[mr_mitm]

> People can't even be bothered to read docs but will just blindly install a package just because someone was able to package it and upload it to PyPI.

That's a straw man argument. No one said "blindly". You can very well carefully consider the pros and cons of adding a dependency and arrive at the conclusion that it makes sense. Many PyPI packages are in the Debian stable repositories, you could use that as an additional barrier as well.

[freehorse]

To be fair, comment^^ actually said

    choice between "reading docs/changelogs carefully, implementing functions", and "adding an extra dependency"

which is what comment^ answers to, which to me actually sounds like that the added dependency comes in place of "reading docs/changelogs carefully".

I think it matters a lot how much one can trust a 3rd party library, how much it is used, how much it is maintained etc. Moreover, it also matters how central and important this is to what you are actually doing, for example if the datetimes I come across are pretty much specific and with limited scope, I would probably care about reading docs less than if I am reading data with datetimes that may be totally wild. Furthermore, there are some libraries that are just considered the standard in some fields. If I use python I call pandas to read csvs, I am obviously not gonna write my own csv parser. It will also make your code more readable for others that already know and use the same libraries if they are so standard. But that's probably a very small minority of libraries that people actually use in certain languages.

[robertlagrant]

> If I use python I call pandas to read csvs

So it's you that isn't just using the built in csv parser in this project I inherited. Come back and repent.

[akerl_]

How could it possibly be true that libraries that are so commonly used that you consider them “the standard” are so infrequently used as to be a “very small minority” of libraries people actually use?

[freehorse]

I am not sure I understand the comment. I used pandas as an example of sth I frequently encounter when dealing with python code dealing with data frames. Is it not commonly used? What’s your argument here, I am genuinely asking.

[akerl_]

I'm trying to square two aspects of your comment:

> Some libraries are so common that basically everybody uses them, to the point that they're considered the standard and they don't count when I raise complaints about people pulling in dependencies

> "But that's probably a very small minority of libraries that people actually use in certain languages."

It seems like by definition, the majority of libraries that people are actually using are going to be the popular ones that everybody is using.