Python config
Skill Mattakushi432/Claude-Code-Skills-Custom-DevTools-Pack/plugins/devtools-pack/skills/python-config
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When to activate: configuration management, pydantic-settings, env files, feature flags, environment-specific settings
SKILL.md
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Python Configuration Patterns
Pydantic Settings (12-Factor App)
from pydantic import PostgresDsn, RedisDsn, SecretStr, AnyHttpUrl, field_validator
from pydantic_settings import BaseSettings, SettingsConfigDict
from functools import lru_cache
class Settings(BaseSettings):
model_config = SettingsConfigDict(
env_file=".env",
env_file_encoding="utf-8",
case_sensitive=False,
)
# Application
app_name: str = "MyApp"
environment: str = "development" # development | staging | production
debug: bool = False
# Database
database_url: PostgresDsn
database_pool_size: int = 10
database_max_overflow: int = 20
# Cache
redis_url: RedisDsn = "redis://localhost:6379/0"
# Auth
secret_key: SecretStr
access_token_expire_minutes: int = 30
# External services
sendgrid_api_key: SecretStr | None = None
stripe_secret_key: SecretStr | None = None
@field_validator("environment")
@classmethod
def validate_env(cls, v: str) -> str:
allowed = {"development", "staging", "production"}
if v not in allowed:
raise ValueError(f"environment must be one of {allowed}")
return v
@property
def is_production(self) -> bool:
return self.environment == "production"
@lru_cache
def get_settings() -> Settings:
return Settings()
# Usage in FastAPI
settings = Annotated[Settings, Depends(get_settings)]
Environment-Specific Settings
# config/base.py
class BaseConfig(BaseSettings):
debug: bool = False
log_level: str = "INFO"
database_url: PostgresDsn
# config/development.py
class DevelopmentConfig(BaseConfig):
debug: bool = True
log_level: str = "DEBUG"
# config/production.py
class ProductionConfig(BaseConfig):
debug: bool = False
# Production enforces certain required fields
sentry_dsn: AnyHttpUrl
def get_config() -> BaseConfig:
env = os.getenv("ENVIRONMENT", "development")
configs = {
"development": DevelopmentConfig,
"production": ProductionConfig,
}
return configs.get(env, DevelopmentConfig)()
Feature Flags
from pydantic import BaseModel
class FeatureFlags(BaseSettings):
model_config = SettingsConfigDict(env_prefix="FEATURE_")
new_dashboard: bool = False
ai_recommendations: bool = False
beta_api: bool = False
flags = FeatureFlags()
# Usage
if flags.new_dashboard:
return new_dashboard_response()
# Runtime flags from Redis (for fast toggling without redeploy)
async def is_enabled(feature: str, redis: Redis) -> bool:
raw = await redis.get(f"feature:{feature}")
return raw == b"true" if raw else False
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