Rename FastAPI server to `eos` and FastHTML server to `eosdash`.
Make an user easily identify what server is meant. FastAPI and FastHTML are
implementation details that may confuse the non-technical user.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
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>
Normalize electricity price prediction to €/Wh.
Provide electricity price prediction by €/kWh for convenience.
Allow to configure electricity price charges by €/kWh.
Also added error page to fastapi rest server to get rid of annoying
unrelated fault messages during testing.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* 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).
* 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
Extend single_test_optimization.py to be able to use real world data from new prediction classes.
- .venv/bin/python single_test_optimization.py --real_world --verbose
Can also be run with profiling "--profile".
Add single_test_prediction.py to fetch predictions from remote prediction providers
- .venv/bin/python single_test_prediction.py --verbose --provider-id PVForecastAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id LoadAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id ElecPriceAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id BrightSky | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id ClearOutside | more
Can also be run with profiling "--profile".
single_test_optimization.py is an example on how to retrieve prediction data for optimization and
use it to set up the optimization parameters.
Changes:
- load: Only one load provider at a time (vs. 5 before)
Bug fixes:
- prediction: only use providers that are enabled to retrieve or set data.
- prediction: fix pre pendulum format strings
- dataabc: Prevent error when resampling data with no datasets.
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>
* Migrate from Flask to FastAPI
* FastAPI migration:
- Use pydantic model classes as input parameters to the
data/calculation classes.
- Interface field names changed to constructor parameter names (for
simplicity only during transition, should be updated in a followup
PR).
- Add basic interface requirements (e.g. some values > 0, etc.).
* Update tests for new data format.
* Python requirement down to 3.9 (TypeGuard no longer needed)
* Makefile: Add helpful targets (e.g. development server with reload)
* Move API doc from README to pydantic model classes (swagger)
* Link to swagger.io with own openapi.yml.
* Commit openapi.json and check with pytest for changes so the
documentation is always up-to-date.
* Streamline docker
* FastAPI: Run startup action on dev server
* Fix config for /strompreis, endpoint still broken however.
* test_openapi: Compare against docs/.../openapi.json
* Move fastapi to server/ submodule
* See #187 for new repository structure.
