Dash Cytoscape

A Component Library for Dash aimed at facilitating network visualization in Python, wrapped around Cytoscape.js.

Interacting with the stylesheet:

Interacting with the elements:

Getting Started

Prerequisites

Make sure that dash and its dependent libraries are correctly installed:

pip install dash dash-html-components

If you want to install the latest versions, check out the Dash docs on installation.

Usage

Install the library using pip:

pip install dash-cytoscape

Create the following example inside an app.py file:

import dash
import dash_cytoscape as cyto
import dash_html_components as html

app = dash.Dash(__name__)
app.layout = html.Div([
    cyto.Cytoscape(
        id='cytoscape',
        elements=[
            {'data': {'id': 'one', 'label': 'Node 1'}, 'position': {'x': 50, 'y': 50}},
            {'data': {'id': 'two', 'label': 'Node 2'}, 'position': {'x': 200, 'y': 200}},
            {'data': {'source': 'one', 'target': 'two','label': 'Node 1 to 2'}}
        ],
        layout={'name': 'preset'}
    )
])

if __name__ == '__main__':
    app.run_server(debug=True)

Documentation

View the Dash Cytoscape User Guide to get started now. You can also use the component reference to find how to use a certain feature.

To learn more about the core Dash components and how to use callbacks, view the Dash documentation.

For supplementary information about the underlying Javascript API, view the Cytoscape.js documentation.

Development and Contributions

Make sure that you have read and understood our code of conduct, then head over to CONTRIBUTING to get started.

License

Dash, Cytoscape.js and Dash Cytoscape are licensed under MIT. Please view LICENSE for more details.

Contact and Support

See https://plot.ly/dash/support for ways to get in touch.

Acknowledgments

Huge thanks to the Cytoscape Consortium and the Cytoscape.js team for their contribution in making such a complete API for creating interactive networks. This library would not have been possible without their massive work!

The Pull Request and Issue Templates were inspired from the scikit-learn project.