Skip to main content

A JupyterLab extension for displaying GPU usage dashboards

Project description

jupyterlab_nvdashboard

Github Actions Status

A JupyterLab extension for displaying GPU usage dashboards

This extension is composed of a Python package named jupyterlab_nvdashboard for the server extension and a NPM package named jupyterlab-nvdashboard for the frontend extension.

Requirements

  • JupyterLab >= 3.0

Install

pip install jupyterlab_nvdashboard

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_nvdashboard 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_nvdashboard

Releases for both packages are handled by gpuCI. Nightly builds are triggered when a push to a versioned branch occurs (i.e. branch-0.5). Stable builds are triggered when a push to the main branch occurs.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jupyterlab_nvdashboard-0.7.0a2107234.tar.gz (26.0 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file jupyterlab_nvdashboard-0.7.0a2107234.tar.gz.

File metadata

  • Download URL: jupyterlab_nvdashboard-0.7.0a2107234.tar.gz
  • Upload date:
  • Size: 26.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/0.0.0 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.7.10

File hashes

Hashes for jupyterlab_nvdashboard-0.7.0a2107234.tar.gz
Algorithm Hash digest
SHA256 c5b9c5f1de12623942c845a573b8a9eaeae5000a587946dbc63e1e3f10b19f0c
MD5 874895681c6c224bea70a86569d2712a
BLAKE2b-256 e64cf843b84ff1d207333ce1c58e7f59f1e76a68e4af61eb6d610d19266d1fd6

See more details on using hashes here.

Provenance

File details

Details for the file jupyterlab_nvdashboard-0.7.0a2107234-py3-none-any.whl.

File metadata

  • Download URL: jupyterlab_nvdashboard-0.7.0a2107234-py3-none-any.whl
  • Upload date:
  • Size: 35.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/0.0.0 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.7.10

File hashes

Hashes for jupyterlab_nvdashboard-0.7.0a2107234-py3-none-any.whl
Algorithm Hash digest
SHA256 f9020f17a253636588702f720b4cb990a9c4093268afa09c5bf8429b2ef8a3ff
MD5 2ddf3ac8fdfa685c90a48b494c6aef44
BLAKE2b-256 66b137575cb07bee60cf05a8c2c7397fdfac851dfa819eace1dfa36248e8292e

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page