Skip to content

Latest commit

 

History

History
167 lines (133 loc) · 6.57 KB

README.md

File metadata and controls

167 lines (133 loc) · 6.57 KB

ViP-IPykernel

Lifecycle GitHub Release Date Release PyPI

GitHub Workflow Status (main) Codecov

DEV Medium

Venv in Parent IPykernel - an IPython kernel for Jupyter that runs out the closest venv

Overview

Check the medium or dev.to articles to read more about the background behind this project.

Do you use venv's for all of your environments? Do you run Jupyter out of a system/user installed location or via JupyterHub? Are you bored of making a kernel for every single venv? Then this is the package for you!

vip-ipykernel overwrites the default python3 kernel and replaces it with one which will traverse directories upwards until it finds a .venv directory, if it finds one then it will start the kernel with python out of that directory, if it does not find a venv then it will carry on with the default python3.

NOTE: Your venv must have ipykernel installed in it, as this 'kernel' just searches for and launches ipykernel out of the local venv. If ipykernel is not available inside the venv then it will fail to start.

This only needs to be installed once, you can do this with pip install vip-ipykernel --user to install it into your local user environment.

Once the package is installed, run python3 -m vip_ipykernel.kernelspec --user to install the kernel, now when you run a notebook with the default python3 kernel it will instead use the venv in a parent directory.

If you want to revert the changes, run python3 -m ipykernel install --user, this will re-install the default python3 kernel.

Alternatively, if you don't want to overwrite the default kernel, then you can pass a name (python3 -m vip_ipykernel.kernelspec --user --name venv-kernel) to so that the kernel appears separately in the list of kernels and the default behaviour is not modified.

How it Works

The standard python3 kernel is:

{
 "argv": [
  "/usr/bin/python3",
  "-m",
  "ipykernel_launcher",
  "-f",
  "{connection_file}"
 ],
 "display_name": "Python 3",
 "language": "python"
}

This just says "Run using python3 to run ipykernel_launcher with an argument -f {connection_file}". When you install the vip ipykernel this is replace by:

{
 "argv": [
  "/usr/bin/python3",
  "-m",
  "vip_ipykernel_launcher",
  "-m",
  "ipykernel_launcher",
  "-f",
  "{connection_file}"
 ],
 "display_name": "Python 3",
 "language": "python"
}

Which will instead run the vip_ipykernel.vip_ipykernel_launcher module, passing it the arguments -m ipykernel_launcher -f {connection_file}. The module runs a function venv_search which looks in the current directory, and upwards to any parent directories, until it finds a .venv or venv directory containing bin/python3.

If it finds a venv with python3 in it, it passes the arguments -m ipykernel_launcher -f {connection_file} to that python executable, which starts and connects the kernel from that venv to your current session, in the same way that a kernel installed for that specific venv would.

If it does not find a venv, then it will default to the system python executable and behave like the standard python3 kernel.

Caveats and Gotchas

VSCode Jupyter Notebook Integration

VSCode manages kernels for its notebooks with its own system, so it will not use the vip-ipykernel.

Venv Names

Currently only venv's named .venv or venv are searched for, if your venv has a different name it won't be found, and if you have multiple venv's available then the first one (sorted alphanumerically, so .venv takes priority over venv) will be used.

Acknowledgements

The kernel implementation and tests are largely copy-and-paste'd directly from the ipykernel project with some minor modifications made to search for a venv and launch python out of it if possible.

Thank you to Thomas Kluyver (@takluyver) for the review of the initial code in the first PR: #1

Todo

  • Expand tests to different versions of ipykernel/jupyter_core
  • Look at ways to show kernel errors
  • Support for other environments:
    • Poetry-created venvs (poetry env info --path)
    • Pipenv-created venvs
    • Pyenv-created venvs
    • Conda-created environments
    • User-configured venvs
    • Reading from vscode configuration?
    • etc...