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By Kevin McAleer, 2 Minutes
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.
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.
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
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 Pydanticβs model instance is directly available in the function parameters.
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.
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.
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.
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