Jupyterlab templates from different types of contentsmanager
Project description
jupyterlab_multicontents_templates
Inspired by Jupyterlab-templates but added extra functions:
- Allow templates from any location, including S3, GCS, psql, etc., just installed the required jupyter contents manager.
- Preview notebook before import the template
- Directly publish notebook as templates into the selected folder with name
- Share Template URL and directly opened preview
This extension is composed of a Python package named jupyterlab_multicontents_templates
for the server extension and a NPM package named jupyterlab_multicontents_templates
for the frontend extension.
Screenshots
-
Use Template with preview
-
Publish notebook to Templates
-
Share Templates
Requirements
- JupyterLab >= 3.0
Install
pip install jupyterlab_multicontents_templates
Config
configure jupyter_notebook_config.py
with the following settings:
import os
from IPython.html.services.contents.filemanager import FileContentsManager
from s3contents import S3ContentsManager
c.JupyterLabMultiContentsTemplates.template_folders = {
"templates from Local File": {
"manager_class": FileContentsManager,
"kwargs": {
"root_dir": os.environ["HOME"]
},
},
"templates from S3 prefix1": {
"manager_class": S3ContentsManager,
"kwargs": {
"bucket": "example-bucket",
"prefix": "path/to/notebooks",
},
},
"templates from S3 prefix2": {
"manager_class": S3ContentsManager,
"kwargs": {
"bucket": "another-example-bucket",
"prefix": "path/to/notebooks",
},
},
}
# If you're using jupyterhub please set this value to True to enable sharing:
c.JupyterLabMultiContentsTemplates.append_hub_user_redirect = True
# Set this value to True if you want to sort template directory contents by name (ascending)
c.JupyterLabMultiContentsTemplates.sort_templates_by_name_asc = False
Troubleshoot
If you are seeing the frontend extension, but it is not working, check that the server extension is enabled:
jupyter server extension list
If the server extension is installed and enabled, but you are not seeing the frontend extension, check the frontend extension is installed:
jupyter labextension list
Contributing
Development install
Note: You will need NodeJS to build the extension package.
The jlpm
command is JupyterLab's pinned version of
yarn that is installed with JupyterLab. You may use
yarn
or npm
in lieu of jlpm
below.
# Clone the repo to your local environment
# Change directory to the jupyterlab_multicontents_templates directory
# Install package in development mode
pip install -e .
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm run build
You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.
# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm run watch
# Run JupyterLab in another terminal
jupyter lab
With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).
By default, the jlpm run build
command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:
jupyter lab build --minimize=False
Uninstall
pip uninstall jupyterlab_multicontents_templates
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