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A flexible, customizable, Streamlit component for interactive graph visualization using Cytoscape.js

Project description

streamlit-cytoscape

A flexible, customizable Streamlit component for interactive graph visualization using Cytoscape.js. This project is a fork of st-link-analysis by @AlrasheedA, who developed the bulk of the original component. This fork extends the original with additional customization options and bug fixes.

Overview

This project provides a Streamlit custom component for visualizing and interacting with graph data using Cytoscape.js. It supports customizable edge and node styles, labels, colors, captions, and icons.

Features

  • Customizable Node and Edge Styles: Easily define the appearance of nodes and edges using a variety of style options.
  • Custom Styles Pass-through: Use the custom_styles parameter on NodeStyle and EdgeStyle to pass any valid Cytoscape.js style property directly, enabling fine-grained control over shapes, borders, opacity, fonts, and more.
  • Material Icons Support: Supports a subset of Material icons for styling nodes which can be passed by name (e.g., icon='person'). Custom icons can still be used by passing a URL (e.g., icon='url(...)').
  • Customizable Layouts: Choose from different layout algorithms to arrange the graph elements.
  • Interactive Features:
    • Toolbar with fullscreen, JSON export, and layout refresh buttons.
    • View control bar for zooming, fitting, and centering the view.
    • View all properties of the selected elements in a side panel.
    • Highlights neighboring nodes or edges when an element is selected.
  • Node Actions (Expand / Remove): Enable node removal and expansion using the node_actions parameter. Removal can be triggered by a delete keydown or a remove button click, while expansion occurs on a double-click or expand button click.

Installation

pip install streamlit-cytoscape

Usage

import streamlit as st
from streamlit_cytoscape import streamlit_cytoscape, NodeStyle, EdgeStyle

st.set_page_config(layout="wide")

# Sample Data
elements = {
    "nodes": [
        {"data": {"id": 1, "label": "PERSON", "name": "Streamlit"}},
        {"data": {"id": 2, "label": "PERSON", "name": "Hello"}},
        {"data": {"id": 3, "label": "PERSON", "name": "World"}},
        {"data": {"id": 4, "label": "POST", "content": "x"}},
        {"data": {"id": 5, "label": "POST", "content": "y"}},
    ],
    "edges": [
        {"data": {"id": 6, "label": "FOLLOWS", "source": 1, "target": 2}},
        {"data": {"id": 7, "label": "FOLLOWS", "source": 2, "target": 3}},
        {"data": {"id": 8, "label": "POSTED", "source": 3, "target": 4}},
        {"data": {"id": 9, "label": "POSTED", "source": 1, "target": 5}},
        {"data": {"id": 10, "label": "QUOTES", "source": 5, "target": 4}},
    ],
}

# Style node & edge groups
node_styles = [
    NodeStyle("PERSON", "#FF7F3E", "name", "person"),
    NodeStyle("POST", "#2A629A", "content", "description"),
]

edge_styles = [
    EdgeStyle("FOLLOWS", caption='label', directed=True),
    EdgeStyle("POSTED", caption='label', directed=True),
    EdgeStyle("QUOTES", caption='label', directed=True),
]

# Render the component
st.markdown("### streamlit-cytoscape: Example")
streamlit_cytoscape(elements, "cose", node_styles, edge_styles)

Custom Styles

Use the custom_styles parameter to apply any valid Cytoscape.js style property:

from streamlit_cytoscape import NodeStyle, EdgeStyle

# Custom node styling with borders, shapes, and fonts
node_styles = [
    NodeStyle(
        label="PERSON",
        color="#FF7F3E",
        caption="name",
        icon="person",
        custom_styles={
            "shape": "diamond",
            "width": 60,
            "height": 60,
            "border-width": 3,
            "border-color": "#000000",
            "border-style": "dashed",
            "opacity": 0.9,
            "font-size": 14,
            "color": "#FFFFFF",
        },
    ),
]

# Custom edge styling with line styles and arrows
edge_styles = [
    EdgeStyle(
        label="FOLLOWS",
        caption="label",
        directed=True,
        custom_styles={
            "width": 3,
            "line-style": "dashed",
            "opacity": 0.8,
            "target-arrow-shape": "vee",
            "arrow-scale": 1.5,
            "font-size": 10,
        },
    ),
]

See the Cytoscape.js style documentation for all available properties.

API Reference

Element Description
streamlit_cytoscape Main component for creating and displaying the graph, including layout and height settings.
NodeStyle Defines styles for nodes, including labels, colors, captions, icons, and custom_styles for Cytoscape.js pass-through.
EdgeStyle Defines styles for edges, including curve styles, labels, colors, directionality, and custom_styles for Cytoscape.js pass-through.
Event Define an event to pass to component function and listen to.

Development

Ensure you have Python 3.10+, Node.js, and npm installed.

Setup

# Create conda environment
conda create -n streamlit_cytoscape python=3.10
conda activate streamlit_cytoscape

# Install Python package
poetry install

# Install frontend dependencies
cd src/streamlit_cytoscape/frontend
npm install

Running the App

Change _RELEASE flag in src/streamlit_cytoscape/component.py to False.

In one terminal start the frontend dev server:

cd src/streamlit_cytoscape/frontend
npm run start

In another terminal run the streamlit server:

cd examples
poetry run streamlit run app.py

Testing

poetry run black .
poetry run flake8 src/streamlit_cytoscape tests examples
poetry run mypy src/streamlit_cytoscape
poetry run pytest

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

streamlit_cytoscape was created by Natalie Gill. It is licensed under the terms of the MIT license.

AI Disclosure Statement

Generative AI tools (Claude Code, Anthropic) were used as coding assistants during the development of this project. The authors maintain full responsibility for the accuracy of all code. AI-assisted outputs were reviewed and validated against expected behavior before integration.

Acknowledgments

This project is a fork of st-link-analysis by @AlrasheedA, who developed the bulk of the original component. This fork extends the original with additional customization options.

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