python-configuration

You can manage Python configuration using environment variables by utilizing Pydantic for setting parsing and typed validation against a predefined schema. This approach ensures configuration consistency and keeps secrets safe.

The best way to load environment-specific settings is using an environment-driven approach that supports multiple environments like dev, staging, and prod. You can initialize settings directly for a specific environment.

Pydantic validates configuration settings by parsing and type-checking environment variables against a predefined schema. This mechanism ensures consistency across local development and production workflows.

To keep Python secrets out of source control and logs, handle them through environment variables or secret management systems. This structured approach prevents sensitive data from leaking into your repository.

Yes, you can use python-dotenv alongside Pydantic to configure environments for deploying Python applications. This combination is suitable for managing settings and secrets within a CI/CD pipeline workflow.