New in version 0.3.
Applications fail, servers fail. Sooner or later you will see an exception in production. Even if your code is 100% correct, you will still see exceptions from time to time. Why? Because everything else involved will fail. Here are some situations where perfectly fine code can lead to server errors:
- the client terminated the request early and the application was still reading from the incoming data
- the database server was overloaded and could not handle the query
- a filesystem is full
- a harddrive crashed
- a backend server overloaded
- a programming error in a library you are using
- network connection of the server to another system failed
And that’s just a small sample of issues you could be facing. So how do we
deal with that sort of problem? By default if your application runs in
production mode, Flask will display a very simple page for you and log the
exception to the
But there is more you can do, and we will cover some better setups to deal with errors.
Error Logging Tools¶
Sending error mails, even if just for critical ones, can become overwhelming if enough users are hitting the error and log files are typically never looked at. This is why we recommend using Sentry for dealing with application errors. It’s available as an Open Source project on GitHub and is also available as a hosted version which you can try for free. Sentry aggregates duplicate errors, captures the full stack trace and local variables for debugging, and sends you mails based on new errors or frequency thresholds.
To use Sentry you need to install the raven client:
$ pip install raven
And then add this to your Flask app:
from raven.contrib.flask import Sentry sentry = Sentry(app, dsn='YOUR_DSN_HERE')
Or if you are using factories you can also init it later:
from raven.contrib.flask import Sentry sentry = Sentry(dsn='YOUR_DSN_HERE') def create_app(): app = Flask(__name__) sentry.init_app(app) ... return app
The YOUR_DSN_HERE value needs to be replaced with the DSN value you get from your Sentry installation.
Afterwards failures are automatically reported to Sentry and from there you can receive error notifications.
You might want to show custom error pages to the user when an error occurs. This can be done by registering error handlers.
An error handler is a normal view function that return a response, but instead of being registered for a route, it is registered for an exception or HTTP status code that would is raised while trying to handle a request.
@app.errorhandler(werkzeug.exceptions.BadRequest) def handle_bad_request(e): return 'bad request!', 400 # or, without the decorator app.register_error_handler(400, handle_bad_request)
Non-standard HTTP codes cannot be registered by code because they are not known
by Werkzeug. Instead, define a subclass of
HTTPException with the appropriate code and
register and raise that exception class.
class InsufficientStorage(werkzeug.exceptions.HTTPException): code = 507 description = 'Not enough storage space.' app.register_error_handler(InsuffcientStorage, handle_507) raise InsufficientStorage()
Handlers can be registered for any exception class, not just
HTTPException subclasses or HTTP status
codes. Handlers can be registered for a specific class, or for all subclasses
of a parent class.
When an exception is caught by Flask while handling a request, it is first
looked up by code. If no handler is registered for the code, it is looked up
by its class hierarchy; the most specific handler is chosen. If no handler is
HTTPException subclasses show a
generic message about their code, while other exceptions are converted to a
generic 500 Internal Server Error.
For example, if an instance of
ConnectionRefusedError is raised, and a handler
is registered for
the more specific
ConnectionRefusedError handler is called with the
exception instance to generate the response.
Handlers registered on the blueprint take precedence over those registered globally on the application, assuming a blueprint is handling the request that raises the exception. However, the blueprint cannot handle 404 routing errors because the 404 occurs at the routing level before the blueprint can be determined.
Changed in version 0.11: Handlers are prioritized by specificity of the exception classes they are registered for instead of the order they are registered in.
Debugging Application Errors¶
For production applications, configure your application with logging and notifications as described in Application Errors. This section provides pointers when debugging deployment configuration and digging deeper with a full-featured Python debugger.
When in Doubt, Run Manually¶
Having problems getting your application configured for production? If you have shell access to your host, verify that you can run your application manually from the shell in the deployment environment. Be sure to run under the same user account as the configured deployment to troubleshoot permission issues. You can use Flask’s builtin development server with debug=True on your production host, which is helpful in catching configuration issues, but be sure to do this temporarily in a controlled environment. Do not run in production with debug=True.
Working with Debuggers¶
To dig deeper, possibly to trace code execution, Flask provides a debugger out of the box (see Debug Mode). If you would like to use another Python debugger, note that debuggers interfere with each other. You have to set some options in order to use your favorite debugger:
debug- whether to enable debug mode and catch exceptions
use_debugger- whether to use the internal Flask debugger
use_reloader- whether to reload and fork the process on exception
debug must be True (i.e., exceptions must be caught) in order for the other
two options to have any value.
If you’re using Aptana/Eclipse for debugging you’ll need to set both
use_reloader to False.
A possible useful pattern for configuration is to set the following in your config.yaml (change the block as appropriate for your application, of course):
FLASK: DEBUG: True DEBUG_WITH_APTANA: True
Then in your application’s entry-point (main.py), you could have something like:
if __name__ == "__main__": # To allow aptana to receive errors, set use_debugger=False app = create_app(config="config.yaml") if app.debug: use_debugger = True try: # Disable Flask's debugger if external debugger is requested use_debugger = not(app.config.get('DEBUG_WITH_APTANA')) except: pass app.run(use_debugger=use_debugger, debug=app.debug, use_reloader=use_debugger, host='0.0.0.0')