This release is a pre-release and may not be stable for production use.
JupyterLab GPU Dashboards
A JupyterLab extension for displaying dashboards of GPU usage.
Built with JupyterLab and Bokeh Server
What's here
This repository contains two sets of code:
- Python code defining a Bokeh Server application that generates the dashboards
in the
jupyterlab_nvdashboard/directory - TypeScript code integrating these dashboards into JupyterLab in the
src/directory
You should be able to modify only the Python code to edit the dashboards without modifying the TypeScript code.
Prerequisites
- JupyterLab 1.0
- bokeh
- pynvml
Installation
This extension has a server-side (Python) and a client-side (Typescript) component, and we must install both in order for it to work.
Note: Currently nvdashboard does not support Windows
To install the server-side component, run the following in your terminal
pip install jupyterlab-nvdashboard
To install the client-side component, run
jupyter labextension install jupyterlab-nvdashboard
Development
To install the server-side part, run the following in your terminal from the repository directory:
pip install -e .
In order to install the client-side component (requires node version 8 or later), run the following in the repository directory:
jlpm install
jlpm run build
jupyter labextension install .
To rebuild the package and the JupyterLab app:
jlpm run build
jupyter lab build
Publishing
This application is distributed as two subpackages.
The JupyterLab frontend part is published to npm, and the server-side part to both PyPI and Anaconda (nightlies).
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.
1 maintainer
Release files for jupyterlab-nvdashboard 0.6.0a210501
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| jupyterlab-nvdashboard-0.6.0a210501.tar.gz | 9.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| jupyterlab_nvdashboard-0.6.0a210501-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.7 kB
Release files / jupyterlab-nvdashboard-0.6.0a210501.tar.gz
| Download URL | jupyterlab-nvdashboard-0.6.0a210501.tar.gz |
|---|---|
| Size | 9.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.10
|
Release files / jupyterlab_nvdashboard-0.6.0a210501-py3-none-any.whl
| Download URL | jupyterlab_nvdashboard-0.6.0a210501-py3-none-any.whl |
|---|---|
| Size | 10.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
9b269ff4fe5775efd039d03ba6295c6bf54f40268c681575bf0e63b13a9ea86f
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.10
|
