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The lack of dependency awareness drives me insane. Someone imports a single method from the wrong package, which snowballs into the blind leading the blind and pinning transitive dependencies in order to deliver quick "fixes" for things we don't even use or need, which ultimately becomes 100 different kinds of nightmare that stifle any hope of agility.


In a code review a couple of years ago, I had to say "no" to a dev casually including pandas (and in turn numpy) for a one-liner convenience function in a Django web app that has no involvement with any number crunching whatsoever.


Coincidentally, Copilot has been incredibly liberal lately with its suggestions of including Pandas or Numpy in a tiny non-AI Flask app, even for simple things. I expect things to get worse.


There's a ton you can do with sqlite, which is in the Python standard library. You just have to think about it and write some SQL instead of having a nice Pythonic interface.


To push back on this, I consider pandas/numpy so crucial to Python as a whole they are effectively stdlib to me. I wouldn't blink at this because it would happen sooner or later.

Unless is was absolutely critical the server have as small as a footprint as humanly possible and it was absolutely guaranteed there would never need to be included in the future of course. However, that first constraint is the main one.


You forgot the "/s"?


Automated dependency resolution has made it so the default is frequently

> Someone imports a single method from the RIGHT package

and hundreds of megabytes come in for what might be one simple function.




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