The goal is to build a basic RESTful API in Python using FastAPI and validate data with Pydantic.
Before we start – a little refresher on APIs!
An API (Application Programming Interface) is a set of rules that allows different software applications to communicate with each other. Think of it as a waiter in a restaurant: you (the client) order food, the waiter (API) takes your order to the kitchen (server), and brings back your meal. In web development, APIs serve as the bridge between frontend applications (websites, mobile apps) and backend services (databases, business logic). APIs are essential because they enable separation of concerns, platform independence (one API serving web and mobile), scalability, reusability across multiple applications, and integration between different services. For example, in a museum website, the frontend displays artworks to users, the API handles requests like "get all Rembrandt paintings," and the backend manages the database.
FastAPI is our framework of choice because it's one of the fastest Python frameworks available, offering performance comparable to Node.js and Go. It provides an excellent developer experience with automatic interactive documentation (at /docs and /redoc), built-in data validation using Pydantic models, type safety with Python type hints, and intuitive design that's easy to learn. FastAPI leverages modern Python features like async/await for high-performance applications, includes built-in security features, and offers excellent IDE support with autocompletion and error detection. This combination of speed, developer-friendly features, and modern Python capabilities makes FastAPI perfect for building robust, well-documented APIs.
There are other widely used frameworks such as Django and Flask. Feel free to explore them in your own time after you are done with this module!
Make sure you are familiar with RESTful APIs and HTTP Protocols
Review the Python types and virtual environments on the FastAPI page. These pages are specifically targeted to help set yourself up to work with FastAPI.
These are more advanced topics which are needed in order to use FastAPI and Pydantic.
- Classes and Object-Oriented Programming (OOP) basics: A refresher from the basics
- OOP: Inheritance and Composition
- Requests
- Decorators
- Environment Variables
- The official FastAPI Tutorial is a great place to start.
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Getting Started with FastAPI
- First Steps: Creating your first API
- Path Parameters: Dynamic URL segments
- Query Parameters: URL query strings
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Request and Response Handling
- Request Body: Handling POST data with Pydantic models
- Response Model: Structuring API responses
- Status Codes: HTTP status codes
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Data Validation with Pydantic
- Pydantic Models: Data validation and serialization
- Field Validation: Custom validation rules
- Error Handling: Managing validation errors
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Advanced Features
- Dependencies: Dependency injection system
- Middleware: Request/response processing
- Background Tasks: Async task processing
- Interactive Documentation: FastAPI automatically generates interactive API docs at
/docs - Testing: Testing FastAPI applications with pytest
- Deployment: Deployment basics for production
By the end of this week, you should be able to:
- Create a basic FastAPI application with multiple endpoints
- Use Pydantic models for request/response validation
- Handle different HTTP methods (GET, POST, PUT, DELETE)
- Implement path and query parameters
- Add basic error handling and status codes
- Test your API using the interactive documentation
Check out this great tutorial which deconstructs the ins and outs of FastAPI.