Debugging Python code becomes significantly harder once applications move beyond local scripts and into real environments. Logs are incomplete, errors are intermittent, and reproducing failures is often non-trivial.

This talk focuses on practical debugging techniques for Python applications, emphasizing tools and workflows that developers can apply immediately. Rather than relying on theoretical examples, the session walks through realistic failure scenarios and shows how to diagnose them using Python’s built-in and ecosystem tooling.

Topics include structured logging, stack trace analysis, runtime inspection, and controlled reproduction of bugs. Attendees will see how to move from vague error reports to actionable fixes, even when issues cannot be reproduced locally on the first attempt.

All examples use small, reproducible Python programs that attendees can run on their own machines. The goal is not to introduce new frameworks, but to build confidence and intuition around debugging techniques that work across different kinds of Python applications.

By the end of the talk, attendees will be better equipped to debug issues in unfamiliar codebases, reason about failures under incomplete information, and reduce time spent guessing at the root cause of bugs.

Debugging Python in Production: Practical Techniques Beyond Print Statements - Anshul Jannumahanti