Pydantic Models for Request Bodies 📦

Pydantic models define the structure and validation rules for request body data in your API.

What is a Pydantic Model?

A Pydantic model is a Python class that defines:

• What fields are required

• What types those fields should be

• Optional validation rules

Creating a Simple Model

from pydantic import BaseModel

class Item(BaseModel):
    name: str
    price: float
    description: str = None

This defines an Item with:

• `name` (required string)

• `price` (required float)

• `description` (optional string, defaults to None)

Using the Model in an Endpoint

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    price: float
    description: str = None

@app.post("/items")
async def create_item(item: Item):
    # item is automatically validated as an Item
    return item

Example Requests

Valid Request:

{
  "name": "Laptop",
  "price": 999.99,
  "description": "High-performance laptop"
}

Response: `{"name": "Laptop", "price": 999.99, "description": "High-performance laptop"}`

Request Missing Optional Field:

{
  "name": "Mouse",
  "price": 25.00
}

Response: `{"name": "Mouse", "price": 25.00, "description": null}`

Invalid Request (missing required field):

{
  "price": 100.00
}

Response: 422 Error - "name" field is required

Accessing Model Data

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

@app.post("/users")
async def create_user(user: User):
    # Access fields like object attributes
    print(f"Username: {user.username}")
    print(f"Email: {user.email}")

    # Convert to dictionary
    user_dict = user.dict()

    # Save to database
    db.save_user(user_dict)

    return user

Real-World Example

from typing import Optional

class BlogPost(BaseModel):
    title: str
    content: str
    author: str
    tags: list = []
    published: bool = False
    views: int = 0

@app.post("/posts")
async def create_post(post: BlogPost):
    return {
        "id": 1,
        "created": "2024-03-02",
        **post.dict()
    }

Interactive Documentation

When you define a Pydantic model, FastAPI automatically:

1. Shows the expected data structure in `/docs`

2. Provides example requests

3. Validates incoming data

4. Returns helpful error messages

🔑 Key Takeaways

• ✅ Pydantic models define request structure

• ✅ Inherit from `BaseModel`

• ✅ Type hints specify field types

• ✅ Fields without defaults are required

• ✅ Fields with defaults are optional

• ✅ FastAPI validates automatically

• ✅ Invalid data returns 422 error