What is the role of the Pydantic library in FastAPI?

Pydantic in FastAPI is used for data validation and serialization. It allows describing data structures using models based on Python classes, where field types are strictly defined.

Main roles of Pydantic in FastAPI:

• Validation of incoming data: when receiving a request, FastAPI automatically checks that the data matches the described model (e.g., JSON with the required fields and types).
• Serialization and deserialization: converting data from JSON to Python objects and back.
• Automatic generation of OpenAPI schemas: based on Pydantic models, FastAPI builds API documentation.

Example of a Pydantic model in FastAPI:

from pydantic import BaseModel
from fastapi import FastAPI

app = FastAPI()

class User(BaseModel):
    id: int
    name: str
    email: str

@app.post("/users/")
async def create_user(user: User):
    return {"message": f"User {user.name} created", "user": user}

Here, FastAPI will automatically verify that the request body contains the fields id, name, and email of the correct types, and will create a User object.