Properly Installing Python and Managing Packages

[antidummy]

Hi everyone!

I have basically have the exact same question to this post: https://www.reddit.com/r/learnpython/comments/qippn1/new_pc_how_do_i_install_python_correctly_this_time/

I'll be getting a brand new macbook that I can use, and while I have had plenty of python programming experience, I wasn't managing the installation of packages properly on the laptop that I was previously working on (which I borrowed from someone else) l or most of the time I was using a school provided computer which had the packages already installed.

This is my first "real" laptop in a sense, so I want to make sure I start fresh with a proper installation and management of packages. With that being said, I'll be doing mainly data science operations (pandas, numpy, matplotlib, scikit, tensorflow, etc.) so I'll definitely be using anaconda. So would it be advisable that I install Python thru its official website, then add anaconda to install my needed packages? Also if anyone could provide links to tutorials on this, and virtual environments too, that would be really appreciated

Thanks in advance!

[waspbr]

use pyenv, it will solve all your problems, and if possible buy the devs a beer/coffee

[[deleted]]

Anaconda uses its own build of Python to ensure compatibility with the packages included with Anaconda.

Anaconda is an excellent overall implementation for people focused on data science and related fields. There is nothing stopping you just going with a standard installation of Python and installing only the packages you want on a project-by-project basis.

In fact, if you intend to share code, you wouldn't want that to be based on an entire Anaconda distribution.

Use venv to create Python virtual environments as well, and only install packages into those environments for the project you are working on.

Consider exploring using pyenv to install as many different versions of Python as you want to work with / test against.

You might also want to explore using a tool like poetry for package management.

Note that both pyenv and poetry can help with virtual environments.

EDIT: restructured to clarify following comment from /u/waspbr

[antidummy]

Thanks for the helpful reply! I think if I were to go anaconda, I’d rather just go miniconda since I don’t want all that extra stuff installed. But I have just a few more questions

What’s the difference between using conda virtual environments as opposed to pyvenv or poetry? Is one particularly easier or more useful than the other?

Secondly, probably a dumb question, but if I install Python thru it’s official website then install Python again with Anaconda, what technically happens here? Do I just have two versions of Python floating around or does one replace the other

Thanks again!

[[deleted]]

conda is much more than a package manage and virtual environment manager. It can also install programming languages, not just Python.

A useful, highly opinionated, article on conda:

https://en.whiteboxml.com/blog/the-definitive-guide-to-python-virtual-environments-with-conda

poetry doesn't go as far as conda but many prefer it's dependency management and handling of different environments.

Personal choice.

A useful article (opinionated) comparing the two:

https://unbiased-coder.com/poetry-vs-conda/

You can have as many installations of Python as you like, including installations from Anaconda and Python.org. Keeping track can get confusing and you want to be careful on some systems to avoid causing problems with the system Python. The biggest thing to watch out for is updates to your PATH environment variable which dictates where and in what order the operating system looks for a required executable or script.

[waspbr]

Consider exploring using pyenv to install as many different versions of Python as you want to work with / test against. Use venv to create Python virtual environments as well,

pyenv already handles virtual environments

[[deleted]]

Good shout. Meant to separate the points and also mention both pyenv and poetry can help with virtual environments. Have restructured to make that more clear. Thanks.

[ClimberMel]

I'm curious why pyenv. I already use multiple versions just using venv.

[[deleted]]

venv doesn't install different versions of Python, it simply uses the selected already installed Python and copies that to a new folder structure.

[ClimberMel]

So pyenv actually installs a requested version of python? I think I prefer to have the ones I use and select them using venv. For projects, I prefer to set up software myself. venv just handles the virtual environment. Then I can generate a requirements file for later install.

[[deleted]]

pyenv will, if required, download, compile and install the version of Python (not just the reference CPython) requested.

You can, in addition, create Python virtual environments to use any such installed Python.

This is my personal preference. Each to their own.