* 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.
* Add EOS_CONFIG_DIR to set config dir (relative path to EOS_DIR or
absolute path).
- config_folder_path read-only
- config_file_path read-only
* Default values to support app start with empty config:
- latitude/longitude (Berlin)
- optimization_ev_available_charge_rates_percent (null, so model
default value is used)
- Enable Akkudoktor electricity price forecast (docker-compose).
* Fix some endpoints (empty data, remove unused params, fix types).
* cacheutil: Use cache dir. Closes#240
* Support EOS_LOGGING_LEVEL environment variable to set log level.
* tests: All tests use separate temporary config
- Add pytest switch --check-config-side-effect to check user
config file existence after each test. Will also fail if user config
existed before test execution (but will only check after the test has
run).
Enable flag in github workflow.
- Globally mock platformdirs in config module. Now no longer required
to patch individually.
Function calls to config instance (e.g. merge_settings_from_dict)
were unaffected previously.
* Set Berlin as default location (default config/docker-compose).
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>
* 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>
* Integrated single_test_optimization into pytest to run a basic optimization test with tolerance set to 1e-6, ensuring quick detection of deviations.
* Added a long-run test (400 generations, like single_test_optimization), which can be triggered using --full-run in pytest.
* Mocked PDF creation in optimization tests and added a new PDF generation test with image comparison validation.
Note: Current tolerance is set to 1e-6; feedback on whether this tolerance is tight enough is welcome.
---------
Co-authored-by: Normann <github@koldrack.com>
Co-authored-by: Michael Osthege <michael.osthege@outlook.com>
