Installing a ipykernel and running jupyter notebook inside a virtual env - not using conda

Question

I've hit a dead end trying to solve/debug this issue which doesn't seem like it should be that difficult.

I'm working in Pycharm IDE (not the professional) and I'm working inside a virtual environment let's call it pythonProject and I want to be able to run launch a jupyter notebook in this environment so that it can pick up all the python packages i've installed and configured for this environment.

As I understand it from the documentation, these are the steps I need to take.

My terminal prompt statement:

(pythonProject) oliver@oliver-u20:~/pythonProject$

commands:

python3 -m pip install ipykernel
python3 -m pip install notebook
python3 -m ipykernel install --user --name pythonProject --display-name "Python (pythonProject)"
jupyter notebook

But when I load jupyter notebook, it only shows python3 under kernels.

I tried outputting jupyter kernelspec list And get only the base kernel which suggests from this that it's not finding my kernelspec, but I can't seem to figure from the documentation what i'm supposed to do.

Am I missing something?

Answer 1

Ok so I've solved this.

I think there was an install issue with jupyter.

I tried reproducing this in a completely new project and venv and could get the kernel showing.

In the project and venv where I still couldn't, I noticed a discrepancy in the output of my jupyter --paths

In the working venv I could see under data /home/oliver/.local/share/jupyter Which is where the kernels I installed are located.

However in the project that wasn't working there was instead: /home/oliver/snap/jupyter/6/.local/share/jupyter

I'm guessing this snap path is from how I originally installed jupyter on my Ubuntu via the app store - seemed sensible at the time.

So I uninstalled jupyter, restarted my venv and the jupyter --paths has magically changed so that /home/oliver/.local/share/jupyter is present and when I start a jupyter notebook at the command line with jupyter notebook I can see all my kernels showing!

I found this quite difficult to debug with the documentation and command help outputs so hope someone else finds this useful.