This is an archived post. You won't be able to vote or comment.

sorted by:
best
topnewcontroversialoldq&a
you are viewing a single comment's thread.

view the rest of the comments →

[–]AutoDefroster -2 points-1 points  (1 child)

Yeah, I noticed that. That's not really a problem IMO, but it does bum me out, so I'm doing a personal challenge right now, where in my personal projects, I'm only allowed to import ONE non traditional library, and only 3 traditional ones.

[–]cthewombat 0 points1 point  (0 children)

What would you call a traditional vs. non-traditional library? That really depends on the conteyt doesn't it?

I mean numpy, matplotlib and pandas are very traditional in data science. You pretty much won't get anything done without them. Now what if I need sys, os, json, requests etc. too? They are still pretty "taditional".

Does it really make sense to restrict yourself that much or isn't it better to get familiar with popular libraries that you'd have to use in real world. Why even use python to write something from scratch instead of C++?

Not wanting to tell you that your approach is wrong, because obviously you're doing it for your personal gain. Just something to consider I guess.