Data validation is crucial for building robust APIs. When users send data to your endpoints, you need to ensure it meets your requirements before processing it. FastAPI uses Pydantic models to automatically validate incoming request data and provide clear error messages when validation fails.
Pydantic is a Python library that uses type annotations to validate and serialize data. When you define a Pydantic model, you're creating a schema that describes what valid data looks like. FastAPI integrates seamlessly with Pydantic, automatically validating request bodies against your models.
The power of Pydantic lies in its field types and validators. Built-in types like EmailStr handle common validation patterns, while Field() lets you set constraints like minimum values or string lengths. For custom validation logic, you can write field validators that check business rules specific to your application.
When validation fails, FastAPI automatically returns a 422 status code with detailed error information. This helps API consumers understand exactly what went wrong and how to fix their requests. The error response includes which fields failed validation and why.
For security and data privacy, you often need different models for input and output. A user registration might require a password field, but your API response should never include that password. Pydantic response models let you control exactly which fields are returned to the client.
Validation happens automatically when FastAPI deserializes the request body into your Pydantic model. If validation passes, your endpoint function receives a fully validated object. If it fails, FastAPI handles the error response without your endpoint code ever executing.
1from pydantic import BaseModel, Field, field_validator
2from typing import Optional
3
4class Product(BaseModel):
5 name: str = Field(..., min_length=1, max_length=100)
6 price: float = Field(..., gt=0) # Greater than 0
7 category: str
8 in_stock: bool = True
9
10 @field_validator('name')
11 @classmethod
12 def validate_name(cls, v):
13 if v.strip() != v:
14 raise ValueError('Name cannot have leading/trailing spaces')
15 return v.title() # Convert to title case
16
17# Usage example
18try:
19 product = Product(
20 name="wireless headphones",
21 price=99.99,
22 category="electronics"
23 )
24 print(product.name) # "Wireless Headphones"
25except ValidationError as e:
26 print(e.errors()) # Detailed error information