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By Kevin McAleer, 2 Minutes
FastAPI’s integration with Pydantic goes beyond simple request validation. It extends to sophisticated features like response models, dependency injection, and complex data serialization, which are crucial for building efficient and scalable web applications.
FastAPI allows specifying response models for endpoints, which helps in controlling the API’s output, ensuring that only the necessary data is sent back to the client.
from fastapi import FastAPI from pydantic import BaseModel class ItemBase(BaseModel): name: str description: str = None class ItemCreate(ItemBase): price: float class ItemResponse(ItemBase): id: int app = FastAPI() @app.post("/items/", response_model=ItemResponse) async def create_item(item: ItemCreate): # Your logic to save the item and return the item with its ID return ItemResponse(id=1, **item.dict())
In this example, the input model ItemCreate and the output model ItemResponse are differentiated, providing clear separation between input and output data structures.
ItemCreate
ItemResponse
FastAPI supports dependency injection, allowing you to define reusable dependencies that can be injected into your path operation functions.
from fastapi import Depends, FastAPI def get_db(): # Imagine this function connects to your database db = "Connected to database" try: yield db finally: db = "Disconnected" @app.get("/items/") async def read_items(db = Depends(get_db)): return {"db_connection": db}
This feature is particularly useful for database connections, user authentication, and other cross-cutting concerns.
Pydantic models can also be used to perform complex data serialization and validation, handling nested models, polymorphic models, and even custom serialization logic.
FastAPI provides easy-to-implement tools for adding security and authentication to your applications, from basic authentication to OAuth2, leveraging Pydantic models for request and response data.
Create a FastAPI endpoint for updating user information. Use dependency injection to simulate fetching a user from a database and update the user’s information based on the provided request body. Define Pydantic models for the request and response data to ensure proper validation and serialization.
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