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Json configuration (#141)

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* Add json config
* Adjust code to new config

---------

Co-authored-by: Chris <git@nootch.de>
This commit is contained in:
Chris
2024-11-11 21:38:13 +01:00
committed by GitHub
parent fc74cde56f
commit ed3226e522
21 changed files with 726 additions and 171 deletions
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9
src/akkudoktoreos/class_ems.py
View File

@@ -3,12 +3,13 @@ from typing import Dict, List, Optional, Union
import numpy as np
from akkudoktoreos.config import prediction_hours
from akkudoktoreos.config import EOSConfig
class EnergieManagementSystem:
def __init__(
self,
config: EOSConfig,
pv_prognose_wh: Optional[np.ndarray] = None,
strompreis_euro_pro_wh: Optional[np.ndarray] = None,
einspeiseverguetung_euro_pro_wh: Optional[np.ndarray] = None,
@@ -25,9 +26,9 @@ class EnergieManagementSystem:
self.eauto = eauto
self.haushaltsgeraet = haushaltsgeraet
self.wechselrichter = wechselrichter
self.ac_charge_hours = np.full(prediction_hours, 0)
self.dc_charge_hours = np.full(prediction_hours, 1)
self.ev_charge_hours = np.full(prediction_hours, 0)
self.ac_charge_hours = np.full(config.prediction_hours, 0)
self.dc_charge_hours = np.full(config.prediction_hours, 1)
self.ev_charge_hours = np.full(config.prediction_hours, 0)
def set_akku_discharge_hours(self, ds: List[int]) -> None:
self.akku.set_discharge_per_hour(ds)

51
src/akkudoktoreos/class_optimize.py
View File

@@ -8,25 +8,24 @@ from akkudoktoreos.class_akku import PVAkku
from akkudoktoreos.class_ems import EnergieManagementSystem
from akkudoktoreos.class_haushaltsgeraet import Haushaltsgeraet
from akkudoktoreos.class_inverter import Wechselrichter
from akkudoktoreos.config import possible_ev_charge_currents
from akkudoktoreos.config import AppConfig
from akkudoktoreos.visualize import visualisiere_ergebnisse
class optimization_problem:
def __init__(
self,
prediction_hours: int = 48,
strafe: float = 10,
optimization_hours: int = 24,
config: AppConfig,
verbose: bool = False,
fixed_seed: Optional[int] = None,
):
"""Initialize the optimization problem with the required parameters."""
self.prediction_hours = prediction_hours
self.strafe = strafe
self._config = config
self.prediction_hours = config.eos.prediction_hours
self.strafe = config.eos.penalty
self.opti_param = None
self.fixed_eauto_hours = prediction_hours - optimization_hours
self.possible_charge_values = possible_ev_charge_currents
self.fixed_eauto_hours = config.eos.prediction_hours - config.eos.optimization_hours
self.possible_charge_values = config.eos.available_charging_rates_in_percentage
self.verbose = verbose
self.fix_seed = fixed_seed
self.optimize_ev = True
@@ -210,7 +209,10 @@ class optimization_problem:
if self.optimize_ev:
self.toolbox.register(
"attr_ev_charge_index", random.randint, 0, len(possible_ev_charge_currents) - 1
"attr_ev_charge_index",
random.randint,
0,
len(self._config.eos.available_charging_rates_in_percentage) - 1,
)
self.toolbox.register("attr_int", random.randint, start_hour, 23)
@@ -236,7 +238,7 @@ class optimization_problem:
"mutate_ev_charge_index",
tools.mutUniformInt,
low=0,
up=len(possible_ev_charge_currents) - 1,
up=len(self._config.eos.available_charging_rates_in_percentage) - 1,
indpb=0.2,
)
# - Start hour mutation for household devices
@@ -271,7 +273,8 @@ class optimization_problem:
if self.optimize_ev:
eautocharge_hours_float = [
possible_ev_charge_currents[i] for i in eautocharge_hours_index
self._config.eos.available_charging_rates_in_percentage[i]
for i in eautocharge_hours_index
]
ems.set_ev_charge_hours(eautocharge_hours_float)
else:
@@ -420,6 +423,7 @@ class optimization_problem:
# Initialize the inverter and energy management system
wr = Wechselrichter(10000, akku)
ems = EnergieManagementSystem(
config=self._config.eos,
gesamtlast=parameter["gesamtlast"],
pv_prognose_wh=parameter["pv_forecast"],
strompreis_euro_pro_wh=parameter["strompreis_euro_pro_wh"],
@@ -444,23 +448,24 @@ class optimization_problem:
)
if self.optimize_ev:
eautocharge_hours_float = [
possible_ev_charge_currents[i] for i in eautocharge_hours_float
self._config.eos.available_charging_rates_in_percentage[i]
for i in eautocharge_hours_float
]
ac_charge, dc_charge, discharge = self.decode_charge_discharge(discharge_hours_bin)
# Visualize the results
visualisiere_ergebnisse(
parameter["gesamtlast"],
parameter["pv_forecast"],
parameter["strompreis_euro_pro_wh"],
o,
ac_charge,
dc_charge,
discharge,
parameter["temperature_forecast"],
start_hour,
self.prediction_hours,
einspeiseverguetung_euro_pro_wh,
gesamtlast=parameter["gesamtlast"],
pv_forecast=parameter["pv_forecast"],
strompreise=parameter["strompreis_euro_pro_wh"],
ergebnisse=o,
ac=ac_charge,
dc=dc_charge,
discharge=discharge,
temperature=parameter["temperature_forecast"],
start_hour=start_hour,
einspeiseverguetung_euro_pro_wh=einspeiseverguetung_euro_pro_wh,
config=self._config,
extra_data=extra_data,
)

46
src/akkudoktoreos/class_strompreis.py
View File

@@ -1,12 +1,14 @@
import hashlib
import json
import os
import zoneinfo
from datetime import datetime, timedelta, timezone
from pathlib import Path
import numpy as np
import requests
from akkudoktoreos.config import AppConfig, SetupIncomplete
def repeat_to_shape(array, target_shape):
# Check if the array fits the target shape
@@ -23,53 +25,57 @@ def repeat_to_shape(array, target_shape):
class HourlyElectricityPriceForecast:
def __init__(
self, source, cache_dir="cache", charges=0.000228, prediction_hours=24, cache=True
self, source: str | Path, config: AppConfig, charges=0.000228, use_cache=True
): # 228
self.cache_dir = cache_dir
self.cache = cache
os.makedirs(self.cache_dir, exist_ok=True)
self.cache_time_file = os.path.join(self.cache_dir, "cache_timestamp.txt")
self.cache_dir = config.working_dir / config.directories.cache
self.use_cache = use_cache
if not self.cache_dir.is_dir():
raise SetupIncomplete(f"Output path does not exist: {self.cache_dir}.")
self.cache_time_file = self.cache_dir / "cache_timestamp.txt"
self.prices = self.load_data(source)
self.charges = charges
self.prediction_hours = prediction_hours
self.prediction_hours = config.eos.prediction_hours
def load_data(self, source):
cache_filename = self.get_cache_filename(source)
if source.startswith("http"):
if os.path.exists(cache_filename) and not self.is_cache_expired() and self.cache:
def load_data(self, source: str | Path):
cache_file = self.get_cache_file(source)
if isinstance(source, str):
if cache_file.is_file() and not self.is_cache_expired() and self.use_cache:
print("Loading data from cache...")
with open(cache_filename, "r") as file:
with cache_file.open("r") as file:
json_data = json.load(file)
else:
print("Loading data from the URL...")
response = requests.get(source)
if response.status_code == 200:
json_data = response.json()
with open(cache_filename, "w") as file:
with cache_file.open("w") as file:
json.dump(json_data, file)
self.update_cache_timestamp()
else:
raise Exception(f"Error fetching data: {response.status_code}")
else:
with open(source, "r") as file:
elif source.is_file():
with source.open("r") as file:
json_data = json.load(file)
else:
raise ValueError(f"Input is not a valid path: {source}")
return json_data["values"]
def get_cache_filename(self, url):
def get_cache_file(self, url):
hash_object = hashlib.sha256(url.encode())
hex_dig = hash_object.hexdigest()
return os.path.join(self.cache_dir, f"cache_{hex_dig}.json")
return self.cache_dir / f"cache_{hex_dig}.json"
def is_cache_expired(self):
if not os.path.exists(self.cache_time_file):
if not self.cache_time_file.is_file():
return True
with open(self.cache_time_file, "r") as file:
with self.cache_time_file.open("r") as file:
timestamp_str = file.read()
last_cache_time = datetime.strptime(timestamp_str, "%Y-%m-%d %H:%M:%S")
return datetime.now() - last_cache_time > timedelta(hours=1)
def update_cache_timestamp(self):
with open(self.cache_time_file, "w") as file:
with self.cache_time_file.open("w") as file:
file.write(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
def get_price_for_date(self, date_str):

304
src/akkudoktoreos/config.py
View File

@@ -1,30 +1,290 @@
"""This module provides functionality to manage and handle configuration for the EOS system.
The module including loading, merging, and validating JSON configuration files.
It also provides utility functions for working directory setup and date handling.
Key features:
- Loading and merging configurations from default or custom JSON files
- Validating configurations using Pydantic models
- Managing directory setups for the application
- Utility to get prediction start and end dates
"""
import json
import os
import shutil
from datetime import datetime, timedelta
from pathlib import Path
from typing import Any, Optional
output_dir = "output"
from pydantic import BaseModel, ValidationError
prediction_hours = 48
optimization_hours = 24
strafe = 10
possible_ev_charge_currents = [
0.0,
6.0 / 16.0,
# 7.0 / 16.0,
8.0 / 16.0,
# 9.0 / 16.0,
10.0 / 16.0,
# 11.0 / 16.0,
12.0 / 16.0,
# 13.0 / 16.0,
14.0 / 16.0,
# 15.0 / 16.0,
1.0,
]
EOS_DIR = "EOS_DIR"
ENCODING = "UTF-8"
CONFIG_FILE_NAME = "EOS.config.json"
DEFAULT_CONFIG_FILE = Path(__file__).parent.joinpath("default.config.json")
def get_start_enddate(prediction_hours=48, startdate=None):
############
# Parameter
############
class FolderConfig(BaseModel):
"""Folder configuration for the EOS system.
Uses working_dir as root path.
The working directory can be either cwd or
a path or folder defined by the EOS_DIR environment variable.
Attributes:
output (str): Directory name for output files.
cache (str): Directory name for cache files.
"""
output: str
cache: str
class EOSConfig(BaseModel):
"""EOS system-specific configuration.
Attributes:
prediction_hours (int): Number of hours for predictions.
optimization_hours (int): Number of hours for optimizations.
penalty (int): Penalty factor used in optimization.
available_charging_rates_in_percentage (list[float]): List of available charging rates as percentages.
"""
prediction_hours: int
optimization_hours: int
penalty: int
available_charging_rates_in_percentage: list[float]
feed_in_tariff_eur_per_wh: int
class BaseConfig(BaseModel):
"""Base configuration for the EOS system.
Attributes:
directories (FolderConfig): Configuration for directory paths (output, cache).
eos (EOSConfig): Configuration for EOS-specific settings.
"""
directories: FolderConfig
eos: EOSConfig
class AppConfig(BaseConfig):
"""Application-level configuration that extends the base configuration with a working directory.
Attributes:
working_dir (Path): The root directory for the application.
"""
working_dir: Path
def run_setup(self) -> None:
"""Runs setup for the application by ensuring that required directories exist.
If a directory does not exist, it is created.
Raises:
OSError: If directories cannot be created.
"""
print("Checking directory settings and creating missing directories...")
for key, value in self.directories.model_dump().items():
if not isinstance(value, str):
continue
path = self.working_dir / value
print(f"'{key}': {path}")
os.makedirs(path, exist_ok=True)
class SetupIncomplete(Exception):
"""Exception class for errors related to incomplete setup of the EOS system."""
def _load_json(path: Path) -> dict[str, Any]:
"""Load a JSON file from a given path.
Args:
path (Path): Path to the JSON file.
Returns:
dict[str, Any]: Parsed JSON content.
Raises:
FileNotFoundError: If the JSON file does not exist.
json.JSONDecodeError: If the file cannot be parsed as valid JSON.
"""
with path.open("r") as f_in:
return json.load(f_in)
def _merge_json(default_data: dict[str, Any], custom_data: dict[str, Any]) -> dict[str, Any]:
"""Recursively merge two dictionaries, using values from `custom_data` when available.
Args:
default_data (dict[str, Any]): The default configuration values.
custom_data (dict[str, Any]): The custom configuration values.
Returns:
dict[str, Any]: Merged configuration data.
"""
merged_data = {}
for key, default_value in default_data.items():
if key in custom_data:
custom_value = custom_data[key]
if isinstance(default_value, dict) and isinstance(custom_value, dict):
merged_data[key] = _merge_json(default_value, custom_value)
elif type(default_value) is type(custom_value):
merged_data[key] = custom_value
else:
# use default value if types differ
merged_data[key] = default_value
else:
merged_data[key] = default_value
return merged_data
def _config_update_available(merged_data: dict[str, Any], custom_data: dict[str, Any]) -> bool:
"""Check if the configuration needs to be updated by comparing merged data and custom data.
Args:
merged_data (dict[str, Any]): The merged configuration data.
custom_data (dict[str, Any]): The custom configuration data.
Returns:
bool: True if there is a difference indicating that an update is needed, otherwise False.
"""
if merged_data.keys() != custom_data.keys():
return True
for key in merged_data:
value1 = merged_data[key]
value2 = custom_data[key]
if isinstance(value1, dict) and isinstance(value2, dict):
if _config_update_available(value1, value2):
return True
elif value1 != value2:
return True
return False
def get_config_file(path: Path, copy_default: bool) -> Path:
"""Get the valid configuration file path. If the custom config is not found, it uses the default config.
Args:
path (Path): Path to the working directory.
copy_default (bool): If True, copy the default configuration if custom config is not found.
Returns:
Path: Path to the valid configuration file.
"""
config = path.resolve() / CONFIG_FILE_NAME
if config.is_file():
print(f"Using configuration from: {config}")
return config
if not path.is_dir():
print(f"Path does not exist: {path}. Using default configuration...")
return DEFAULT_CONFIG_FILE
if not copy_default:
print("No custom configuration provided. Using default configuration...")
return DEFAULT_CONFIG_FILE
try:
return Path(shutil.copy2(DEFAULT_CONFIG_FILE, config))
except Exception as exc:
print(f"Could not copy default config: {exc}. Using default copy...")
return DEFAULT_CONFIG_FILE
def _merge_and_update(custom_config: Path, update_outdated: bool = False) -> bool:
"""Merge custom and default configurations, and optionally update the custom config if outdated.
Args:
custom_config (Path): Path to the custom configuration file.
update_outdated (bool): If True, update the custom config if it is outdated.
Returns:
bool: True if the custom config was updated, otherwise False.
"""
if custom_config == DEFAULT_CONFIG_FILE:
return False
default_data = _load_json(DEFAULT_CONFIG_FILE)
custom_data = _load_json(custom_config)
merged_data = _merge_json(default_data, custom_data)
if not _config_update_available(merged_data, custom_data):
print(f"Custom config {custom_config} is up-to-date...")
return False
print(f"Custom config {custom_config} is outdated...")
if update_outdated:
with custom_config.open("w") as f_out:
json.dump(merged_data, f_out, indent=2)
return True
return False
def load_config(
working_dir: Path, copy_default: bool = False, update_outdated: bool = True
) -> AppConfig:
"""Load the application configuration from the specified directory, merging with defaults if needed.
Args:
working_dir (Path): Path to the working directory.
copy_default (bool): Whether to copy the default configuration if custom config is missing.
update_outdated (bool): Whether to update outdated custom configuration.
Returns:
AppConfig: Loaded application configuration.
Raises:
ValueError: If the configuration is incomplete or not valid.
"""
# make sure working_dir is always a full path
working_dir = working_dir.resolve()
config = get_config_file(working_dir, copy_default)
_merge_and_update(config, update_outdated)
with config.open("r", encoding=ENCODING) as f_in:
try:
base_config = BaseConfig.model_validate(json.load(f_in))
return AppConfig.model_validate(
{"working_dir": working_dir, **base_config.model_dump()}
)
except ValidationError as exc:
raise ValueError(f"Configuration {config} is incomplete or not valid: {exc}")
def get_working_dir() -> Path:
"""Get the working directory for the application, either from an environment variable or the current working directory.
Returns:
Path: The path to the working directory.
"""
custom_dir = os.getenv(EOS_DIR)
if custom_dir is None:
working_dir = Path.cwd()
print(f"No custom directory provided. Setting working directory to: {working_dir}")
else:
working_dir = Path(custom_dir).resolve()
print(f"Custom directory provided. Setting working directory to: {working_dir}")
return working_dir
def get_start_enddate(
prediction_hours: int, startdate: Optional[datetime] = None
) -> tuple[str, str]:
"""Calculate the start and end dates based on the given prediction hours and optional start date.
Args:
prediction_hours (int): Number of hours for predictions.
startdate (Optional[datetime]): Optional starting datetime.
Returns:
tuple[str, str]: The current date (start date) and end date in the format 'YYYY-MM-DD'.
"""
if startdate is None:
date = (datetime.now().date() + timedelta(hours=prediction_hours)).strftime("%Y-%m-%d")
date_now = datetime.now().strftime("%Y-%m-%d")

15
src/akkudoktoreos/default.config.json Normal file
View File

@@ -0,0 +1,15 @@
{
"directories": {
"output": "output",
"cache": "cache"
},
"eos": {
"prediction_hours": 48,
"optimization_hours": 24,
"penalty": 10,
"available_charging_rates_in_percentage": [
0.0, 0.375, 0.5, 0.625, 0.75, 0.875, 1.0
],
"feed_in_tariff_eur_per_wh": 48
}
}

27
src/akkudoktoreos/visualize.py
View File

@@ -1,5 +1,4 @@
import datetime
import os
# Set the backend for matplotlib to Agg
import matplotlib
@@ -8,7 +7,7 @@ import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
from akkudoktoreos.class_sommerzeit import ist_dst_wechsel
from akkudoktoreos.config import output_dir
from akkudoktoreos.config import AppConfig, SetupIncomplete
matplotlib.use("Agg")
@@ -23,22 +22,24 @@ def visualisiere_ergebnisse(
discharge, # Discharge allowed
temperature,
start_hour,
prediction_hours,
einspeiseverguetung_euro_pro_wh,
config: AppConfig,
filename="visualization_results.pdf",
extra_data=None,
):
#####################
# 24-hour visualization
#####################
if not os.path.exists(output_dir):
os.makedirs(output_dir)
output_file = os.path.join(output_dir, filename)
output_dir = config.working_dir / config.directories.output
if not output_dir.is_dir():
raise SetupIncomplete(f"Output path does not exist: {output_dir}.")
output_file = output_dir.joinpath(filename)
with PdfPages(output_file) as pdf:
# Load and PV generation
plt.figure(figsize=(14, 14))
plt.subplot(3, 3, 1)
hours = np.arange(0, prediction_hours)
hours = np.arange(0, config.eos.prediction_hours)
gesamtlast_array = np.array(gesamtlast)
# Plot individual loads
@@ -101,9 +102,9 @@ def visualisiere_ergebnisse(
plt.figure(figsize=(14, 10))
if ist_dst_wechsel(datetime.datetime.now()):
hours = np.arange(start_hour, prediction_hours - 1)
hours = np.arange(start_hour, config.eos.prediction_hours - 1)
else:
hours = np.arange(start_hour, prediction_hours)
hours = np.arange(start_hour, config.eos.prediction_hours)
# Energy flow, grid feed-in, and grid consumption
plt.subplot(3, 2, 1)
@@ -187,7 +188,7 @@ def visualisiere_ergebnisse(
# Plot for AC, DC charging, and Discharge status using bar charts
ax1 = plt.subplot(3, 2, 5)
hours = np.arange(0, prediction_hours)
hours = np.arange(0, config.eos.prediction_hours)
# Plot AC charging as bars (relative values between 0 and 1)
plt.bar(hours, ac, width=0.4, label="AC Charging (relative)", color="blue", alpha=0.6)
@@ -209,16 +210,16 @@ def visualisiere_ergebnisse(
# Configure the plot
ax1.legend(loc="upper left")
ax1.set_xlim(0, prediction_hours)
ax1.set_xlim(0, config.eos.prediction_hours)
ax1.set_xlabel("Hour")
ax1.set_ylabel("Relative Power (0-1) / Discharge (0 or 1)")
ax1.set_title("AC/DC Charging and Discharge Overview")
ax1.grid(True)
if ist_dst_wechsel(datetime.datetime.now()):
hours = np.arange(start_hour, prediction_hours - 1)
hours = np.arange(start_hour, config.eos.prediction_hours - 1)
else:
hours = np.arange(start_hour, prediction_hours)
hours = np.arange(start_hour, config.eos.prediction_hours)
pdf.savefig() # Save the current figure state to the PDF
plt.close() # Close the current figure to free up memory

46
src/akkudoktoreosserver/flask_server.py
View File

@@ -20,20 +20,18 @@ from akkudoktoreos.class_optimize import optimization_problem
from akkudoktoreos.class_pv_forecast import PVForecast
from akkudoktoreos.class_strompreis import HourlyElectricityPriceForecast
from akkudoktoreos.config import (
SetupIncomplete,
get_start_enddate,
optimization_hours,
output_dir,
prediction_hours,
get_working_dir,
load_config,
)
app = Flask(__name__)
opt_class = optimization_problem(
prediction_hours=prediction_hours,
strafe=10,
optimization_hours=optimization_hours,
verbose=True,
)
working_dir = get_working_dir()
# copy config to working directory. Make this a CLI option later
config = load_config(working_dir, True)
opt_class = optimization_problem(config)
def isfloat(num: Any) -> TypeGuard[float]:
@@ -58,14 +56,11 @@ def isfloat(num: Any) -> TypeGuard[float]:
@app.route("/strompreis", methods=["GET"])
def flask_strompreis():
# Get the current date and the end date based on prediction hours
date_now, date = get_start_enddate(prediction_hours, startdate=datetime.now().date())
filepath = os.path.join(
r"test_data", r"strompreise_akkudokAPI.json"
) # Adjust the path to the JSON file
date_now, date = get_start_enddate(config.eos.prediction_hours, startdate=datetime.now().date())
price_forecast = HourlyElectricityPriceForecast(
source=f"https://api.akkudoktor.net/prices?start={date_now}&end={date}",
prediction_hours=prediction_hours,
cache=False,
config=config.eos.prediction_hours,
use_cache=False,
)
specific_date_prices = price_forecast.get_price_for_daterange(
date_now, date
@@ -141,7 +136,7 @@ def flask_gesamtlast_simple():
request.args.get("year_energy")
) # Get annual energy value from query parameters
date_now, date = get_start_enddate(
prediction_hours, startdate=datetime.now().date()
config.eos.prediction_hours, startdate=datetime.now().date()
) # Get the current date and prediction end date
###############
@@ -159,7 +154,9 @@ def flask_gesamtlast_simple():
0
] # Get expected household load for the date range
gesamtlast = Gesamtlast(prediction_hours=prediction_hours) # Create Gesamtlast instance
gesamtlast = Gesamtlast(
prediction_hours=config.eos.prediction_hours
) # Create Gesamtlast instance
gesamtlast.hinzufuegen(
"Haushalt", leistung_haushalt
) # Add household load to total load calculation
@@ -181,13 +178,15 @@ def flask_pvprognose():
# Retrieve URL and AC power measurement from query parameters
url = request.args.get("url")
ac_power_measurement = request.args.get("ac_power_measurement")
date_now, date = get_start_enddate(prediction_hours, startdate=datetime.now().date())
date_now, date = get_start_enddate(
config.eos.prediction_hours, startdate=datetime.now().date()
)
###############
# PV Forecast
###############
PVforecast = PVForecast(
prediction_hours=prediction_hours, url=url
prediction_hours=config.eos.prediction_hours, url=url
) # Instantiate PVForecast with given parameters
if isfloat(ac_power_measurement): # Check if the AC power measurement is a valid float
PVforecast.update_ac_power_measurement(
@@ -255,9 +254,10 @@ def flask_optimize():
@app.route("/visualization_results.pdf")
def get_pdf():
# Endpoint to serve the generated PDF with visualization results
return send_from_directory(
os.path.abspath(output_dir), "visualization_results.pdf"
) # Adjust the directory if needed
output_path = config.working_dir / config.directories.output
if not output_path.is_dir():
raise SetupIncomplete(f"Output path does not exist: {output_path}.")
return send_from_directory(output_path, "visualization_results.pdf")
@app.route("/site-map")
@@ -293,6 +293,8 @@ def root():
if __name__ == "__main__":
try:
config.run_setup()
# Set host and port from environment variables or defaults
host = os.getenv("FLASK_RUN_HOST", "0.0.0.0")
port = os.getenv("FLASK_RUN_PORT", 8503)