How to Work with Environment Variables and Configuration Files in FastAPI

In this tutorial, you'll learn how to securely manage configuration data in your FastAPI projects using environment variables and .env files. FastAPI is not only known for its performance and simplicity, but it also integrates well with best practices like keeping secrets, API keys, and database URLs outside your source code.

Using tools like python-dotenv and pydantic-settings (for Pydantic v2+), you'll see how to build robust, secure, and flexible FastAPI applications with proper configuration management.

What You’ll Learn:
Why using environment variables is important for security and flexibility
How to create and load a .env file in your FastAPI project
How to use the pydantic-settings package to define configuration schemas
How to access values like database URLs, secret keys, and debug flags from .env
Setting up a config.py or settings.py file for clean configuration management
Preventing hardcoded secrets in your codebase
Loading environment variables automatically at runtime
Tips on structuring configuration files for different environments (development, production, staging)
Real-world use cases such as using .env for AWS keys, database credentials, and API secrets
How to integrate environment configs into Dockerized FastAPI applications

Why This Is Essential:
Storing sensitive data in your codebase is risky and bad practice. By using .env files and environment variables, you keep your configuration modular, secure, and portable, especially when deploying to services like Heroku, AWS, Docker, and more. It also simplifies switching between local development and production environments.

Who Should Watch:

Beginners and intermediate FastAPI developers

Developers deploying apps with Docker, Cloud services, or CI/CD

Anyone looking to secure their configuration or make their apps more flexible

Developers working on multi-environment projects

Those who want to follow 12-factor app design principles

Prerequisites:

A basic understanding of FastAPI and Python

Familiarity with Pydantic models

Some exposure to terminal/command-line usage

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