Toptal

Django projects used to frustrate me because I lacked a robust and scalable way to add new environments. By bringing together pydantic and Python 3.5 type hints, I built the powerful foundation I needed.

As described in PEP 484, type hints support static analysis, but these same annotations are also available at runtime. Third-party packages like pydantic offer runtime type checking that uses this additional metadata. Pydantic uses Python type hints to help manage settings metadata and perform runtime data validation.

This pydantic tutorial will show the far-reaching, positive effects of using pydantic settings management with Django.

Our configuration adheres to the best practices described on the Twelve-Factor App website:

Define nonconstant and secret configurations as environment variables. In development environments, define environment variables in a .env file and add the .env to .gitignore. Use the cloud provider’s mechanisms to define (secret) environment variables for the QA, staging, and

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