Why 'It Works on My Machine' Isn't Enough in Python
Key Takeaways
The video discusses the importance of testing and debugging Python code in different environments to avoid issues that may arise when the code is run on another machine or in production, highlighting the limitations of the 'it works on my machine' approach.
Full Transcript
it works on my machine why hand your code off to someone else or gets run in production and something ends up being different there are you running with the debug flag on or in the database side your schema doesn't match the other person's schema you've got a record the other person doesn't or they have something triggering the problem that you don't which browser you're using what cookies are set yesterday I ordered a pizza there's this final confirm step that doesn't look like a final confirm step and every once in a while I forget to hit that actual button they hadn't got my order and what was I talking about and so I came back up to my apartment and sure enough my pizza was still in the shopping cart the coding equivalent of this is failing to commit or merge or being on a different branch the difference in CPU speed or network speed between machines might actually hide a race condition which only gets triggered somewhere else so when it gets a bigger processor it starts to fall over or it gets a slower network speed and it starts to fall over
Original Description
From our podcast, episode 219. #programming #python #pythonprogramming #PythonPodcast #LearnPython #coding #bugs #shorts
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