Request and response models

Deploying AI into Production with FastAPI

Matt Eckerle

Software and Data Engineering Leader

Request and response structures in APIs

Request structure

Data sent by the client to the API
Typically includes:
- HTTP method (GET, POST, etc.)
- Headers
- Query parameters
- Request body

http://localhost:8000/users/? [email protected]

:8000: The port number. FastAPI typically uses 8000 by default.
/users/: The path to the specific endpoint we're accessing.
?: Indicates the start of the query parameters.
`[email protected]`: The query parameter. In this case, we're passing an email address to the endpoint.

Response structure

Data sent back by the API to the client
- JSON response payload with user information
Typically includes:
- Status code (200 OK, 404 Not Found, etc.)
- Headers
- Response body (data requested or operation result)

HTTP/1.1 200 OK
date: Fri, 18 Oct 2024 12:34:56 GMT
server: uvicorn
content-length: 76
content-type: application/json

{
  "username": "johndoe",
  "email": "[email protected]",
  "age": 30
}

Pydantic model

Creation of User
Use of Pydantic

from pydantic import BaseModel

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

Inherits from BaseModel
Defines attributes with type annotations
Automatic validation based on types

Validation error

from pydantic import ValidationError
try:
    invalid_user = User(username="john_doe", email="[email protected]", 
                        age="thirty")
    print("Invalid User:", invalid_user)
except ValidationError as e:
    print("Validation Error:", e)

Validation Error: 1 validation error for User age
Input should be a valid integer, unable to parse string as an integer 
[type=int_parsing, input_value='thirty', input_type=str]

Using Pydantic models in FastAPI

from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()


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


@app.post("/users", response_model=User)

async def create_user(user: User):
    return user

Model used as response_model
Model used as parameter type hint
Automatic request validation
De/serialization of request/response
Generate API docs

Request and response formats

curl -X 'POST' \
  'http://localhost:8000/users/' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "username": "john_doe",
  "email": "[email protected]",
  "age": 30
  }'

{
  "username": "john_doe",
  "email": "[email protected]",
  "age": 30
}

Let's practice!

Deploying AI into Production with FastAPI