Setting up Jupyter notebook kernels for multiple CUDA versions.

gistfile1.txt

You can also set the variables in your kernel.json file:
My solution is useful if you need the same environment variables every time you start a jupyter kernel, especially if you have multiple sets of environment variables for different tasks.

To create a new ipython kernel with your environment variables, do the following:

Read the documentation at https://jupyter-client.readthedocs.io/en/stable/kernels.html#kernel-specs
Run jupyter kernelspec list to see a list with installed kernels and where the files are stored.
Copy the directory that contains the kernel.json (e.g. named python2) to a new directory (e.g. python2_myENV).
Change the display_name in the new kernel.json file.
Add a env dictionary defining the environment variables.
Your kernel json could look like this (I did not modify anything from the installed kernel.json except display_name and env):

{
 "display_name": "Python 2 with environment",
 "language": "python",
 "argv": [
  "/usr/bin/python2",
  "-m",
  "ipykernel_launcher",
  "-f",
  "{connection_file}"
 ],
 "env": {"LD_LIBRARY_PATH":""}
}
Use cases and advantages of this approach
In my use-case, I wanted to set the variable LD_LIBRARY_PATH which effects how compiled modules (e.g. written in C) are loaded. Setting this variable using %set_env did not work.
I can have multiple python kernels with different environments.
To change the environment, I only have to switch/ restart the kernel, but I do not have to restart the jupyter instance (useful, if I do not want to loose the variables in another notebook). See -however - https://github.com/jupyter/notebook/issues/2647

Short version

jupyter kernelspec list

Available kernels:
  python2    /home/duane/PycharmProjects/.venv/imm/share/jupyter/kernels/python2

cd /home/duane/PycharmProjects/.venv/imm/share/jupyter/kernels/python2

vi kernel.json

{
 "display_name": "Python 2", 
 "language": "python", 
 "argv": [
  "python", 
  "-m", 
  "ipykernel_launcher", 
  "-f", 
  "{connection_file}"
 ],
 "env": {"LD_LIBRARY_PATH":"/usr/local/cuda-9.0/lib64"}
}