python-configuration

# Python Configuration Management

Externalize configuration from code using environment variables and typed settings. Well-managed configuration enables the same code to run in any environment without modification.

## When to Use This Skill

- Setting up a new project's configuration system
- Migrating from hardcoded values to environment variables
- Implementing pydantic-settings for typed configuration
- Managing secrets and sensitive values
- Creating environment-specific settings (dev/staging/prod)
- Validating configuration at application startup

## Core Concepts

### 1. Externalized Configuration

All environment-specific values (URLs, secrets, feature flags) come from environment variables, not code.

### 2. Typed Settings

Parse and validate configuration into typed objects at startup, not scattered throughout code.

### 3. Fail Fast

Validate all required configuration at application boot. Missing config should crash immediately with a clear message.

### 4. Sensible Defaults

Provide reasonable defaults for local development while requiring explicit values for sensitive settings.

## Quick Start

```python
from pydantic_settings import BaseSettings
from pydantic import Field

class Settings(BaseSettings):
    database_url: str = Field(alias="DATABASE_URL")
    api_key: str = Field(alias="API_KEY")
    debug: bool = Field(default=False, alias="DEBUG")

settings = Settings()  # Loads from environment
```

## Fundamental Patterns

### Pattern 1: Typed Settings with Pydantic

Create a central settings class that loads and validates all configuration.

```python
from pydantic_settings import BaseSettings
from pydantic import Field, PostgresDsn, ValidationError
import sys

class Settings(BaseSettings):
    """Application configuration loaded from environment variables."""

    # Database
    db_host: str = Field(alias="DB_HOST")
    db_port: int = Field(default=5432, alias="DB_PORT")
    db_name: str = Field(alias="DB_NAME")
    db_user: str = Field(alias="DB