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An interactive 3D visualization tool for Python dependencies, illustrating relationships, structural communities, and package metrics using a knowledge graph approach

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gssakash/python_library_graph

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python-library-graph: 3D Dependency Visualizer

Visualize your Python project's dependencies and analyze their structure with interactive 3D graphs powered by Plotly.

python-library-graph is a command-line tool that transforms complex Python dependency networks into intuitive, interactive 3D visualizations. It automatically detects related dependency communities, highlights project relationships, and helps you understand coupling across your environment.


Features

  • Interactive 3D Visualization
    Explore dependency networks using a browser-based interactive Plotly chart.

  • Community Detection
    Automatically group related dependencies using the Louvain algorithm for structural insights.

  • Root Highlighting
    Clearly mark your project’s root and visually differentiate direct and transitive dependencies.

  • Simple CLI
    Generate complete dependency graphs with a single command.


Installation

You can install python-library-graph directly from PyPI (once published - TBD):


Usage

Navigate to the root directory of your Python project (the one containing your requirements.txt or where dependencies are installed), then run:


Command Options

Option Description Default
--output-html <dependency_graph.html> Output the graph as an interactive HTML file. N/A
--output-image <dependency_graph.png> Export the graph as a static image (requires kaleido). N/A
--no-community Disable community detection and use depth-based coloring (Direct/Transitive). Enabled
--version Show the version number and exit. N/A

📊 Example Visualization

Dependency Graph


License

This project is licensed under the MIT License.
See the LICENSE file for details.


Contributing

Contributions are welcome!
Please open an issue or submit a pull request on the GitHub repository.

Developed by: Akash GSS

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An interactive 3D visualization tool for Python dependencies, illustrating relationships, structural communities, and package metrics using a knowledge graph approach

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