Issue: I am having issues with the environment and version of Python not matching the settings in VSCode, and causing issues with the packages I am trying to use in Jupyter notebooks. I am using a Windows 10 machine with Python 3.9.1 installed (including older versions), with Visual Studio Code 1.52.1 . Short summary - I install a package using pip. My guess is that it associates with the latest version of Python. I set up an interpreter in VS Code for that version of python, and try to import the package. The package is not found. If I call sys.version from the Jupyter notebook, I see that a default version of Python is running (3.8.5). The simple notebook throws an error because it cannot find that package that I installed with pip.
Screenshot that shows the associations:
This error is reproducible with only the
import pygmt
command in the notebook, i.e. it does not depend on the other packages imported.
Question: How can I control the version that Jupyter notebooks will run in VSCode if changing the interpreter doesn't work? Every other issue like this that I have found was due to not choosing the correct interpreter. In this case, I have. Why is it not running that version of the interpreter?
Thank you.
Edit This edit is in response to @Jill Cheng's answer (see my comment below for tl;dr). I can change the interpreter (lower left corner of VSCode) to match the default that VSCode wants to run. No problem. But there still are problems.
- I cannot install pygmt, the targeted package, into this version of Python (see the command in in the terminal).
- I cannot make VSCode operate in the opposite direction - i.e. I can never get it to run Python 3.9.1 even when that is the interpreter I chose.
I have reinstalled VSCode now several times, and Python 3.8.5 seems to always be the default. To me, the easiest solution seems to be changing the default Python version of VSCode - in fact, isn't that the point of selecting an interpreter? It is more nebulous to me why I cannot install pygmt into Python 3.8.5, and I don't know if it is beneficial to have multiple different versions of Python all with different packages (or is this just what Python users deal with daily?).