jupyter notebook running kernel in different env

@tschundler’s solution works perfectly if your environment has already been created.

If you want to change the default kernel at the creation of your virtual environment and avoid any manual configuration, you just need to add jupyter at the end of the conda command:

conda create --name ENVNAME python=PYTHONVERSION jupyter

The correct kernel will then be used when you use ipython or jupyter notebook.

In my case somehow jupyter wasn’t able to ‘pick’ the virtual environment’s python. So I had to edit ~/.local/share/jupyter/kernels/{my_env_name}/kernel.json
and add path to the interpreter

in the argv key.

There is also an easy way here

workon my-virtualenv-name  # activate your virtualenv, if you haven't already
pip install tornado==4.5.3
pip install ipykernel==4.8.2

You should now be able to see your kernel in the IPython notebook menu: Kernel -> Change kernel and be able to switch to it (you may need to refresh the page before it appears in the list). IPython will remember which kernel to use for that notebook from then on.

This worked for me. source

pip install --user ipykernel
python -m ipykernel install --user --name=myenv

Output
Installed kernelspec myenv in /home/user/.local/share/jupyter/kernels/myenv

and go to above directory
open kernel.json

{
 "argv": [
  "/home/user/anaconda3/envs/myenv/bin/python", # path to your virtual environment python
  "-m",
  "ipykernel_launcher",
  "-f",
  "{connection_file}"
 ],
 "display_name": "myenv",
 "language": "python"
}

I know this is an old question, but nobody has mentioned nb_conda_kernels, which was made to solve this problem. You must have it installed in the environment from which you launched the running notebook, and any other environment which has kernel/s installed (ipykernel, r-irkernel, etc ) will be available as an option (Start Preferred Kernel):

Sharing my experience here, in case someone made the same mistake:

TL;DR

In VSCode I created the virtual environment from an Ubuntu terminal but forgot to activate the WSL extension too. Once I activated the WSL extension, I was able to change the Jupyterkernel to my virtual environment.

Full explanation

Using VSCode I work with the WSL extension (see here). I created my virtual environment from an Ubuntu terminal [Created a new terminal and selected ‘Ubuntu (WSL)’] and then went to my Jupyter notebook to change my kernel, but it did not appear in the list.

I tried the solution proposed above of adding the path to kernel.json in my virtual environment, adapting to my case (I don’t use conda) but I was surprised to see that the folder bin in my environment did not have a file named python.

The solution was to activate the WSL extension: lower right corner > click on the arrows (Open a remote connection) > reopen folder in WSL.

After this, I could see in the explorer two new entries in the bin folder for Python and Python3 (the arrow on the right side seem to indicate it’s a symbolic link).
Virtual environment now shows the python symbolic links

Then I went to my Jupyter notebook and changed the kernel to my virtual environment.

In the end, I did not have to change the path in kernel.json.

P.S: The above is my understanding of my problem and the solution given my non-existing knowledge about Linux, so any comments to complement/improve this answer are very welcome!