How to validate request bodies with Pydantic models in FastAPI

Request Body Validation with Pydantic

FastAPI uses Pydantic models to describe, validate, and parse JSON request bodies. Declare a class that inherits from BaseModel, add typed fields, and use it as a parameter type in your route function.

Basic model and route

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    price: float
    in_stock: bool = True

@app.post("/items/")
def create_item(item: Item):
    return item

FastAPI reads the JSON body, validates every field against the types declared, and injects a fully typed Item object into the function. If price is missing or is a string that cannot be coerced, the caller gets a 422 with details about which field failed.

Adding constraints with Field

from pydantic import BaseModel, Field

class Product(BaseModel):
    name: str = Field(..., min_length=2, max_length=100)
    price: float = Field(..., gt=0)
    quantity: int = Field(default=0, ge=0)

Field(...) marks a field as required. Use gt, ge, lt, le, min_length, max_length to constrain values. These constraints appear in the generated OpenAPI schema so frontend teams see them too.

Nested models

class Address(BaseModel):
    city: str
    country: str

class User(BaseModel):
    name: str
    address: Address

Nest models directly. Pydantic validates the full tree and FastAPI serializes it back to nested JSON automatically.