Skip to main content

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

Project description

vitessce-python

PyPI docs

Binder Open In Colab

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

Installation

To install with pip:

$ pip install 'vitessce[all]'

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
$ uv sync --extra dev --extra docs --extra all

Alternatively, use conda:

$ conda create -n vitessce-dev python=3.12
$ conda activate vitessce-dev
$ pip install -e ".[dev,docs,all]"

Troubleshooting SpatialQuery installation on macOS:

$ # Use the macOS clang instead of from homebrew.
$ CC=/usr/bin/clang CXX=/usr/bin/clang++ pip install -e ".[dev,docs,all,sq]"

Linting and testing

uv run flake8
uv run pytest

Formatting

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 '{}' \;

Documentation

uv run make html

Deployment

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.

Troubleshooting

Check JavaScript console

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 your Python environment

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.

Restart Kernel and Clear All Outputs, then refresh the browser tab

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).

Check the widget configuration

If the widget renders successfully, you can get its current configuration by

vw = vc.widget()
vw
vw.config

Usage when Jupyter is running on a remote machine

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")

For more information see the data location options documentation.

Ensure that Vitessce and Jupyter are installed in the same environment

With the environment activated, run pip list on the command line:

Package                       Version
----------------------------- -----------
...
jupyterlab                    3.x.x
...
vitessce                      3.x.x

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.

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

vitessce-3.8.3.tar.gz (337.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

vitessce-3.8.3-py3-none-any.whl (82.8 kB view details)

Uploaded Python 3

File details

Details for the file vitessce-3.8.3.tar.gz.

File metadata

  • Download URL: vitessce-3.8.3.tar.gz
  • Upload date:
  • Size: 337.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for vitessce-3.8.3.tar.gz
Algorithm Hash digest
SHA256 1f492ecc277644d8ae600f99889de2f62ffc42ee2fc9a6f4bef0ddf24aa15dc2
MD5 7e9260624addb706b10d6d1c069482b5
BLAKE2b-256 5d483acb5ec639b5df5d8007e4ee16ffc4e135a621b9b2c6d730cfa67658566b

See more details on using hashes here.

File details

Details for the file vitessce-3.8.3-py3-none-any.whl.

File metadata

  • Download URL: vitessce-3.8.3-py3-none-any.whl
  • Upload date:
  • Size: 82.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for vitessce-3.8.3-py3-none-any.whl
Algorithm Hash digest
SHA256 d37abcfb372c0d5b229170d6b94652ab4859201b94a0f7d5ee45673bf729b3b1
MD5 9d6083317cc53a5571aa954745edb61b
BLAKE2b-256 dcfc1a32c023a37c1330b33793fcc6b56eab008b9fcb8bf63ebc00af0df3f4ff

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page