Skip to main content

Altair Jupyter Widget library that relies on VegaFusion for serverside calculations

Project description

VegaFusion Jupyter

This directory contains the vegafusion-jupyter package. For documentation on using this package to display Altair visualizations powered by VegaFusion in Jupyter contexts, see https://vegafusion.io.

The content below was autogenerated by Jupyter Widget cookiecutter

vegafusion-jupyter

Build Status codecov

Altair Jupyter Widget library that relies on VegaFusion for serverside calculations

Installation

You can install using pip:

pip install vegafusion_jupyter

If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable the nbextension:

jupyter nbextension enable --py [--sys-prefix|--user|--system] vegafusion_jupyter

Development Installation

Create a dev environment:

conda create -n vegafusion_jupyter-dev -c conda-forge nodejs yarn python jupyterlab
conda activate vegafusion_jupyter-dev

Install the python. This will also build the TS package.

pip install -e ".[test, examples]"

When developing your extensions, you need to manually enable your extensions with the notebook / lab frontend. For lab, this is done by the command:

jupyter labextension develop --overwrite .
yarn run build

For classic notebook, you need to run:

jupyter nbextension install --sys-prefix --symlink --overwrite --py vegafusion_jupyter
jupyter nbextension enable --sys-prefix --py vegafusion_jupyter

Note that the --symlink flag doesn't work on Windows, so you will here have to run the install command every time that you rebuild your extension. For certain installations you might also need another flag instead of --sys-prefix, but we won't cover the meaning of those flags here.

How to see your changes

Typescript:

If you use JupyterLab to develop then 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 widget.

# Watch the source directory in one terminal, automatically rebuilding when needed
yarn run watch
# Run JupyterLab in another terminal
jupyter lab

After a change wait for the build to finish and then refresh your browser and the changes should take effect.

Python:

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.

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

vegafusion-jupyter-0.1.0.tar.gz (2.9 MB view details)

Uploaded Source

Built Distribution

vegafusion_jupyter-0.1.0-py3-none-any.whl (5.9 MB view details)

Uploaded Python 3

File details

Details for the file vegafusion-jupyter-0.1.0.tar.gz.

File metadata

  • Download URL: vegafusion-jupyter-0.1.0.tar.gz
  • Upload date:
  • Size: 2.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.63.0 importlib-metadata/4.10.0 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.1

File hashes

Hashes for vegafusion-jupyter-0.1.0.tar.gz
Algorithm Hash digest
SHA256 c75279e517a5ba50b89700fc5524040d215c9759cbad9687dd5781bb9acdfef8
MD5 24a6eb96321e65b07d7096d8c35c97f7
BLAKE2b-256 00071c9e36e4cbac09f1b71b269fccc66588866c6aba507da7b816fea1284d4a

See more details on using hashes here.

File details

Details for the file vegafusion_jupyter-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: vegafusion_jupyter-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 5.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.63.0 importlib-metadata/4.10.0 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.1

File hashes

Hashes for vegafusion_jupyter-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e8165a9f8b5d0f7bfcd27baad43bcd049834060640aa22ca004ecfddf2d29bf9
MD5 963f4bffe47fa50fdd5e4bb854cf3549
BLAKE2b-256 38e51f42a4afc557ec73c44c25984dcd363056cf123e6486b0a80f0165cbc080

See more details on using hashes here.

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