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#
# Note the settings file is hardcoded in this class at the top after imports.
#
# To make a new settings section, just add the setting dict to your yaml
# and then define the data class below in the config data classes area.
#
# Example use from anywhere - this will always return the same singleton
# from settings import get_settings
# def main():
# settings = get_settings()
# print(settings.database.host) # Autocomplete works
# print(settings.logging.level)
# if __name__ == "__main__":
# main()
import functools
from pathlib import Path
from typing import Any, Callable, TypeVar
from dataclasses import dataclass, fields, is_dataclass, field, MISSING
import logging
import sys
logger = logging.getLogger(__file__)
try:
import yaml
except ModuleNotFoundError:
msg = (
"Required modules are not installed. "
"Can not continue with module / application loading.\n"
"Install it with: pip install -r requirements"
)
print(msg, file=sys.stderr)
logger.error(msg)
exit()
BASE_DIR = Path(__file__).resolve().parent.parent
DEFAULT_SETTINGS_FILE = BASE_DIR / "config" / "settings.yaml"
# ---------- CONFIG DATA CLASSES ----------
@dataclass
class Cache_Config:
whois_cache_days: int = 7
geoip_cache_days: int = 7
recent_runs_count: int = 10
@dataclass
class AppConfig:
name: str = "MyApp"
version_major: int = 1
version_minor: int = 0
@dataclass
class Settings:
cache: Cache_Config = field(default_factory=Cache_Config)
app: AppConfig = field(default_factory=AppConfig)
@classmethod
def from_yaml(cls, path: str | Path) -> "Settings":
try:
"""Load settings from YAML file into a Settings object."""
with open(path, "r", encoding="utf-8") as f:
raw: dict[str, Any] = yaml.safe_load(f) or {}
except FileNotFoundError:
logger.warning(f"Settings file {path} not found! Using default settings.")
raw = {}
init_kwargs = {}
for f_def in fields(cls):
yaml_value = raw.get(f_def.name, None)
# Determine default value from default_factory or default
if f_def.default_factory is not MISSING:
default_value = f_def.default_factory()
elif f_def.default is not MISSING:
default_value = f_def.default
else:
default_value = None
# Handle nested dataclasses
if is_dataclass(f_def.type):
if isinstance(yaml_value, dict):
# Merge YAML values with defaults
merged_data = {fld.name: getattr(default_value, fld.name) for fld in fields(f_def.type)}
merged_data.update(yaml_value)
init_kwargs[f_def.name] = f_def.type(**merged_data)
else:
init_kwargs[f_def.name] = default_value
else:
init_kwargs[f_def.name] = yaml_value if yaml_value is not None else default_value
return cls(**init_kwargs)
# ---------- SINGLETON DECORATOR ----------
T = TypeVar("T")
def singleton_loader(func: Callable[..., T]) -> Callable[..., T]:
"""Ensure the function only runs once, returning the cached value."""
cache: dict[str, T] = {}
@functools.wraps(func)
def wrapper(*args, **kwargs) -> T:
if func.__name__ not in cache:
cache[func.__name__] = func(*args, **kwargs)
return cache[func.__name__]
return wrapper
# ---------- SINGLETON DECORATOR ----------
T = TypeVar("T")
def singleton_loader(func: Callable[..., T]) -> Callable[..., T]:
"""Decorator to ensure the settings are loaded only once."""
cache: dict[str, T] = {}
@functools.wraps(func)
def wrapper(*args, **kwargs) -> T:
if func.__name__ not in cache:
cache[func.__name__] = func(*args, **kwargs)
return cache[func.__name__]
return wrapper
@singleton_loader
def get_settings(config_path: str | Path | None = None) -> Settings:
"""
Returns the singleton Settings instance.
Args:
config_path: Optional path to the YAML config file. If not provided,
defaults to 'config/settings.yaml' in the current working directory.
"""
if config_path is None:
config_path = DEFAULT_SETTINGS_FILE
else:
config_path = Path(config_path)
return Settings.from_yaml(config_path)