Integrating Pydantic with FastAPI

Discover how to leverage Pydantic models within FastAPI applications for efficient data validation and serialization in web development.

By Kevin McAleer,    2 Minutes

Pydantic and FastAPI: A Powerful Duo

FastAPI is a modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard Python type hints. The synergy between FastAPI and Pydantic is one of the key features of FastAPI, offering automatic request validation, serialization, and documentation.

Using Pydantic Models in FastAPI

FastAPI uses Pydantic models to define the data structures of request and response payloads. This integration simplifies data validation and conversion, ensuring that the data exchanged between clients and the server is correct and consistent.

Defining a Pydantic Model

First, define a Pydantic model to represent the data structure for your API endpoints.

from pydantic import BaseModel

class Item(BaseModel):
    name: str
    description: str = None
    price: float
    tax: float = 0.1

Creating FastAPI Endpoints

With the Pydantic model defined, you can now create FastAPI endpoints that automatically validate incoming requests against the model.

from fastapi import FastAPI, HTTPException
app = FastAPI()

@app.post("/items/")
async def create_item(item: Item):
    return {"name": item.name, "price": item.price}

In this example, the create_item endpoint expects a request body matching the Item model. FastAPI automatically validates the request data, and Pydantic’s model instance is directly available in the function parameters.

Request Validation and Serialization

FastAPI leverages Pydantic models to validate request data and serialize response data. This seamless integration makes it easy to ensure that the data conforms to the specified types and constraints defined in your Pydantic models.

Exception Handling and Documentation

When a request fails validation, FastAPI automatically returns a detailed error response. Additionally, FastAPI uses Pydantic models to generate OpenAPI schema documentation for your API, enhancing the developer experience with auto-generated docs.

Lesson Assignment

Create a FastAPI application with an endpoint to handle creating a user. Define a Pydantic model for a User with fields for username, email, and full_name. Implement the endpoint to validate incoming requests using this model and return the user data in the response.

Additional Resources

• FastAPI Documentation
• Pydantic Documentation