For the notebook search engine I’ve been tinkering with, I want to be able to index notebooks rooted on the same directory path as a notebook server the search engine can be added to as a Jupyter server proxy extension. There doesn’t seem to be a reliably set or accessible environment variable containing this path, so how can we create one?
Here’s a recipe that I think may help: it uses the nbclient
package to run a minimal notebook that just executes a simple, single %pwd
command against the available Jupyter server.
import nbformat from nbclient import NotebookClient _nb = '''{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%pwd" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }''' nb = nbformat.reads(_nb, as_version=nbformat.NO_CONVERT) client = NotebookClient(nb, timeout=600) # Available parameters include: # kernel_name='python3' # resources={'metadata': {'path': 'notebooks/'}}) client.execute() path = nb['cells'][0]['outputs'][0]['data']['text/plain'].strip("'").strip('"')
Or maybe it doesn’t? Maybe it actually just runs in the directory you run the script from, in which case it’s just a labyrinthine pwd
… Hmmm…