Developers tend to ignore that users can be more creative than them. Use their debugging skills for your own benefit: post-mortem debugging is one of the most important features your web framework can provide. This talk will cover some of the simplest practices and available tools for debugging on production environments and to immediately improve quality of your web applications.

1. POST-MORTEM DEBUGGING
AND WEB DEVELOPMENT
Alessandro Molina
@__amol__
amol@turbogears.org

2. Who am I
● CTO @ Axant.it, mostly Python company
(with some iOS and Android)
● TurboGears2 devteam member
● Contributions to web world python libraries
○ MING MongoDB ODM
○ ToscaWidgets2
○ Formencode

3. Why
● Debugging is a core part of the
development process.
● You can try to prevent issues as much as
possible, but users will find new ones.
● Gathering informations to replicate issues
is required to fix them

4. Debugging

5. At least know you have an issue.
● Debugging is the “process of finding and
reducing the number of bugs”
● Users are already doing half of the work.
● When users find a bug for you, make sure
to be aware that they found it
● Log it or it will be forgotten

6. Log what you really need
● Log to replicate
○ Then you are able to write tests that actually verify
the issue has been solved.
● You probably want to log:
○ WSGI Environ
○ Traceback
○ Last N stack frames local variables
○ Request Headers & Body (when size permits)

7. Log in an useful way
● Log data in an easy to use way
○ Log request in a way it’s quick to replay it
○ Log in a computer friendly format for test units
○ Request dump is good: netcat to replay it and is
already understood by computers.
● Organize your informations
○ Use a tool to group and avoid duplicates
○ Know what got solved and what didn’t
○ Log by email, so you don’t have to check yourself

8. Log or...

9. But log in a separate thread or...

10. Crash Report
● Many middlewares and frameworks
provide exception reporting by email:
○ pyramid_exclog (Pyramid)
○ WebError (Pylons)
○ BackLash (TurboGears)
○ Django & Flask, framework provided
● Logging module has what you need:
Logger.exception + handlers.SMTPHandler

11. Ready-Made Email Reporting
● Looking for a stand-alone solution?
○ Backlash can be used by itself, not bound to
TurboGears.
○ Only dependency is “WebOb”
● Supports both Python2 and Python3
from backlash.trace_errors import EmailReporter
email_reporter = EmailReporter(smtp_server="localhost",
error_email="email@host.com",
from_address="errors@host.com")
app = backlash.TraceErrorsMiddleware(app, [email_reporter])

12. Try Sentry
● Gathers data and detects duplicates
● Provides “Reply Request” button
● Mark exceptions as solved to keep track
● Can log multiple events, not only
exceptions
from backlash.trace_errors.sentry import SentryReporter
sentry_reporter = SentryReporter(sentry_dsn="http://public:secret@example.com/1")
app = backlash.TraceErrorsMiddleware(app, [sentry_reporter])

13. Sentry

14. See what’s happening now
● On development and test environments
receiving errors by email is not convenient
● In case of freezes you don’t get an
exception that can be reported
● Some problems need to be
troubleshooted on the fly

15. Interactive Debugger
● Python provides built-in Post Mortem
debugging through pdb module
try:
return app(environ, start_response)
except:
import pdb
pdb.post_mortem()
● While it’s ready to use and works great it’s
not the most comfortable tool when
working on web development

16. Browser Debugger
● Many frameworks have browser debugger
○ Pyramid DebugBar
○ Werkzeug DebuggedApplication
○ TurboGears ErrorWare
● BackLash provides a stand-alone version
of the Werkzeug debugger.
import backlash
app = backlash.DebuggedApplication(app)

17. Werkzeug/BackLash Debugger

18. Browser Debugger Console
● Browser debuggers usually implement a
special URL with an interactive console
that runs in the context of the application.
● Use it to see what’s happening right now
○ for threadId, stack in sys._current_frames().items()
● Try /__console__ on Werkzeug or Backlash

19. Production Debugging
● In-browser debugger must be disabled on
production environments
○ Unless you are PythonAnyware you want to block
people from running code on your servers.
● So we are back again at the starting point
○ How do I debug issues that don’t provide an
exception traceback on production?

20. Attaching to running processes
To inspect running applications you can rely
on tools like ispyd and pyrasite that are able
to attach to a running python process
from ispyd.plugins.wsgi import
WSGIApplicationWrapper
app = WSGIApplicationWrapper(app)

21. ispyd
(wsgi:18630) requests
No active transactions.
(wsgi:18630) requests
==== 67 ====
thread_id = 140735076232384
start_time = Mon Apr 9 21:49:54 2012
duration = 0.013629 seconds
HTTP_HOST = 'localhost:5000'
QUERY_STRING = ''
…
File: "wsgi.py", line 19, in hello
time.sleep(0.05)

22. Pyrasite

23. Not only Debugging
● Debugging tools can also help in finding
and solving performance issues
● When a request is taking a lot of time, just
attach ipsyd and see what it’s happening
● There are specific tools that can
proactively notify you of slow requests

24. Slow Requests Tracing
● Backlash provides slow request tracing for
any WSGI framework.
● Dogslow: a Django tool created by
Bitbucket guys to monitor slow requests
● Both Notify you by email, no need to check
○ Backlash can also use any backlash reporter, for
example by reporting slow requests on sentry.

25. Slow Requests Tracing
● Setting up slow request reporting is
incredibly simple both with Backlash and
Dogslow
import backlash
from backlash.trace_errors import EmailReporter
email_reporter = EmailReporter(smtp_server="localhost",
error_email="email@host.com",
from_address="errors@host.com")
app = backlash.TraceSlowRequestsMiddleware(app, [email_reporter])

26. New Relic
● Full stack tracing
○ Controllers
○ SQLAlchemy queries
○ Background Tasks
○ External Services
○ Groups informations by controller, not URL
● On-Demand profiling
○ Turn On / Off controllers profiling from remote

27. New Relic

28. Slow requests stack trace might
not be enough

29. Profiling
● Full profiling has a big cost, so it is usually
constrained to development environment
● If you want to profile on production,
perform sampling, don’t profile every
request
● Use a Low Overhead profiler like PLOP, not
built-in profile module.

30. Questions?