Re:Python 3.11
by lacker on Tuesday October 05, 2021 @04:02PM
(#28764842)
Here's an example, let's say you're developing GPU code that needs to work with different CUDA versions on different machines. Look at the `cupy` install instructions for example:
With conda this installation tends to just work, conda will also install the non-python cudatoolkit for you. With pip you have to either make all your python developers set up their c++ environment the same way as well, to install from source, or set a fixed cuda version that all users have to be on.
Now `cupy` is just one python library that has non-python dependencies. If your project has several dependencies like this, where conda is a one line install and pip means you have to mess around with your c++ environment, conda is probably the right choice for you.
All of the pain you mention with conda is totally correct, though, it's just a question of which sort of pain happens to be worse for the packages you are going to use.
https://docs.cupy.dev/en/stable/install.html
With conda this installation tends to just work, conda will also install the non-python cudatoolkit for you. With pip you have to either make all your python developers set up their c++ environment the same way as well, to install from source, or set a fixed cuda version that all users have to be on.
Now `cupy` is just one python library that has non-python dependencies. If your project has several dependencies like this, where conda is a one line install and pip means you have to mess around with your c++ environment, conda is probably the right choice for you.
All of the pain you mention with conda is totally correct, though, it's just a question of which sort of pain happens to be worse for the packages you are going to use.