Home Backend Development Python Tutorial How to Customize Error Responses for Specific Routes in FastAPI?

How to Customize Error Responses for Specific Routes in FastAPI?

Nov 20, 2024 am 12:54 AM

How to Customize Error Responses for Specific Routes in FastAPI?

How to Customize Error Response for a Specific Route in FastAPI

In FastAPI, you can customize the error response for a specific route by overriding the exception handler for RequestValidationError. Here are a few options:

Option 1 (Simple)

If you don't mind having the Header appear as Optional in the OpenAPI documentation, you can use the following code:

from fastapi import Header, HTTPException

@app.post("/")
def some_route(some_custom_header: Optional[str] = Header(None)):
    if not some_custom_header:
        raise HTTPException(status_code=401, detail="Unauthorized")
    return {"some-custom-header": some_custom_header}
Copy after login

Option 2 (Custom Exception Handler)

To have the Header appear as required in the OpenAPI documentation, you can override the exception handler:

from fastapi import FastAPI, Request, Header, status
from fastapi.exceptions import RequestValidationError
from fastapi.responses import JSONResponse
from fastapi.encoders import jsonable_encoder

app = FastAPI()
routes_with_custom_exception = ["/"]

@app.exception_handler(RequestValidationError)
async def validation_exception_handler(request: Request, exc: RequestValidationError):
    if request.url.path in routes_with_custom_exception:
        # Check for the specific Header in the errors
        for err in exc.errors():
            if err['loc'][0] == 'header' and err['loc'][1] == 'some-custom-header':
                return JSONResponse(content={'401': 'Unauthorized'}, status_code=401)
            
    return JSONResponse(
        status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
        content=jsonable_encoder({'detail': exc.errors(), 'body': exc.body}),
    )

@app.get("/")
def some_route(some_custom_header: str = Header(...)):
    return {'some-custom-header': some_custom_header}
Copy after login

Option 3 (Sub-Application)

You can create a sub-application and mount it to the main app. This will allow you to customize the exception handler only for the routes defined in the sub-application:

from fastapi import FastAPI, Request, Header
from fastapi.exceptions import RequestValidationError
from fastapi.responses import JSONResponse

app = FastAPI()

@app.get('/')
async def main():
    return {'message': 'Hello from main API'}
    

subapi = FastAPI()
   
@subapi.exception_handler(RequestValidationError)
async def validation_exception_handler(request: Request, exc: RequestValidationError):
    # Custom exception handling
    return JSONResponse(content={'401': 'Unauthorized'}, status_code=401)


@subapi.get('/')
async def sub_api_route(some_custom_header: str = Header(...)):
    return {'some-custom-header': some_custom_header}    


app.mount('/sub', subapi)
Copy after login

Option 4 (Custom APIRouter and Exception Handling)

You can use a custom APIRouter class and handle exceptions inside a try-except block:

from fastapi import FastAPI, APIRouter, Response, Request, Header, HTTPException
from fastapi.responses import JSONResponse
from fastapi.exceptions import RequestValidationError
from fastapi.routing import APIRoute
from typing import Callable

class ValidationErrorHandlingRoute(APIRoute):
    def get_route_handler(self) -> Callable:
        original_route_handler = super().get_route_handler()

        async def custom_route_handler(request: Request) -> Response:
            try:
                return await original_route_handler(request)
            except RequestValidationError as e:
                # Custom exception handling
                raise HTTPException(status_code=401, detail='401 Unauthorized')
                            
        return custom_route_handler


app = FastAPI()
router = APIRouter(route_class=ValidationErrorHandlingRoute)


@app.get('/')
async def main():
    return {'message': 'Hello from main API'}
    

@router.get('/custom')
async def custom_route(some_custom_header: str = Header(...)):
    return {'some-custom-header': some_custom_header}


app.include_router(router)
Copy after login

Choose the option that best suits your requirements.

The above is the detailed content of How to Customize Error Responses for Specific Routes in FastAPI?. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Roblox: Bubble Gum Simulator Infinity - How To Get And Use Royal Keys
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Nordhold: Fusion System, Explained
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Mandragora: Whispers Of The Witch Tree - How To Unlock The Grappling Hook
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1671
14
PHP Tutorial
1276
29
C# Tutorial
1256
24
Python vs. C  : Learning Curves and Ease of Use Python vs. C : Learning Curves and Ease of Use Apr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and Time: Making the Most of Your Study Time Python and Time: Making the Most of Your Study Time Apr 14, 2025 am 12:02 AM

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python vs. C  : Exploring Performance and Efficiency Python vs. C : Exploring Performance and Efficiency Apr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Learning Python: Is 2 Hours of Daily Study Sufficient? Learning Python: Is 2 Hours of Daily Study Sufficient? Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python vs. C  : Understanding the Key Differences Python vs. C : Understanding the Key Differences Apr 21, 2025 am 12:18 AM

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Which is part of the Python standard library: lists or arrays? Which is part of the Python standard library: lists or arrays? Apr 27, 2025 am 12:03 AM

Pythonlistsarepartofthestandardlibrary,whilearraysarenot.Listsarebuilt-in,versatile,andusedforstoringcollections,whereasarraysareprovidedbythearraymoduleandlesscommonlyusedduetolimitedfunctionality.

Python: Automation, Scripting, and Task Management Python: Automation, Scripting, and Task Management Apr 16, 2025 am 12:14 AM

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

Python for Web Development: Key Applications Python for Web Development: Key Applications Apr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

See all articles