@alexkyllo I'm on Mac (Apple Silicon) after switching from Windows. I used conda on PC and have used conda on Mac.
What got me was when JupyterLab Desktop came out. Simplified my life massively.
If I need something that doesn't work on M1 I have Docker Desktop or Deepnote.
@alexkyllo @ede they are definitely overkill. Would be nice to get full M1 support for most libraries. Alas the issue isnโt Python but the many underlying C++ libraries popular Python libraries are built on.
Takes time and it will work. I would love to never use containers.
@alexkyllo @benlindsay @brianokken @ede Virtual environment are most definitely **not** motivated by macOS specifically. You've just been lucky that it hasn't bit you yet (speaking as someone who has been coding in Python before environments existed).
And I'm not touching the education angle on this one as there are arguments on both sides. Either you want to keep it simple and assume they are going to break their install anyway, or you want to start with best practices.
@alexkyllo @benlindsay @brianokken @ede If you would like your environments centralized there are various tools to support that workflow.
And I hear there's an editor that will simply remember the environment you select so it's a one-time cost (if not zero-cost if you keep the environment in your workspace) ๐
But I get it, environments are an extra step. Totally fine that it works for you, I just don't want to promote not using environments as a general solution for everyone.
This PEP outlines the behavior of Python scripts when the python command is invoked. Depending on a distribution or system configuration, python may or may not be installed. If python is installed its target interpreter may refer to python2 or python3. ...