If this is from the perspective of a hobbyist or brand new Python dev, that’s a fair opinion to have, I suppose.
That said, if you’re using Python in a professional capacity, you really need to learn how to use the toolchain properly.
Python packaging and virtual environments are not difficult to understand, and I’d wager based on your comments elsewhere in this thread that your frustrations are born from not taking the time to understand why following the instructions from a fourteen-year-old blog post aren’t working.
99.99% of the time, the fault isn’t with pip, it’s with the maintainer of the broken package you’re trying to use.
Most importantly: which tool should a beginner use? The PyPA has a few guides and tutorials, one is using pip + venv, another is using pipenv (why would you still do that?), and another tutorial that lets you pick between Hatchling (hatch’s build backend), setuptools, Flit, and PDM, without explaining the differences between them
If you’re using a manually managed venv, you need to remember to activate it, or to use the appropriate Python.
That really doesn’t seem like a big ask.
I’ve been using python professionally for like 10 years and package management hasn’t really been a big problem.
If you’re doing professional work, you should probably be using docker or something anyway. Working on the host machine is just asking for “it works on my machine what do you mean it doesn’t work in production?” issues.
No, actually most devs don’t use docker like that. Not java devs, not JS devs, not rust devs. That is because maven, npm and cargo manage dependencies per project. You use it for python exactly because pip does it the wrong way and python has big compatibility issues.
Friend, while I appreciate the time and effort on the docs, it has a rather tiny section on one of the truly worst aspects of pip (and the only one that really guts usability): package conflicts.
Due to the nature of Python as an interpreted language, there is little that you can check in advance via automation around “can package A and package B coexist peacefully with the lowest common denominator of package X”? Will it work? Will it fail? Run your tool/code and hope for the best!
Pip is a nightmare with larger, spawling package solutions (i.e. a lot of the ML work out there). But even with the freshest of venv creations, things still go remarkably wrong rather quick in my experience. My favorite is when someone, somewhere in the dependency tree forgets to lock their version, which ends up blossoming into a ticking time bomb before it abruptly stops working.
Hopefully, your experiences have been far more pleasant than mine.
If this is from the perspective of a hobbyist or brand new Python dev, that’s a fair opinion to have, I suppose.
That said, if you’re using Python in a professional capacity, you really need to learn how to use the toolchain properly.
Python packaging and virtual environments are not difficult to understand, and I’d wager based on your comments elsewhere in this thread that your frustrations are born from not taking the time to understand why following the instructions from a fourteen-year-old blog post aren’t working.
99.99% of the time, the fault isn’t with pip, it’s with the maintainer of the broken package you’re trying to use.
I have to agree, I maintain and develop packages in fortrat/C/C++ that use Python as a user interface, and in my experience pip just works.
You only need to throw together a ≈30 line
setup.pyand a 5 line bash script and then you never have to think about it again.This article someone linked is not 14 years old and it perfectly describes the mess python and pip are: https://chriswarrick.com/blog/2023/01/15/how-to-improve-python-packaging/
My favorite part is:
But yes, following old blog post is the issue.
That really doesn’t seem like a big ask.
I’ve been using python professionally for like 10 years and package management hasn’t really been a big problem.
If you’re doing professional work, you should probably be using docker or something anyway. Working on the host machine is just asking for “it works on my machine what do you mean it doesn’t work in production?” issues.
No, actually most devs don’t use docker like that. Not java devs, not JS devs, not rust devs. That is because maven, npm and cargo manage dependencies per project. You use it for python exactly because pip does it the wrong way and python has big compatibility issues.
Why not read the official python docs?
Hahaha!..
Oh shit, you’re serious.
They pretty simply describe how to handle a venv, pip, reqs, etc.
Friend, while I appreciate the time and effort on the docs, it has a rather tiny section on one of the truly worst aspects of pip (and the only one that really guts usability): package conflicts.
Due to the nature of Python as an interpreted language, there is little that you can check in advance via automation around “can package A and package B coexist peacefully with the lowest common denominator of package X”? Will it work? Will it fail? Run your tool/code and hope for the best!
Pip is a nightmare with larger, spawling package solutions (i.e. a lot of the ML work out there). But even with the freshest of venv creations, things still go remarkably wrong rather quick in my experience. My favorite is when someone, somewhere in the dependency tree forgets to lock their version, which ends up blossoming into a ticking time bomb before it abruptly stops working.
Hopefully, your experiences have been far more pleasant than mine.