#!/usr/bin/env python3
import argparse
import os
import subprocess
import sys
from contextlib import asynccontextmanager
from pathlib import Path
from typing import Annotated, Any, AsyncGenerator, Dict, List, Optional, Union
import httpx
import uvicorn
from fastapi import FastAPI, Query, Request
from fastapi.exceptions import HTTPException
from fastapi.responses import FileResponse, HTMLResponse, RedirectResponse, Response
from akkudoktoreos.config.config import ConfigEOS, SettingsEOS, get_config
from akkudoktoreos.core.ems import get_ems
from akkudoktoreos.core.logging import get_logger
from akkudoktoreos.core.pydantic import (
PydanticBaseModel,
PydanticDateTimeData,
PydanticDateTimeDataFrame,
PydanticDateTimeSeries,
)
from akkudoktoreos.measurement.measurement import get_measurement
from akkudoktoreos.optimization.genetic import (
OptimizationParameters,
OptimizeResponse,
optimization_problem,
)
from akkudoktoreos.prediction.prediction import get_prediction
from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
logger = get_logger(__name__)
config_eos = get_config()
measurement_eos = get_measurement()
prediction_eos = get_prediction()
ems_eos = get_ems()
# Command line arguments
args = None
ERROR_PAGE_TEMPLATE = """
Energy Optimization System (EOS) Error
STATUS_CODE
ERROR_TITLE
ERROR_MESSAGE
ERROR_DETAILS
Back to Home
"""
def create_error_page(
status_code: str, error_title: str, error_message: str, error_details: str
) -> str:
"""Create an error page by replacing placeholders in the template."""
return (
ERROR_PAGE_TEMPLATE.replace("STATUS_CODE", status_code)
.replace("ERROR_TITLE", error_title)
.replace("ERROR_MESSAGE", error_message)
.replace("ERROR_DETAILS", error_details)
)
# ----------------------
# EOSdash server startup
# ----------------------
def start_eosdash() -> subprocess.Popen:
"""Start the EOSdash server as a subprocess.
Returns:
server_process: The process of the EOSdash server
"""
eosdash_path = Path(__file__).parent.resolve().joinpath("eosdash.py")
if args is None:
# No command line arguments
host = config_eos.server_eosdash_host
port = config_eos.server_eosdash_port
eos_host = config_eos.server_eos_host
eos_port = config_eos.server_eos_port
log_level = "info"
access_log = False
reload = False
else:
host = args.host
port = config_eos.server_eosdash_port if config_eos.server_eosdash_port else (args.port + 1)
eos_host = args.host
eos_port = args.port
log_level = args.log_level
access_log = args.access_log
reload = args.reload
cmd = [
sys.executable,
str(eosdash_path),
"--host",
str(host),
"--port",
str(port),
"--eos-host",
str(eos_host),
"--eos-port",
str(eos_port),
"--log_level",
log_level,
"--access_log",
str(access_log),
"--reload",
str(reload),
]
server_process = subprocess.Popen(
cmd,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
)
return server_process
# ----------------------
# EOS REST Server
# ----------------------
@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
"""Lifespan manager for the app."""
# On startup
if config_eos.server_eos_startup_eosdash:
try:
eosdash_process = start_eosdash()
except Exception as e:
logger.error(f"Failed to start EOSdash server. Error: {e}")
sys.exit(1)
# Handover to application
yield
# On shutdown
# nothing to do
app = FastAPI(
title="Akkudoktor-EOS",
description="This project provides a comprehensive solution for simulating and optimizing an energy system based on renewable energy sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements), heat pumps, electric vehicles, and consideration of electricity price data, this system enables forecasting and optimization of energy flow and costs over a specified period.",
summary="Comprehensive solution for simulating and optimizing an energy system based on renewable energy sources",
version="0.0.1",
license_info={
"name": "Apache 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0.html",
},
lifespan=lifespan,
root_path=str(Path(__file__).parent),
)
# That's the problem
opt_class = optimization_problem(verbose=bool(config_eos.server_eos_verbose))
server_dir = Path(__file__).parent.resolve()
class PdfResponse(FileResponse):
media_type = "application/pdf"
@app.put("/v1/config/value")
def fastapi_config_value_put(
key: Annotated[str, Query(description="configuration key")],
value: Annotated[Any, Query(description="configuration value")],
) -> ConfigEOS:
"""Set the configuration option in the settings.
Args:
key (str): configuration key
value (Any): configuration value
Returns:
configuration (ConfigEOS): The current configuration after the write.
"""
if key not in config_eos.config_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
if key in config_eos.config_keys_read_only:
raise HTTPException(status_code=404, detail=f"Key '{key}' is read only.")
try:
setattr(config_eos, key, value)
except Exception as e:
raise HTTPException(status_code=400, detail=f"Error on update of configuration: {e}")
return config_eos
@app.post("/v1/config/update")
def fastapi_config_update_post() -> ConfigEOS:
"""Update the configuration from the EOS configuration file.
Returns:
configuration (ConfigEOS): The current configuration after update.
"""
try:
_, config_file_path = config_eos.from_config_file()
except:
raise HTTPException(
status_code=404,
detail=f"Cannot update configuration from file '{config_file_path}'.",
)
return config_eos
@app.get("/v1/config/file")
def fastapi_config_file_get() -> SettingsEOS:
"""Get the settings as defined by the EOS configuration file.
Returns:
settings (SettingsEOS): The settings defined by the EOS configuration file.
"""
try:
settings, config_file_path = config_eos.settings_from_config_file()
except:
raise HTTPException(
status_code=404,
detail=f"Cannot read configuration from file '{config_file_path}'.",
)
return settings
@app.put("/v1/config/file")
def fastapi_config_file_put() -> ConfigEOS:
"""Save the current configuration to the EOS configuration file.
Returns:
configuration (ConfigEOS): The current configuration that was saved.
"""
try:
config_eos.to_config_file()
except:
raise HTTPException(
status_code=404,
detail=f"Cannot save configuration to file '{config_eos.config_file_path}'.",
)
return config_eos
@app.get("/v1/config")
def fastapi_config_get() -> ConfigEOS:
"""Get the current configuration.
Returns:
configuration (ConfigEOS): The current configuration.
"""
return config_eos
@app.put("/v1/config")
def fastapi_config_put(
settings: Annotated[SettingsEOS, Query(description="settings")],
) -> ConfigEOS:
"""Write the provided settings into the current settings.
The existing settings are completely overwritten. Note that for any setting
value that is None, the configuration will fall back to values from other sources such as
environment variables, the EOS configuration file, or default values.
Args:
settings (SettingsEOS): The settings to write into the current settings.
Returns:
configuration (ConfigEOS): The current configuration after the write.
"""
try:
config_eos.merge_settings(settings, force=True)
except Exception as e:
raise HTTPException(status_code=400, detail=f"Error on update of configuration: {e}")
return config_eos
@app.get("/v1/measurement/keys")
def fastapi_measurement_keys_get() -> list[str]:
"""Get a list of available measurement keys."""
return sorted(measurement_eos.record_keys)
@app.get("/v1/measurement/load-mr/series/by-name")
def fastapi_measurement_load_mr_series_by_name_get(
name: Annotated[str, Query(description="Load name.")],
) -> PydanticDateTimeSeries:
"""Get the meter reading of given load name as series."""
key = measurement_eos.name_to_key(name=name, topic="measurement_load")
if key is None:
raise HTTPException(
status_code=404, detail=f"Measurement load with name '{name}' is not available."
)
if key not in measurement_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
pdseries = measurement_eos.key_to_series(key=key)
return PydanticDateTimeSeries.from_series(pdseries)
@app.put("/v1/measurement/load-mr/value/by-name")
def fastapi_measurement_load_mr_value_by_name_put(
datetime: Annotated[str, Query(description="Datetime.")],
name: Annotated[str, Query(description="Load name.")],
value: Union[float | str],
) -> PydanticDateTimeSeries:
"""Merge the meter reading of given load name and value into EOS measurements at given datetime."""
key = measurement_eos.name_to_key(name=name, topic="measurement_load")
if key is None:
raise HTTPException(
status_code=404, detail=f"Measurement load with name '{name}' is not available."
)
if key not in measurement_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
measurement_eos.update_value(datetime, key, value)
pdseries = measurement_eos.key_to_series(key=key)
return PydanticDateTimeSeries.from_series(pdseries)
@app.put("/v1/measurement/load-mr/series/by-name")
def fastapi_measurement_load_mr_series_by_name_put(
name: Annotated[str, Query(description="Load name.")], series: PydanticDateTimeSeries
) -> PydanticDateTimeSeries:
"""Merge the meter readings series of given load name into EOS measurements at given datetime."""
key = measurement_eos.name_to_key(name=name, topic="measurement_load")
if key is None:
raise HTTPException(
status_code=404, detail=f"Measurement load with name '{name}' is not available."
)
if key not in measurement_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
pdseries = series.to_series() # make pandas series from PydanticDateTimeSeries
measurement_eos.key_from_series(key=key, series=pdseries)
pdseries = measurement_eos.key_to_series(key=key)
return PydanticDateTimeSeries.from_series(pdseries)
@app.get("/v1/measurement/series")
def fastapi_measurement_series_get(
key: Annotated[str, Query(description="Prediction key.")],
) -> PydanticDateTimeSeries:
"""Get the measurements of given key as series."""
if key not in measurement_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
pdseries = measurement_eos.key_to_series(key=key)
return PydanticDateTimeSeries.from_series(pdseries)
@app.put("/v1/measurement/value")
def fastapi_measurement_value_put(
datetime: Annotated[str, Query(description="Datetime.")],
key: Annotated[str, Query(description="Prediction key.")],
value: Union[float | str],
) -> PydanticDateTimeSeries:
"""Merge the measurement of given key and value into EOS measurements at given datetime."""
if key not in measurement_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
measurement_eos.update_value(datetime, key, value)
pdseries = measurement_eos.key_to_series(key=key)
return PydanticDateTimeSeries.from_series(pdseries)
@app.put("/v1/measurement/series")
def fastapi_measurement_series_put(
key: Annotated[str, Query(description="Prediction key.")], series: PydanticDateTimeSeries
) -> PydanticDateTimeSeries:
"""Merge measurement given as series into given key."""
if key not in measurement_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
pdseries = series.to_series() # make pandas series from PydanticDateTimeSeries
measurement_eos.key_from_series(key=key, series=pdseries)
pdseries = measurement_eos.key_to_series(key=key)
return PydanticDateTimeSeries.from_series(pdseries)
@app.put("/v1/measurement/dataframe")
def fastapi_measurement_dataframe_put(data: PydanticDateTimeDataFrame) -> None:
"""Merge the measurement data given as dataframe into EOS measurements."""
dataframe = data.to_dataframe()
measurement_eos.import_from_dataframe(dataframe)
@app.put("/v1/measurement/data")
def fastapi_measurement_data_put(data: PydanticDateTimeData) -> None:
"""Merge the measurement data given as datetime data into EOS measurements."""
datetimedata = data.to_dict()
measurement_eos.import_from_dict(datetimedata)
@app.get("/v1/prediction/keys")
def fastapi_prediction_keys_get() -> list[str]:
"""Get a list of available prediction keys."""
return sorted(prediction_eos.record_keys)
@app.get("/v1/prediction/series")
def fastapi_prediction_series_get(
key: Annotated[str, Query(description="Prediction key.")],
start_datetime: Annotated[
Optional[str],
Query(description="Starting datetime (inclusive)."),
] = None,
end_datetime: Annotated[
Optional[str],
Query(description="Ending datetime (exclusive)."),
] = None,
) -> PydanticDateTimeSeries:
"""Get prediction for given key within given date range as series.
Args:
key (str): Prediction key
start_datetime (Optional[str]): Starting datetime (inclusive).
Defaults to start datetime of latest prediction.
end_datetime (Optional[str]: Ending datetime (exclusive).
Defaults to end datetime of latest prediction.
"""
if key not in prediction_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
if start_datetime is None:
start_datetime = prediction_eos.start_datetime
else:
start_datetime = to_datetime(start_datetime)
if end_datetime is None:
end_datetime = prediction_eos.end_datetime
else:
end_datetime = to_datetime(end_datetime)
pdseries = prediction_eos.key_to_series(
key=key, start_datetime=start_datetime, end_datetime=end_datetime
)
return PydanticDateTimeSeries.from_series(pdseries)
@app.get("/v1/prediction/list")
def fastapi_prediction_list_get(
key: Annotated[str, Query(description="Prediction key.")],
start_datetime: Annotated[
Optional[str],
Query(description="Starting datetime (inclusive)."),
] = None,
end_datetime: Annotated[
Optional[str],
Query(description="Ending datetime (exclusive)."),
] = None,
interval: Annotated[
Optional[str],
Query(description="Time duration for each interval."),
] = None,
) -> List[Any]:
"""Get prediction for given key within given date range as value list.
Args:
key (str): Prediction key
start_datetime (Optional[str]): Starting datetime (inclusive).
Defaults to start datetime of latest prediction.
end_datetime (Optional[str]: Ending datetime (exclusive).
Defaults to end datetime of latest prediction.
interval (Optional[str]): Time duration for each interval.
Defaults to 1 hour.
"""
if key not in prediction_eos.record_keys:
raise HTTPException(status_code=404, detail=f"Key '{key}' is not available.")
if start_datetime is None:
start_datetime = prediction_eos.start_datetime
else:
start_datetime = to_datetime(start_datetime)
if end_datetime is None:
end_datetime = prediction_eos.end_datetime
else:
end_datetime = to_datetime(end_datetime)
if interval is None:
interval = to_duration("1 hour")
else:
interval = to_duration(interval)
prediction_list = prediction_eos.key_to_array(
key=key,
start_datetime=start_datetime,
end_datetime=end_datetime,
interval=interval,
).tolist()
return prediction_list
@app.post("/v1/prediction/update")
def fastapi_prediction_update(force_update: bool = False, force_enable: bool = False) -> Response:
"""Update predictions for all providers.
Args:
force_update: Update data even if it is already cached.
Defaults to False.
force_enable: Update data even if provider is disabled.
Defaults to False.
"""
try:
prediction_eos.update_data(force_update=force_update, force_enable=force_enable)
except Exception as e:
raise HTTPException(status_code=400, detail=f"Error on update of provider: {e}")
return Response()
@app.post("/v1/prediction/update/{provider_id}")
def fastapi_prediction_update_provider(
provider_id: str, force_update: Optional[bool] = False, force_enable: Optional[bool] = False
) -> Response:
"""Update predictions for given provider ID.
Args:
provider_id: ID of provider to update.
force_update: Update data even if it is already cached.
Defaults to False.
force_enable: Update data even if provider is disabled.
Defaults to False.
"""
try:
provider = prediction_eos.provider_by_id(provider_id)
except ValueError:
raise HTTPException(status_code=404, detail=f"Provider '{provider_id}' not found.")
try:
provider.update_data(force_update=force_update, force_enable=force_enable)
except Exception as e:
raise HTTPException(status_code=400, detail=f"Error on update of provider: {e}")
return Response()
@app.get("/strompreis")
def fastapi_strompreis() -> list[float]:
"""Deprecated: Electricity Market Price Prediction per Wh (€/Wh).
Electricity prices start at 00.00.00 today and are provided for 48 hours.
If no prices are available the missing ones at the start of the series are
filled with the first available price.
Note:
Electricity price charges are added.
Note:
Set ElecPriceAkkudoktor as elecprice_provider, then update data with
'/v1/prediction/update'
and then request data with
'/v1/prediction/list?key=elecprice_marketprice_wh' or
'/v1/prediction/list?key=elecprice_marketprice_kwh' instead.
"""
settings = SettingsEOS(
elecprice_provider="ElecPriceAkkudoktor",
)
config_eos.merge_settings(settings=settings)
ems_eos.set_start_datetime() # Set energy management start datetime to current hour.
# Create electricity price forecast
prediction_eos.update_data(force_update=True)
# Get the current date and the end date based on prediction hours
# Fetch prices for the specified date range
start_datetime = to_datetime().start_of("day")
end_datetime = start_datetime.add(days=2)
try:
elecprice = prediction_eos.key_to_array(
key="elecprice_marketprice_wh",
start_datetime=start_datetime,
end_datetime=end_datetime,
).tolist()
except Exception as e:
raise HTTPException(
status_code=404,
detail=f"Can not get the electricity price forecast: {e}. Did you configure the electricity price forecast provider?",
)
return elecprice
class GesamtlastRequest(PydanticBaseModel):
year_energy: float
measured_data: List[Dict[str, Any]]
hours: int
@app.post("/gesamtlast")
def fastapi_gesamtlast(request: GesamtlastRequest) -> list[float]:
"""Deprecated: Total Load Prediction with adjustment.
Endpoint to handle total load prediction adjusted by latest measured data.
Total load prediction starts at 00.00.00 today and is provided for 48 hours.
If no prediction values are available the missing ones at the start of the series are
filled with the first available prediction value.
Note:
Use '/v1/prediction/list?key=load_mean_adjusted' instead.
Load energy meter readings to be added to EOS measurement by:
'/v1/measurement/load-mr/value/by-name' or
'/v1/measurement/value'
"""
settings = SettingsEOS(
prediction_hours=request.hours,
load_provider="LoadAkkudoktor",
loadakkudoktor_year_energy=request.year_energy,
)
config_eos.merge_settings(settings=settings)
ems_eos.set_start_datetime() # Set energy management start datetime to current hour.
# Insert measured data into EOS measurement
# Convert from energy per interval to dummy energy meter readings
measurement_key = "measurement_load0_mr"
measurement_eos.key_delete_by_datetime(key=measurement_key) # delete all load0_mr measurements
energy = {}
try:
for data_dict in request.measured_data:
dt_str = to_datetime(data_dict["time"], as_string=True)
value = float(data_dict["Last"])
energy[dt_str] = value
except Exception as e:
raise HTTPException(
status_code=404,
detail=f"Invalid measured data: {e}.",
)
energy_mr_dates = []
energy_mr_values = []
energy_mr = 0.0
for i, key in enumerate(sorted(energy)):
energy_mr += energy[key]
dt = to_datetime(key)
if i == 0:
# first element, add start value before
dt_before = dt - to_duration("1 hour")
energy_mr_dates.append(dt_before)
energy_mr_values.append(0.0)
energy_mr_dates.append(dt)
energy_mr_values.append(energy_mr)
measurement_eos.key_from_lists(measurement_key, energy_mr_dates, energy_mr_values)
# Create load forecast
prediction_eos.update_data(force_update=True)
# Get the forcast starting at start of day
start_datetime = to_datetime().start_of("day")
end_datetime = start_datetime.add(days=2)
try:
prediction_list = prediction_eos.key_to_array(
key="load_mean_adjusted",
start_datetime=start_datetime,
end_datetime=end_datetime,
).tolist()
except Exception as e:
raise HTTPException(
status_code=404,
detail=f"Can not get the total load forecast: {e}. Did you configure the load forecast provider?",
)
return prediction_list
@app.get("/gesamtlast_simple")
def fastapi_gesamtlast_simple(year_energy: float) -> list[float]:
"""Deprecated: Total Load Prediction.
Endpoint to handle total load prediction.
Total load prediction starts at 00.00.00 today and is provided for 48 hours.
If no prediction values are available the missing ones at the start of the series are
filled with the first available prediction value.
Args:
year_energy (float): Yearly energy consumption in Wh.
Note:
Set LoadAkkudoktor as load_provider, then update data with
'/v1/prediction/update'
and then request data with
'/v1/prediction/list?key=load_mean' instead.
"""
settings = SettingsEOS(
load_provider="LoadAkkudoktor",
loadakkudoktor_year_energy=year_energy / 1000, # Convert to kWh
)
config_eos.merge_settings(settings=settings)
ems_eos.set_start_datetime() # Set energy management start datetime to current hour.
# Create load forecast
prediction_eos.update_data(force_update=True)
# Get the forcast starting at start of day
start_datetime = to_datetime().start_of("day")
end_datetime = start_datetime.add(days=2)
try:
prediction_list = prediction_eos.key_to_array(
key="load_mean",
start_datetime=start_datetime,
end_datetime=end_datetime,
).tolist()
except Exception as e:
raise HTTPException(
status_code=404,
detail=f"Can not get the total load forecast: {e}. Did you configure the load forecast provider?",
)
return prediction_list
class ForecastResponse(PydanticBaseModel):
temperature: list[Optional[float]]
pvpower: list[float]
@app.get("/pvforecast")
def fastapi_pvforecast() -> ForecastResponse:
"""Deprecated: PV Forecast Prediction.
Endpoint to handle PV forecast prediction.
PVForecast starts at 00.00.00 today and is provided for 48 hours.
If no forecast values are available the missing ones at the start of the series are
filled with the first available forecast value.
Note:
Set PVForecastAkkudoktor as pvforecast_provider, then update data with
'/v1/prediction/update'
and then request data with
'/v1/prediction/list?key=pvforecast_ac_power' and
'/v1/prediction/list?key=pvforecastakkudoktor_temp_air' instead.
"""
settings = SettingsEOS(
elecprice_provider="PVForecastAkkudoktor",
)
config_eos.merge_settings(settings=settings)
ems_eos.set_start_datetime() # Set energy management start datetime to current hour.
# Create PV forecast
prediction_eos.update_data(force_update=True)
# Get the forcast starting at start of day
start_datetime = to_datetime().start_of("day")
end_datetime = start_datetime.add(days=2)
try:
ac_power = prediction_eos.key_to_array(
key="pvforecast_ac_power",
start_datetime=start_datetime,
end_datetime=end_datetime,
).tolist()
temp_air = prediction_eos.key_to_array(
key="pvforecastakkudoktor_temp_air",
start_datetime=start_datetime,
end_datetime=end_datetime,
).tolist()
except Exception as e:
raise HTTPException(
status_code=404,
detail=f"Can not get the PV forecast: {e}. Did you configure the PV forecast provider?",
)
# Return both forecasts as a JSON response
return ForecastResponse(temperature=temp_air, pvpower=ac_power)
@app.post("/optimize")
def fastapi_optimize(
parameters: OptimizationParameters,
start_hour: Annotated[
Optional[int], Query(description="Defaults to current hour of the day.")
] = None,
) -> OptimizeResponse:
if start_hour is None:
start_hour = to_datetime().hour
# TODO: Remove when config and prediction update is done by EMS.
config_eos.update()
prediction_eos.update_data()
# Perform optimization simulation
result = opt_class.optimierung_ems(parameters=parameters, start_hour=start_hour)
# print(result)
return result
@app.get("/visualization_results.pdf", response_class=PdfResponse)
def get_pdf() -> PdfResponse:
# Endpoint to serve the generated PDF with visualization results
output_path = config_eos.data_output_path
if output_path is None or not output_path.is_dir():
raise HTTPException(status_code=404, detail=f"Output path does not exist: {output_path}.")
file_path = output_path / "visualization_results.pdf"
if not file_path.is_file():
raise HTTPException(status_code=404, detail="No visualization result available.")
return PdfResponse(file_path)
@app.get("/site-map", include_in_schema=False)
def site_map() -> RedirectResponse:
return RedirectResponse(url="/docs")
# Keep the proxy last to handle all requests that are not taken by the Rest API.
@app.delete("/{path:path}", include_in_schema=False)
async def proxy_delete(request: Request, path: str) -> Response:
return await proxy(request, path)
@app.get("/{path:path}", include_in_schema=False)
async def proxy_get(request: Request, path: str) -> Response:
return await proxy(request, path)
@app.post("/{path:path}", include_in_schema=False)
async def proxy_post(request: Request, path: str) -> Response:
return await proxy(request, path)
@app.put("/{path:path}", include_in_schema=False)
async def proxy_put(request: Request, path: str) -> Response:
return await proxy(request, path)
async def proxy(request: Request, path: str) -> Union[Response | RedirectResponse | HTMLResponse]:
if config_eos.server_eosdash_host and config_eos.server_eosdash_port:
# Proxy to EOSdash server
url = f"http://{config_eos.server_eosdash_host}:{config_eos.server_eosdash_port}/{path}"
headers = dict(request.headers)
data = await request.body()
try:
async with httpx.AsyncClient() as client:
if request.method == "GET":
response = await client.get(url, headers=headers)
elif request.method == "POST":
response = await client.post(url, headers=headers, content=data)
elif request.method == "PUT":
response = await client.put(url, headers=headers, content=data)
elif request.method == "DELETE":
response = await client.delete(url, headers=headers, content=data)
except Exception as e:
error_page = create_error_page(
status_code="404",
error_title="Page Not Found",
error_message=f"""
EOSdash server not reachable: '{url}'
Did you start the EOSdash server
or set 'server_eos_startup_eosdash'?
If there is no application server intended please
set 'server_eosdash_host' or 'server_eosdash_port' to None.
""",
error_details=f"{e}",
)
return HTMLResponse(content=error_page, status_code=404)
return Response(
content=response.content,
status_code=response.status_code,
headers=dict(response.headers),
)
else:
# Redirect the root URL to the site map
return RedirectResponse(url="/docs")
def run_eos(host: str, port: int, log_level: str, access_log: bool, reload: bool) -> None:
"""Run the EOS server with the specified configurations.
This function starts the EOS server using the Uvicorn ASGI server. It accepts
arguments for the host, port, log level, access log, and reload options. The
log level is converted to lowercase to ensure compatibility with Uvicorn's
expected log level format. If an error occurs while attempting to bind the
server to the specified host and port, an error message is logged and the
application exits.
Parameters:
host (str): The hostname to bind the server to.
port (int): The port number to bind the server to.
log_level (str): The log level for the server. Options include "critical", "error",
"warning", "info", "debug", and "trace".
access_log (bool): Whether to enable or disable the access log. Set to True to enable.
reload (bool): Whether to enable or disable auto-reload. Set to True for development.
Returns:
None
"""
# Make hostname Windows friendly
if host == "0.0.0.0" and os.name == "nt":
host = "localhost"
try:
uvicorn.run(
"akkudoktoreos.server.eos:app",
host=host,
port=port,
log_level=log_level.lower(), # Convert log_level to lowercase
access_log=access_log,
reload=reload,
)
except Exception as e:
logger.error(f"Could not bind to host {host}:{port}. Error: {e}")
raise e
def main() -> None:
"""Parse command-line arguments and start the EOS server with the specified options.
This function sets up the argument parser to accept command-line arguments for
host, port, log_level, access_log, and reload. It uses default values from the
config_eos module if arguments are not provided. After parsing the arguments,
it starts the EOS server with the specified configurations.
Command-line Arguments:
--host (str): Host for the EOS server (default: value from config_eos).
--port (int): Port for the EOS server (default: value from config_eos).
--log_level (str): Log level for the server. Options: "critical", "error", "warning", "info", "debug", "trace" (default: "info").
--access_log (bool): Enable or disable access log. Options: True or False (default: False).
--reload (bool): Enable or disable auto-reload. Useful for development. Options: True or False (default: False).
"""
parser = argparse.ArgumentParser(description="Start EOS server.")
# Host and port arguments with defaults from config_eos
parser.add_argument(
"--host",
type=str,
default=str(config_eos.server_eos_host),
help="Host for the EOS server (default: value from config_eos)",
)
parser.add_argument(
"--port",
type=int,
default=config_eos.server_eos_port,
help="Port for the EOS server (default: value from config_eos)",
)
# Optional arguments for log_level, access_log, and reload
parser.add_argument(
"--log_level",
type=str,
default="info",
help='Log level for the server. Options: "critical", "error", "warning", "info", "debug", "trace" (default: "info")',
)
parser.add_argument(
"--access_log",
type=bool,
default=False,
help="Enable or disable access log. Options: True or False (default: True)",
)
parser.add_argument(
"--reload",
type=bool,
default=False,
help="Enable or disable auto-reload. Useful for development. Options: True or False (default: False)",
)
args = parser.parse_args()
try:
run_eos(args.host, args.port, args.log_level, args.access_log, args.reload)
except:
exit(1)
if __name__ == "__main__":
main()