Error Handling in Flask APIs addresses a recurring problem in Python projects: Turn expected exceptions into consistent responses while keeping unexpected failures observable. This guide explains the mechanism, provides an executable example, and identifies the boundaries that keep an implementation reliable.
Concept and use case
Flask looks up handlers by status code and then exception hierarchy, selecting the most specific match. A handler must return the proper status.
For the related fundamentals, also read the Flask API guide. Integration stays simpler when functions receive dependencies and data explicitly instead of relying on global state.
Practical example
from flask import Flask, jsonify
from werkzeug.exceptions import HTTPException
app = Flask(__name__)
@app.errorhandler(HTTPException)
def http_error(error):
response = error.get_response()
response.data = jsonify(
code=error.code,
message=error.description,
).get_data()
response.content_type = "application/json"
return responseDefine specific domain exceptions, preserve HTTPException headers, and use a stable error envelope with a code and safe message.
Important decisions
The correct choice depends on the public contract, expected volume, and failure behavior.
Consider concurrency, empty inputs, and partial failures. Document every limit that affects consumers and choose names that express intent.
Common mistakes
A minimal example does not replace bounds, error handling, and observability. A broad Exception handler can swallow 404 and 405 or hide bugs. Never return tracebacks or database errors to clients.
Avoid catching exceptions without context or returning partial output as if it were complete. An explicit failure is usually safer than silently incorrect data.
How to validate
Validate behavior, not only the happy path. Test a known error, unknown route, wrong method, and unexpected exception, checking status, content type, and logs.