Advanced input validation and error handling

Deploying AI into Production with FastAPI

Matt Eckerle

Software and Data Engineering Leader

Why we need advanced input

API for restaurant orders
Variable number of items

class Order(BaseModel):
    item1: str
    item2: str
    item3: str

A restaurant

Nested Pydantic models

from pydantic import BaseModel

class Foo(BaseModel):
    count: int

class Bar(BaseModel):
    foo: Foo

>>> m = Bar(foo={'count': 4})
>>> print(m)
foo=Foo(count=4)

from pydantic import BaseModel
from typing import List


class OrderItem(BaseModel):
    name: str
    quantity: int


class RestaurantOrder(BaseModel):
    customer_name: str
    items: List[OrderItem]

Custom model validators

from fastapi import FastAPI
from fastapi.exceptions import (
    RequestValidationError
)
from pydantic import (
    BaseModel,
    model_validator,
)

from typing import List

class OrderItem(BaseModel):
    name: str
    quantity: int

class RestaurantOrder(BaseModel):
    customer_name: str
    items: List[OrderItem]


    @model_validator(mode="after")

    def validate_after(self):
        if len(self.items) == 0:
           raise RequestValidationError(
               "No items in order!"
           )
        return self

{"detail":"No items in order!"}

Global exception handlers

from fastapi import FastAPI
from fastapi.exceptions import RequestValidationError
from fastapi.responses import PlainTextResponse


app = FastAPI()

@app.exception_handler(RequestValidationError)

async def validation_exception_handler(request, exc):
    msg = "Input validation error. See the documentation: http://127.0.0.1:8000/docs"
    return PlainTextResponse(msg, status_code=422)

Input validation error. See the documentation: http://127.0.0.1:8000/docs

Let's practice!

Deploying AI into Production with FastAPI