Python API and Jupyter widget facilitating interactive visualization of spatial single-cell data with Vitessce.
To install with pip:
$ pip install vitessce[all]
Explore our example notebooks. These contain demos of different use cases and integrations with single-cell data analysis packages.
For a development installation (requires NodeJS and NPM),
$ git clone https://github.com/vitessce/vitessce-python.git
$ cd vitessce-python
$ uv sync --extra dev --extra docs --extra all
uv run flake8
uv run pytest
One file:
uv run autopep8 --in-place --aggressive ./path/to/file.py
All .py
files:
find . -name '*.py' -exec uv run autopep8 --in-place --aggressive '{}' \;
uv run make html
To deploy a new version, increment the version of the Python package in pyproject.toml
.
Then, when you push or merge the code with the incremented versions to main
, the GitHub Action deploy.yml
workflow will build and push the package to PyPI.
Check the JavaScript console in the web browser for error messages. To do so, shift+right click in Jupyter, then click Inspect element. You may need to enable your browser's develop mode in its preferences for this option to appear when you right-click.
Check that you have activated the correct conda or other virtual environment as you expect.
When sharing errors, it can be helpful to share the current versions of packages in the environment, e.g., by conda list
or pip list
.
To ensure that older widget JavaScript output is not causing conflicts with newer JavaScript output (which may persist via notebook outputs even without running notebook cells), clear old outputs by Kernel -> Restart Kernel and Clear All Outputs. Then refresh the browser tab (containing Jupyter) to ensure all JavaScript outputs are fresh.
This is also typically required when running !pip install vitessce[all]
from within a Jupyter notebook cell in the same session as running vc.widget()
for the first time.
The Kernel restart/Output clearing is required when a new Jupyter widget is installed in the environment, otherwise Jupyter will not yet recognize the newly-installed widget (as the notebook was opened with a different set of Jupyter widgets installed, and widget discovery is performed only at certain stages in the notebook lifecycle).
If the widget renders successfully, you can get its current configuration by
vw = vc.widget()
vw
vw.config
If Jupyter is running on a remote machine, then use proxy=True
. You may need to specify host_name
as well (widget
should be able to detect this but the plain display
cannot).
vw = vc.widget(proxy=True)
vw
or
vc.display(proxy=True, host_name="http://localhost:8888")
With the environment activated, run pip list
on the command line:
Package Version
----------------------------- -----------
...
jupyterlab 3.x.x
...
vitessce 3.x.x
- ipywidget docs: Building a Custom Widget
- ipywidget docs: Low Level Widget Tutorial
- ipywidget example: ipyleaflet
- ipywidget example (with React): ipymaterialui
- ipywidget example (with React): higlass-python
- ipywidget cookiecutter
- Sphinx: Getting Started
- Read the Docs Sphinx Theme
- jupyter server proxy
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.