scharf_2x40
I found this, which dives deeper into the impact of inefficient software.
Yeah that point was not entirely accurate. What I meant was, that a np.array and a list don’t work together. Coming from julia and matlab it just does not make sense to me, why I can’t use a function written for a list for a np.array even if they basically represent the exaxt same thing.
Julia for example hast linalg as a module but functions work on lists with no problem.
Python is strongly typed, but dynamically checked. Working with other languages I just found, that the type errors in python are the hardest to catch and to debug, but maybe I am just more used to othet languages
I see it’s use as language to write small scripts, I just don’t see much use besides that.
Here is a article talking about the speed of compiled python vs Julia. I don’t see why it is better to go to all these extra steps just to end up with something slower. https://www.matecdev.com/posts/julia-python-numba-cython.html
Yeah, ofc every language must have a type system, the problem is, that this is not enforced. I.e 3 == ‘3’ throws no error, when working with dataframes for example this can be a pain in the ass. But yeah, I don’t say that nobody should use Python (although the title is a bit dramatic) I just think that there are better alternatives out there.