Broken jupyter notebook kernel integration with conda environments

Greetings. I’m currently in a Jupyter kernel hell. I can’t figure how to fix it. And I’m not sure whether it’s a Jupyter or conda issue, so thanks for the patience!

Here’s my setup. I use conda to manage my python environments. I work on many different projects that use Jupyter notebooks, each project having its own environment (specified in environment.yml files).

I recently reinstalled conda to update my root environment to Python 3.6 and conda 4.3.13. As part of this reinstallation, I tried to remove files that I thought would get freshly regenerated including jupyter configuration files (IIRC).

This reinstallation of conda triggered the issue:

• when I run jupyter notebook with the conda environment activated, the specific conda environment is not available in the spawned notebook browser.
• If I run python -m ipykernel.kernelspec (I think) then I the activated conda environment becomes the default Python 3 kernel for all my notebook servers.
• Creating new conda environments with jupyter installed does not add them to the list of kernels in jupyter.

Before I reinstalled conda (and deleted jupyter config directories since I wanted to freshly reinstall everything related to python):

• if I launched a notebook from an activated conda environment, the default Python 3 kernel would correspond to that notebook
• if I created a new conda environment, the kernel would show up as a choice in all jupyter sessions regardless of which environment jupyter notebook was running from
• I never had to mess around with configuration files.

So I think I’ve broken something and I want the old (or any environment aware) behavior back. Tagging @minrk @jakevdp @kalefranz @asmeurer in case you or someone you mention can help. Will really appreciate any guidance!

[dhimmel]

conda install nb_conda_kernels failed with:

UnsatisfiableError: The following specifications were found to be in conflict:
  - nb_conda_kernels -> _nb_ext_conf -> nb_anacondacloud -> python 2.7* -> openssl 1.0.1*
  - python 3.6*

So I installed nb_conda_kernels from conda-forge using:

conda install --channel=conda-forge nb_conda_kernels

Now I can choose from my conda environments in the Jupyter kernel menu. Phew!

Note that the nb_conda_kernels README states:

To use a conda environment as a kernel, don’t forget to install ipykernel in this environment or it won’t show up in the kernel list.

[dhimmel]

I think Continuum stopped shipping their environments-as-kernels plugin by default - you can probably still install it

@takluyver, thanks for that info! It was enough for me to track down nb_conda_kernels (anaconda cloud, repo). Once I’m back at the affected machine, I’ll let you know if this fixes my issues.

nb_conda also looks interesting (allows you to manage conda environments in a Jupyter browser tab).

In worst case, I should be able to use the single kernel installation commands you link to:

source activate myenv
python -m ipykernel install --user --name myenv --display-name "Python (myenv)"
source activate other-env
python -m ipykernel install --user --name other-env --display-name "Python (other-env)"

But I’m not a huge fan of this solution as it’s a manual step. Furthermore, when we have several people collaborating on a repo, we want them to all have the same kernel names for conda environments.