Debugging Python Projects With PySnooper


December 8th, 2019

45 mins 30 secs

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About this Episode


Debugging is a painful but necessary practice in software development. The tools that are available in Python range from the built-in debugger, to tools integrated with your coding environment, to the trusty print function. In this episode Ram Rachum describes his work on PySnooper and how it can be used to speed up your problem solving in complex or legacy applications.


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  • Your host as usual is Tobias Macey and today I’m interviewing Ram Rachum about PySnooper, an alternative approach to debugging your python projects


  • Introductions
  • How did you get introduced to Python?
  • How do developers normally debug their code, and what need does PySnooper address that isn’t addressed by the established methods?
  • What is the workflow for using PySnooper for investigating or debugging a project? (This will probably be answered in the answer to the question above)
  • What are some of the pieces of information that it surfaces and how do they aid the developer in directing their investigation?
  • What were some of the projects that you were testing it with and how did they influence the direction that you took PySnooper?
  • Can you describe how PySnooper is implemented and some of the ways that it has evolved since you first began working on it?
  • What are some of the initial goals that you had for the project which you have since abandoned as either not useful or too challenging to implement?
  • What are some of the edge cases or technical challenges that you have encountered while working on PySnooper, either in Python itself or in the tool?
  • There is another project called Snoop which builds on top of your work on PySnooper to add some extra functionality and developer ergonomics. What, if anything, was your reaction to it and how has it influenced your work on PySnooper?
  • One of the notable aspects of your work on PySnooper is the amount of attention that it garnered shortly after you published it. How has that visibility affected the long-term popularity and use of PySnooper?
  • What have been some of the most interesting, unexpected, or difficult aspects of creating, maintaining, and promoting PySnooper?
  • What do you have planned for the future of the project?

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