Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.
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Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.
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Stars38,174
Forks4,092
LanguagePython
LicenseMIT
📦 Ships with wshobson-agents
</> SKILL.md
python-configuration.SKILL.md
---name: python-configuration
description: Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.
---# 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.
Create a `.env` file for local development (never commit this):
```bash
# .env (add to .gitignore)
DB_PASSWORD=local_dev_password
API_SECRET_KEY=dev-secret-key
DEBUG=true
```
### Pattern 4: Namespaced Environment Variables
Prefix related variables for clarity and easy debugging.
```bash
# Database configuration
DB_HOST=localhost
DB_PORT=5432
DB_NAME=myapp
DB_USER=admin
DB_PASSWORD=secret
# Redis configuration
REDIS_URL=redis://localhost:6379
REDIS_MAX_CONNECTIONS=10
# Authentication
AUTH_SECRET_KEY=your-secret-key
AUTH_TOKEN_EXPIRY_SECONDS=3600
AUTH_ALGORITHM=HS256
# Feature flags
FEATURE_NEW_CHECKOUT=true
FEATURE_BETA_UI=false
```
Makes `env | grep DB_` useful for debugging.
## Detailed worked examples and patterns
Detailed sections (starting with `## Advanced Patterns`) live in `references/details.md`. Read that file when the navigation summary above is insufficient.
## Best Practices Summary
1. **Never hardcode config** - All environment-specific values from env vars
2. **Use typed settings** - Pydantic-settings with validation
3. **Fail fast** - Crash on missing required config at startup
4. **Provide dev defaults** - Make local development easy
5. **Never commit secrets** - Use `.env` files (gitignored) or secret managers
6. **Namespace variables** - `DB_HOST`, `REDIS_URL` for clarity
7. **Import settings singleton** - Don't call `os.getenv()` throughout code
8. **Document all variables** - README should list required env vars
9. **Validate early** - Check config correctness at boot time
10. **Use secrets_dir** - Support mounted secrets in containers
