Introduction

Flask is a powerful and lightweight web framework, but without proper error handling and logging, debugging issues can become challenging. Implementing structured logging and error handling helps maintain application stability, improve debugging, and enhance security.

In this blog, we will explore best practices for handling exceptions, logging errors, and integrating monitoring tools in Flask applications.

Error Handling in Flask

Using Flask’s Built-in Error Handlers

Flask allows you to define custom error handlers for different HTTP status codes using the `@app.errorhandler` decorator.

from flask import Flask, jsonify

app = Flask(__name__)

@app.errorhandler(404)
def not_found_error(error):
return jsonify({"error": "Resource not found"}), 404

@app.errorhandler(500)
def internal_error(error):
return jsonify({"error": "Internal server error"}), 500

if __name__ == '__main__':
app.run(debug=True)

This ensures that structured JSON responses are returned instead of plain-text error messages.

Handling Custom Exceptions

For better control, define custom exception classes to handle specific errors.

class CustomAPIException(Exception):
def __init__(self, message, status_code=400):
super().__init__(message)
self.message = message
self.status_code = status_code

@app.errorhandler(CustomAPIException)
def handle_custom_exception(error):
response = jsonify({"error": error.message})
response.status_code = error.status_code
return response

@app.route('/test-error')
def test_error():
raise CustomAPIException("This is a custom error", 422)

This allows for better debugging and structured error responses across the application.

Logging Best Practices

Configuring Python’s Logging Module

Flask’s default logging is minimal. To improve it, configure structured logging using Python’s `logging` module.

import logging

logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(levelname)s - %(message)s",
handlers=[
logging.FileHandler("app.log"),  # Save logs to a file
logging.StreamHandler()  # Output logs to the console
]
)

logger = logging.getLogger(__name__)

@app.route('/log-test')
def log_test():
logger.info("This is an info log")
logger.error("This is an error log")
return "Logs recorded!"

This setup ensures:
✔ Log rotation (avoiding large log files)
✔ Multiple handlers (console + file logging)
✔ Standardized formatting

Logging Errors to External Services

To monitor logs in real-time, integrate external tools like Sentry.

import sentry_sdk
from sentry_sdk.integrations.flask import FlaskIntegration

sentry_sdk.init(
dsn="your_sentry_dsn",
integrations=[FlaskIntegration()],
traces_sample_rate=1.0
)

@app.route('/sentry-error')
def sentry_error():
1 / 0  # Simulating an error

This captures all exceptions and logs them in Sentry’s dashboard for quick debugging.

Best Practices for Production

✔ Use structured logging (JSON format for better analysis)
✔ Avoid exposing sensitive data in error messages
✔ Monitor logs in real-time using APM tools like Sentry, Datadog, or ELK Stack
✔ Log request/response data only if necessary to avoid performance overhead
✔ Use log levels effectively – DEBUG for development, INFO for general logs, ERROR for failures

Conclusion

Implementing structured error handling and logging in Flask improves application reliability, debugging efficiency, and security. By using custom exceptions, structured logging, and monitoring tools, you can build a robust and maintainable Flask application.

Start logging smarter today! 🚀