EOS/single_test_prediction.py
Bobby Noelte 80bfe4d0f0
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Add a cyclic task that cleans the cache file store from outdated cache files.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

210 lines
6.2 KiB
Python

#!/usr/bin/env python3
import argparse
import cProfile
import pstats
import sys
import time
from akkudoktoreos.config.config import get_config
from akkudoktoreos.prediction.prediction import get_prediction
config_eos = get_config()
prediction_eos = get_prediction()
def config_pvforecast() -> dict:
"""Configure settings for PV forecast."""
settings = {
"general": {
"latitude": 52.52,
"longitude": 13.405,
},
"prediction": {
"hours": 48,
"historic_hours": 24,
},
"pvforecast": {
"provider": "PVForecastAkkudoktor",
"planes": [
{
"peakpower": 5.0,
"surface_azimuth": -10,
"surface_tilt": 7,
"userhorizon": [20, 27, 22, 20],
"inverter_paco": 10000,
},
{
"peakpower": 4.8,
"surface_azimuth": -90,
"surface_tilt": 7,
"userhorizon": [30, 30, 30, 50],
"inverter_paco": 10000,
},
{
"peakpower": 1.4,
"surface_azimuth": -40,
"surface_tilt": 60,
"userhorizon": [60, 30, 0, 30],
"inverter_paco": 2000,
},
{
"peakpower": 1.6,
"surface_azimuth": 5,
"surface_tilt": 45,
"userhorizon": [45, 25, 30, 60],
"inverter_paco": 1400,
},
],
},
}
return settings
def config_weather() -> dict:
"""Configure settings for weather forecast."""
settings = {
"general": {
"latitude": 52.52,
"longitude": 13.405,
},
"prediction": {
"hours": 48,
"historic_hours": 24,
},
"weather": dict(),
}
return settings
def config_elecprice() -> dict:
"""Configure settings for electricity price forecast."""
settings = {
"general": {
"latitude": 52.52,
"longitude": 13.405,
},
"prediction": {
"hours": 48,
"historic_hours": 24,
},
"elecprice": dict(),
}
return settings
def config_load() -> dict:
"""Configure settings for load forecast."""
settings = {
"general": {
"latitude": 52.52,
"longitude": 13.405,
},
"prediction": {
"hours": 48,
"historic_hours": 24,
},
}
return settings
def run_prediction(provider_id: str, verbose: bool = False) -> str:
"""Run the prediction.
Args:
provider_id (str): ID of prediction provider.
verbose (bool, optional): Whether to print verbose output. Defaults to False.
Returns:
dict: Prediction result as a dictionary
"""
# Initialize the oprediction
config_eos = get_config()
prediction_eos = get_prediction()
if provider_id in ("PVForecastAkkudoktor",):
settings = config_pvforecast()
forecast = "pvforecast"
elif provider_id in ("BrightSky", "ClearOutside"):
settings = config_weather()
forecast = "weather"
elif provider_id in ("ElecPriceAkkudoktor",):
settings = config_elecprice()
forecast = "elecprice"
elif provider_id in ("LoadAkkudoktor",):
settings = config_elecprice()
forecast = "load"
settings["load"]["loadakkudoktor_year_energy"] = 1000
else:
raise ValueError(f"Unknown provider '{provider_id}'.")
settings[forecast]["provider"] = provider_id
config_eos.merge_settings_from_dict(settings)
provider = prediction_eos.provider_by_id(provider_id)
prediction_eos.update_data()
# Return result of prediction
if verbose:
print(f"\nProvider ID: {provider.provider_id()}")
print("----------")
print("\nSettings\n----------")
print(settings)
print("\nProvider\n----------")
print(f"elecprice.provider: {config_eos.elecprice.provider}")
print(f"load.provider: {config_eos.load.provider}")
print(f"pvforecast.provider: {config_eos.pvforecast.provider}")
print(f"weather.provider: {config_eos.weather.provider}")
print(f"enabled: {provider.enabled()}")
for key in provider.record_keys:
print(f"\n{key}\n----------")
print(f"Array: {provider.key_to_array(key)}")
return provider.model_dump_json(indent=4)
def main():
"""Main function to run the optimization script with optional profiling."""
parser = argparse.ArgumentParser(description="Run Prediction")
parser.add_argument("--profile", action="store_true", help="Enable performance profiling")
parser.add_argument(
"--verbose", action="store_true", help="Enable verbose output during prediction"
)
parser.add_argument("--provider-id", type=str, default=0, help="Provider ID of prediction")
args = parser.parse_args()
if args.profile:
# Run with profiling
profiler = cProfile.Profile()
try:
result = profiler.runcall(
run_prediction, provider_id=args.provider_id, verbose=args.verbose
)
# Print profiling statistics
stats = pstats.Stats(profiler)
stats.strip_dirs().sort_stats("cumulative").print_stats(200)
# Print result
print("\nPrediction Result:")
print(result)
except Exception as e:
print(f"Error during prediction: {e}", file=sys.stderr)
sys.exit(1)
else:
# Run without profiling
try:
start_time = time.time()
result = run_prediction(provider_id=args.provider_id, verbose=args.verbose)
end_time = time.time()
elapsed_time = end_time - start_time
print(f"\nElapsed time: {elapsed_time:.4f} seconds.")
print("\nPrediction Result:")
print(result)
except Exception as e:
print(f"Error during prediction: {e}", file=sys.stderr)
sys.exit(1)
if __name__ == "__main__":
main()