Response models and response filtering

Difficulty: Beginner

Question

What is response_model in FastAPI and why is it important?

Answer

The `response_model` parameter on a path operation decorator specifies the Pydantic model used to validate and filter the response data. It serves three purposes:

1. Filtering: Strips fields not in the response model (e.g., passwords) 2. Validation: Ensures the response matches the expected schema 3. Documentation: Adds the response schema to OpenAPI docs

This separates input models (request body) from output models (response), which is critical for security - you can return a database object and have FastAPI automatically exclude sensitive fields.

Code examples

Using response_model to filter sensitive fields

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class UserCreate(BaseModel):
    name: str
    email: str
    password: str

class UserResponse(BaseModel):
    name: str
    email: str
    # no password field

@app.post("/users", response_model=UserResponse)
def create_user(user: UserCreate):
    # password is in `user` but won't be returned
    return user  # FastAPI filters it using UserResponse

# Use response_model_exclude_unset=True to omit unset optional fields
@app.get("/users/{id}", response_model=UserResponse, response_model_exclude_unset=True)
def get_user(id: int):
    return {"name": "Alice", "email": "alice@example.com"}

Key points

• `response_model_include` and `response_model_exclude` can select specific fields
• `response_model_exclude_unset=True` omits fields that were not explicitly set
• For complex responses use `Union` types or `response_model=None` with `JSONResponse`

Concepts covered

response_model, output filtering, security, serialization