get, provider, sample_akkudoktor_1_json):
"""Test caching of 8-day electricity price data."""
# Mock response object
mock_response = Mock()
mock_response.status_code = 200
mock_response.content = json.dumps(sample_akkudoktor_1_json)
mock_get.return_value = mock_response
# Mock cache object
mock_cache_instance = mock_cache.return_value
mock_cache_instance.get.return_value = None # Simulate no cache
await provider._update_data(force_update=True)
mock_cache_instance.create.assert_called_once()
mock_cache_instance.get.assert_called_once()
@pytest.mark.asyncio
async def test_key_to_array_resampling(self, provider):
"""Test resampling of forecast data to NumPy array."""
await provider.update_data(force_update=True)
array = await provider.key_to_array(
key="elecprice_marketprice_wh",
start_datetime=provider.ems_start_datetime,
end_datetime=provider.end_datetime,
)
assert isinstance(array, np.ndarray)
assert len(array) == provider.total_hours
# ------------------------------------------------
# Development Akkudoktor
# ------------------------------------------------
@pytest.mark.skip(reason="For development only")
def test_akkudoktor_development_forecast_data(self, provider):
"""Fetch data from real Akkudoktor server."""
# Preset, as this is usually done by update_data()
provider.ems_start_datetime = to_datetime("2024-10-26 00:00:00")
akkudoktor_data = provider._request_forecast()
with FILE_TESTDATA_ELECPRICEAKKUDOKTOR_1_JSON.open(
"w", encoding="utf-8", newline="\n"
) as f_out:
json.dump(akkudoktor_data, f_out, indent=4)