Jupyter kernel for Lean

A kernel to use Lean from a Jupyter notebook.

It works by keeping internally a virtual file, formed by the contents of the evaluated cells, and passing it to the lean server.

Each time a cell is evaluated, the answer from the lean server is parsed. If there are no errors, the content is added to the virtual file.

Warning

This is in a proof of concept stage. Please test it, but beware that some bugs are expected to show.

Installation

First clone the git repo and pip install it from the corresponding directory:

git clone https://github.com/miguelmarco/leankernel.git
cd leankernel
pip install .

Then edit the lean/kernel.json file and adapt the environment variables to your lean installation:

• LEAN_MEMORY : the amount of RAM to be used by your lean process
• LEAN_TIME: the timeout for the lean server
• LEAN_BINARY : the lean executable
• LEAN_PATHFILES : the path to the directory you want to run lean from (in general, where you have created a leanproject).

Finally install the kernel by running

jupyter kernelspec install leankernel/lean --user

This will create a lean folder in your jupyter kernels directory (usually ~/.local/share/jupyter/kernels) and copy the kernel.json and logo file there.

Notes

• If your cell contains the words hint, suggest or library_search, it will be evaluated only as a temporary content, so you can see the output with the corresponding suggestions (you need to start importing the tactic module for those tactics to work).

• If your input is only a line with the content

-- save filename

the content of the virtual file will be saved to filename.

• If your input is only a line with the content

-- print

it will print the already defined objects and already proven theorems and lemmas