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Jupyter widget facilitating interactive visualization of spatial single-cell data with Vitessce

Project description

vitessce-python

PyPI Vitessce JS dependency version docs

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Python API and Jupyter widget facilitating interactive visualization of spatial single-cell data with Vitessce.

Installation

To install with pip:

$ pip install vitessce

Getting started

Explore our example notebooks. These contain demos of different use cases and integrations with single-cell data analysis packages.

Development

For a development installation (requires NodeJS and NPM),

$ git clone https://github.com/vitessce/vitessce-python.git
$ cd vitessce-python
$ conda env create -f environment.yml
$ conda activate vitessce-python-dev
$ pip install -e ".[dev]"
$ jupyter nbextension install --py --symlink --overwrite --sys-prefix vitessce
$ jupyter nbextension enable --py --sys-prefix vitessce

When actively developing your extension for JupyterLab, run the command:

$ jupyter labextension develop --overwrite vitessce

Then you need to rebuild the JS when you make a code change:

$ cd js
$ npm run build

You then need to refresh the JupyterLab page when your javascript changes.

Conda environments

In this repository, there are multiple conda environments for different purposes:

Linting and testing

flake8
pytest

Documentation

make html

Deployment

To deploy a new version, increment the version of the Python package in vitessce/_version.py and the JS package in js/package.json:

cd js
npm version patch

Then, when you push or merge the code with the incremented versions to master, the GitHub Action deploy.yml workflow will build and push the packages to PyPI and NPM.

Resources

Getting/Offering Help

If you have a specific bug or feature request, please feel free to open an issue. Otherwise our discussions section is a great place to get help or offer it. If you aren't sure if something is a bug or not, don't have all the reproduction steps, or just have a general question, feel free to open a discussion post.

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