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-0.9.0.tar.gz (3.1 MB view details)

Uploaded Source

Built Distribution

vegafusion_jupyter-0.9.0-py3-none-any.whl (6.2 MB view details)

Uploaded Python 3

File details

Details for the file vegafusion-jupyter-0.9.0.tar.gz.

File metadata

  • Download URL: vegafusion-jupyter-0.9.0.tar.gz
  • Upload date:
  • Size: 3.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.2

File hashes

Hashes for vegafusion-jupyter-0.9.0.tar.gz
Algorithm Hash digest
SHA256 59ecca50635b85c2985e4fbd34971be2031c19a62bec8fd6fc922bc8956ead55
MD5 abfd91cdd9a9c1a72b6a4ef797370b94
BLAKE2b-256 501cedfcc9462e422341175c7bc91b29b7eae27d90c2f2078469f4a85e89d80e

See more details on using hashes here.

File details

Details for the file vegafusion_jupyter-0.9.0-py3-none-any.whl.

File metadata

  • Download URL: vegafusion_jupyter-0.9.0-py3-none-any.whl
  • Upload date:
  • Size: 6.2 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.2

File hashes

Hashes for vegafusion_jupyter-0.9.0-py3-none-any.whl
Algorithm Hash digest
SHA256 65e8270dd8bfed18a899c86b07c09ba58bfe45af86bfb893692b4c8ec3c08484
MD5 192c6151ddac203a487ff52add9f5c74
BLAKE2b-256 948227a5a06cad372658308ec7b055ab9a1e0cc19b865455a0606f0aafe9124d

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