How to add conda environment to jupyter lab

Assuming your conda-env is named cenv, it is as simple as :

$ conda activate cenv           # . ./cenv/bin/activate in case of virtualenv(cenv)$ conda install ipykernel(cenv)$ ipython kernel install --user --name=<any_name_for_kernel>(cenv)$ conda deactivate

If you restart your jupyter notebook/lab you will be able to see the new kernel available. For newer versions of jupyter kernel will appear without restarting the instance. Just refresh by pressing F5.

PS: If you are using virtualenv etc. the above steps hold good.

A solution using nb_conda_kernels. First, install it in your base environment :

(base)$ conda install -c conda-forge nb_conda_kernels

Then in order to get a kernel for the conda_env cenv :

$ conda activate cenv(cenv)$ conda install ipykernel(cenv)$ conda deactivate

You will get a new kernel named Python [conda env:cenv] in your next run of jupyter lab / jupyter notebook

Note :If you have installed nb_conda_kernels, and want to create a new conda environment and have it accessible right away then

conda create -n new_env_name ipykernel

will do the job.

I tried both of the above solutions and they didn't quite work for me. Then I encountered this medium article which solved it: https://medium.com/@jeremy.from.earth/multiple-python-kernels-for-jupyter-lab-with-conda-c67e50de3aa3

Essentially, after running conda install ipykernel inside of your cenv environment, it is also good to run python -m ipykernel install --user --name cenv within the cenv environment - that way, we make sure that the version of python that is used within the jupyter environment is the one in cenv. Cheers!