I\'m trying to set a good environnement for doing some scientific stuff with python. To do so, I installed Jupyter & miniconda.
Then I want to be able to have di
Assuming your conda-env is named cenv
, it is as simple as :
$ conda activate cenv
(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.
PS: If you are using virtualenv etc. the above steps hold good.
For Anaconda I suggest you a much easier and proper solution; just give a look at the nb_conda_kernels package.
It allows you to "manage your conda environment-based kernels inside the Jupyter Notebook".
Is should be included since Anaconda version 4.1.0, otherwise simply use
conda install nb_conda
Now you should be able to manage all direcly from the Notebook interface.
I found the solution. The setup for the kernels where located here ~/Library/Jupyter/kernels/
.
Then I modified the kernel.json
file and set the right path to python.
Now it's working.
Not sure what else did help, but for me crucial was to install nb_conda_kernels
in root conda environment. Attempting to install it in specific conda environment did not end up in having Jupyter Notebook be able to use other conda environment other than default one.
conda install -n root nb_conda_kernels
jupyter notebook
This worked for me:
source activate {environment_name}
python -m ipykernel install --user --name={environment_name};
Incase ipykernel is not installed, use this command:
conda install -c anaconda ipykernel