python-configuration

Load typed Python configuration from environment variables by defining a Settings class using pydantic-settings, which binds environment variables to typed fields for fail-fast validation and externalized config.

The best way to manage Python environment-specific settings and secrets is using pydantic-settings with Field aliases, enabling environment variable aliases, nesting, and development defaults to externalize configuration from code.

Pydantic validation for environment variables works by mapping environment variables to typed Settings class fields, enforcing fail-fast validation so invalid configuration raises immediate errors during application startup.

Yes, you can use pydantic-settings to set development defaults for Python configuration by defining default values in your Settings class fields while still allowing environment variables to override them in staging or production.

Python configuration fails to load environment variables as typed settings when Field aliases do not match the expected environment variable names, or when fail-fast validation rejects mismatched types during pydantic-settings parsing.