Pydantic

Pydantic is used to define and validate the structure and data types of API data.

With Pydantic, you can create models that describe what fields your API data should contain and what type of data each field should have.

Code

from pydantic import BaseModel


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

Understanding the Code

First, import BaseModel from Pydantic:

from pydantic import BaseModel

Then create a User model:

class User(BaseModel):

The User model contains three fields:

name: str
email: str
age: int

Here:

• name must be a string.
• email must be a string.
• age must be an integer.

Pydantic uses these type definitions to validate the data structure.

Example Data

A valid User object can contain:

{
    "name": "Tarun",
    "email": "tarun@example.com",
    "age": 25
}

Why Use Pydantic?

Pydantic helps FastAPI work with structured and validated data. Instead of manually checking every field, you define the expected structure in a model:

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

FastAPI can then use this model when receiving or returning API data.