Custom error response models in FastAPI - Mini Project: Build & Apply

Custom error response models in FastAPI

📖 Scenario: You are building a simple API that returns user information. You want to handle errors clearly by sending custom error messages in a structured way.

🎯 Goal: Create a FastAPI app that returns user data for a given user ID. If the user ID is not found, return a custom error response model with a clear message and error code.

📋 What You'll Learn

Create a dictionary called users with user IDs as keys and names as values.

Create a Pydantic model called ErrorResponse with fields error_code (int) and message (str).

Create a GET endpoint /users/{user_id} that returns the user name if found.

If the user ID is not found, return a JSON response using the ErrorResponse model with error_code 404 and a message User not found.

💡 Why This Matters

🌍 Real World

APIs often need to send clear error messages to clients. Custom error response models help keep error data consistent and easy to understand.

💼 Career

Backend developers use FastAPI and Pydantic to build APIs with clear error handling, improving user experience and debugging.

1

Create the initial user data dictionary

Create a dictionary called users with these exact entries: 1: "Alice", 2: "Bob", 3: "Charlie".

FastAPI

# Create the users dictionary with IDs and names
# Your code here

Hint

Use curly braces to create a dictionary with keys 1, 2, 3 and values "Alice", "Bob", "Charlie".

2

Define the custom error response model

Import BaseModel from pydantic and create a class called ErrorResponse that inherits from BaseModel. It should have two fields: error_code of type int and message of type str.

FastAPI

users = {1: "Alice", 2: "Bob", 3: "Charlie"}

# Import BaseModel and create ErrorResponse model
# Your code here

Hint

Use class ErrorResponse(BaseModel): and define the two fields with type annotations.

3

Create the FastAPI app and GET endpoint

Import FastAPI and HTTPException from fastapi. Create a FastAPI app called app. Define a GET endpoint /users/{user_id} that takes user_id as an int path parameter. If user_id is in users, return a dictionary with key name and the user name as value.

FastAPI

from pydantic import BaseModel

users = {1: "Alice", 2: "Bob", 3: "Charlie"}

class ErrorResponse(BaseModel):
    error_code: int
    message: str

# Import FastAPI and create app
# Define GET /users/{user_id} endpoint
# Your code here

Hint

Use @app.get("/users/{user_id}") decorator and an async function with user_id: int parameter.

4

Return custom error response when user not found

In the get_user function, if user_id is not in users, raise HTTPException with status_code=404 and detail set to an instance of ErrorResponse with error_code=404 and message="User not found".

FastAPI

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel

users = {1: "Alice", 2: "Bob", 3: "Charlie"}

class ErrorResponse(BaseModel):
    error_code: int
    message: str

app = FastAPI()

@app.get("/users/{user_id}")
async def get_user(user_id: int):
    if user_id in users:
        return {"name": users[user_id]}
    # Raise HTTPException with ErrorResponse detail if user not found
    # Your code here

Hint

Use raise HTTPException(status_code=404, detail=ErrorResponse(error_code=404, message="User not found").dict()) to send the custom error response.

Practice

1. What is the main purpose of using custom error response models in FastAPI?

easy

A. To define a clear and consistent structure for error messages returned by the API

B. To speed up the API response time

C. To automatically fix errors in the API code

D. To hide all error messages from the client

Solution

1. Step 1: Understand error response models

   Custom error response models define how error messages look, making them clear and consistent.

2. Step 2: Identify the purpose in FastAPI

   FastAPI uses these models to send structured error info to clients, improving API usability.

3. Final Answer:

   To define a clear and consistent structure for error messages returned by the API -> Option A

4. Quick Check:

   Custom error models = clear error messages [OK]

Hint: Custom error models shape error messages clearly [OK]

Common Mistakes:

• Thinking they speed up API responses
• Believing they fix code errors automatically
• Assuming they hide errors completely

2. Which of the following is the correct way to define a custom error response model using Pydantic in FastAPI?

easy

A. class ErrorResponse: message = str; code = int

B. class ErrorResponse(BaseModel): message: str; code: int

C. ErrorResponse = {'message': str, 'code': int}

D. def ErrorResponse(message: str, code: int): return {'message': message, 'code': code}

Solution

1. Step 1: Recognize Pydantic model syntax

   Pydantic models are defined as classes inheriting from BaseModel with typed attributes.

2. Step 2: Match correct syntax

   class ErrorResponse(BaseModel): message: str; code: int correctly defines a class with typed fields using BaseModel.

3. Final Answer:

   class ErrorResponse(BaseModel): message: str; code: int -> Option B

4. Quick Check:

   Pydantic model = class with BaseModel [OK]

Hint: Use class with BaseModel and typed fields [OK]

Common Mistakes:

• Defining models as functions
• Using plain dictionaries instead of classes
• Missing BaseModel inheritance

3. Given this FastAPI code snippet, what will be the response when a ValueError is raised?

from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from pydantic import BaseModel

app = FastAPI()

class ErrorResponse(BaseModel):
    detail: str

@app.exception_handler(ValueError)
async def value_error_handler(request: Request, exc: ValueError):
    return JSONResponse(
        status_code=400,
        content=ErrorResponse(detail=str(exc)).dict()
    )

@app.get("/test")
async def test():
    raise ValueError("Invalid input")

medium

A. Empty response with status 204

B. Plain text 'Invalid input' with status 500

C. {"detail": "Invalid input"} with status 400

D. JSON with key 'error' and message 'Invalid input' with status 400

Solution

1. Step 1: Understand exception handler behavior

   The handler catches ValueError and returns JSONResponse with ErrorResponse model content and status 400.

2. Step 2: Check response content and status

   The content is the dict form of ErrorResponse with detail set to the exception message, so JSON has key 'detail' with 'Invalid input'.

3. Final Answer:

   {"detail": "Invalid input"} with status 400 -> Option C

4. Quick Check:

   Exception handler returns JSON with detail key [OK]

Hint: Exception handler returns model dict as JSON with status [OK]

Common Mistakes:

• Expecting plain text instead of JSON
• Confusing status codes
• Assuming different JSON key names

4. Identify the error in this FastAPI custom error handler code:

from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from pydantic import BaseModel

app = FastAPI()

class ErrorResponse(BaseModel):
    message: str

@app.exception_handler(KeyError)
async def key_error_handler(request: Request, exc: KeyError):
    return JSONResponse(
        status_code=404,
        content=ErrorResponse(message=exc).dict()
    )

medium

A. Missing BaseModel inheritance in ErrorResponse

B. Exception handler must be synchronous, not async

C. Using status code 404 instead of 400

D. Passing the exception object directly instead of converting to string

Solution

1. Step 1: Check how exception is passed to model

   The code passes exc (KeyError object) directly to message field which expects a string.

2. Step 2: Identify correct usage

   It should convert exc to string with str(exc) to avoid type errors.

3. Final Answer:

   Passing the exception object directly instead of converting to string -> Option D

4. Quick Check:

   Exception message must be string [OK]

Hint: Convert exception to string before passing to model [OK]

Common Mistakes:

• Passing exception object without str()
• Confusing async/sync handler rules
• Incorrect status code choice

5. You want to create a FastAPI app that returns a custom error response with fields error_code (int) and error_msg (str) whenever a RuntimeError occurs. Which of the following code snippets correctly implements this behavior?

hard

A. class CustomError(BaseModel): error_code: int; error_msg: str

@app.exception_handler(RuntimeError)
async def runtime_error_handler(request: Request, exc: RuntimeError):
return JSONResponse(status_code=500, content=CustomError(error_code=1001, error_msg=str(exc)).dict())

B. class CustomError(BaseModel): error_code: str; error_msg: int

@app.exception_handler(RuntimeError)
async def runtime_error_handler(request: Request, exc: RuntimeError):
return JSONResponse(status_code=400, content=CustomError(error_code='1001', error_msg=exc).dict())

C. class CustomError:
def __init__(self, error_code, error_msg):
self.error_code = error_code
self.error_msg = error_msg

@app.exception_handler(RuntimeError)
async def runtime_error_handler(request: Request, exc: RuntimeError):
return JSONResponse(status_code=500, content=CustomError(1001, str(exc)))

D. @app.exception_handler(RuntimeError)
async def runtime_error_handler(request: Request, exc: RuntimeError):
return JSONResponse(status_code=500, content={'error_code': 1001, 'error_msg': str(exc)})

Solution

1. Step 1: Define correct Pydantic model

   class CustomError(BaseModel): error_code: int; error_msg: str @app.exception_handler(RuntimeError) async def runtime_error_handler(request: Request, exc: RuntimeError): return JSONResponse(status_code=500, content=CustomError(error_code=1001, error_msg=str(exc)).dict()) defines CustomError inheriting from BaseModel with correct field types (int and str).

2. Step 2: Implement exception handler properly

   class CustomError(BaseModel): error_code: int; error_msg: str @app.exception_handler(RuntimeError) async def runtime_error_handler(request: Request, exc: RuntimeError): return JSONResponse(status_code=500, content=CustomError(error_code=1001, error_msg=str(exc)).dict())'s handler returns JSONResponse with status 500 and content as dict from CustomError instance, converting exception to string.

3. Step 3: Check other options for errors

   class CustomError(BaseModel): error_code: str; error_msg: int @app.exception_handler(RuntimeError) async def runtime_error_handler(request: Request, exc: RuntimeError): return JSONResponse(status_code=400, content=CustomError(error_code='1001', error_msg=exc).dict()) swaps types incorrectly and passes exc without str(); class CustomError: def __init__(self, error_code, error_msg): self.error_code = error_code self.error_msg = error_msg @app.exception_handler(RuntimeError) async def runtime_error_handler(request: Request, exc: RuntimeError): return JSONResponse(status_code=500, content=CustomError(1001, str(exc))) uses plain class not BaseModel and returns object not dict; @app.exception_handler(RuntimeError) async def runtime_error_handler(request: Request, exc: RuntimeError): return JSONResponse(status_code=500, content={'error_code': 1001, 'error_msg': str(exc)}) skips model usage.

4. Final Answer:

   Option A correctly defines model and handler returning proper JSON response -> Option A

5. Quick Check:

   Use BaseModel with typed fields and dict() in handler [OK]

Hint: Use BaseModel and dict() for error response content [OK]

Common Mistakes:

• Swapping field types in model
• Not converting exception to string
• Returning model instance instead of dict
• Skipping Pydantic model for error response