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…
OUseful.Info, the blog... 