For what it's worth, I am experiencing the similar issues. I am on Windows 10, and I completely removed Anaconda using the recommended steps (anaconda-clean, then uninstall from add/remove programs). I installed the Python 3.6 version of Anaconda, and now my Jupyter Notebook is completely borked. I can launch the server, but I can't access any of my conda environments (old or new). Only one kernel is listed: "Python 3." If I install Jupyter from within the environment and launch the notebook server while the environment is activated, sys.path still refers to the base installation path. Is something broken with respect to 3.6?

I think Continuum stopped shipping their environments-as-kernels plugin by default - you can probably still install it, or you can set up kernels for environments manually. We're thinking about better ways to expose environments to Jupyter.

Thanks for the quick reply, this restored my workflow entirely. I think you are right about Continuum. I guess it serves me right for relying on pre-built distros, heh.

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.

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.

@takluyver or other repo members: close this issue at will. I may still report some additional findings here...

Thanks

I had similar issue, this was really helpful. Thanks

Thank you. I had same problem.

Such a useful thread. IMO it is more than a little counterintuitive that notebooks do not use the active conda env by default, nor that they are even visible!

Thank you, this is very helpful for me. I am sucking in this problem about two day

I did the following:

python -m ipykernel install --user --name StoAU2 --display-name "Python (StoAU2)"
/home/user/anaconda3/envs/StoAU2/bin/python: No module named ipykernel
[Errno 13] Permission denied: '/usr/local/share/jupyter'`

So then I tried:

source deactivate
python -m ipykernel install --user --name StoAU2 --display-name "Python (StoAU2)"
Installed kernelspec StoAU2 in /home/user/.local/share/jupyter/kernels/stoau2
python -m ipykernel install --user --name StoAU --display-name "Python 3 (StoAU)"
Changed Kernel -> Python (StoAU2).

Then in a Jupyter notebook:

import sys
print(sys.executable)
from jupyter_core.paths import jupyter_data_dir
print(jupyter_data_dir())`

/home/user/anaconda3/bin/python
/home/user/.local/share/jupyter

Still not referring to the right kernel... This is quite an annoying change that terminal kernel and Notebook terminal are not the same.

This is what I tried (based on: https://github.com/Anaconda-Platform/nb_conda_kernels/blob/fe861722902df9c97f47bbf6e16c8c634d17144f/README.md):

conda install -c conda-forge nb_conda_kernels
conda create -n test
package plan Proceed ([y]/n)? y
conda install -n nb_conda_kernels --file requirements.txt -c r

But I got an error that I don't have the requirement.txt (sorry lost actual error). So I reinstalled everything and did the following (which finally worked):

conda create --name StoAU
source activate StoAU
conda install ipykernel
python -m ipykernel install --user --name StoAU --display-name "Python 3 (StoAU)"

I might be a beginner, but I don't understand what the purpose is of creating an environment and installing all packages there, if in the end the notebook doesn't use this kernel with what you've just installed.