Nope. I am working with geodata so I need geopandas for my work. Sadly, there is no serious alternative until now. If, in the future, that will change, I am am absolutely on board giving polars a try.

Syntax highlighting in REPL as you type is big

pip cannot install some system dependencies your library might need. Windows is extra difficult sometimes, as the library might require some paths during installation, Linux is way easier for this kind of stuff. Either you use WSL, or you follow these instructions for Windows I found by googling https://github.com/luarocks/luarocks/blob/main/docs/installation_instructions_for_windows.md

I use Mint btw

Sir, I will make sure to never bother you with a PR and my terrible, terrible code ;)

This is what I would come up with:

try:
    if len(foo) == 0:
    ...
except TypeError:
    ...

There is no need to add a None check, as foo being None should be considered as a faulty input. Avoiding the possibility of foo being None from the beginning using static checks or testing is of course the preferred solution. But in reality we do not work in such optimal environments, at least I can say that from the perspective of data science, where often procedural, untested code is produced that runs only a few times. But I get your point and I think both paths are viable, but I am also okay with being in the wrong here,

I am not saying it’s better, just that I don’t like the proposed way :) I would argue that being “pythonic” has even less value than the Zen, which I quoted because it’s true, not because it is some strict rule (which it isn’t anyway).

You could argue I also need to write that extra code for the if not case, as I explicitly have to check if it is None if my program somewhere further down expects only lists.

Hunting for those sweet milliseconds is a popular game in the Python community ;) if this mechanism is that important for your program, you should definitely use it, I would do as well!

But None has no len

if not foo:  

-> foo could be an empty list or None, it is ambiguous.

len(foo) will lead to an exception TypeError if foo is None, I can cleanly catch that.

It suggests I deal with a boolean when that is not the case. Explicit is better than implicit, and if not foo to check for an empty list may be pythonic, but it’s still implicit af

I don’t like it very much, my variable could also be None here

Absolutely agree. I just use it for some simple stuff like “every nth row in a pandas dataframe slice a string from x to y if column z is True” or something like that. These logics take time to write, and GPT usually comes up with a right solution or one that doesn’t need a lot of modification.

But debugging or analyzing an error? No thanks

Why is the European Space Agency speaking up to this topic

Wow, I hope you’re not connected to the web

This article is about Python venvs using Docker. That I wouldn’t want to pollute the base installation on my local machine should be clear.

But you can just create a venv and install everything in there, no need to create dozens of venvs if that’s what you want.

I am not sure what you mean. Once you created a venv you can always reuse it.

Soon, you won’t have a choice because major distros are adopting PEP 668. This will make pip install fail in the default system Python and show an error telling you to use a virtual environment.

Well, if this is true then why bother convincing people ;)

Wdym? It’s a text about the lesser known features and changes in Python 3.13.

Removed by mod

It makes no sense to discuss here.They probably follow Russia’s narrative of Europe being a puppet of the US.

Lol, ml. users getting wild in the comments

deleted by creator

Nice I guess it’s time to check if my daily used libraries have stable 3.12 releases already.

I guess the free-threaded mode and the JIT compiler will be the most important features from what I read, but their significance is out of my expertise.

My absolute favorite with this update is the new REPL! It features Multiline-editing and a paste mode for easier pasting code. It also added the spaces automatically in my example.

Sometimes I want to make some quick tests on some data in the terminal without installing IPython to my environment first, this is great news!

This new error message will also be very useful for beginners and relieve StackOverflow:

AttributeError: module 'numpy' has no attribute 'array' (consider renaming '/home/me/numpy.py' if it has the same name as a third-party module you intended to import)