A Python interface for the igraph library, enabling fast creation, manipulation, and analysis of large graphs and networks.
python-igraph is a Python interface for the igraph library, which is a powerful tool for creating, manipulating, and analyzing graphs and networks. It provides high-performance graph operations, making it ideal for handling large-scale network data in research and data science applications.
Data scientists, researchers, and developers working with graph and network analysis, especially those needing efficient tools for large-scale complex network research.
Developers choose python-igraph for its high performance, comprehensive graph operations, and cross-platform compatibility, offering a robust and efficient solution for graph analysis compared to other libraries.
Python interface for igraph
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Leverages an optimized C core for efficient handling of large-scale graphs, as highlighted in the philosophy and key features for complex network analysis.
Supports a wide range of functions from graph creation to advanced algorithms, detailed in the extensive documentation on Read the Docs.
Works on Linux, macOS, and Windows with PyPI wheels for most Python versions, ensuring broad accessibility as per installation instructions.
Includes a unit test suite with support for dependencies like NumPy and matplotlib, facilitating reliable development and integration.
Enabling features like GraphML on Windows requires additional steps with vcpkg and multiple environment variables, making installation cumbersome compared to other platforms.
The PyPy version is significantly slower, with tests taking ~15 seconds versus ~5 seconds on CPython, and has limitations like missing docstrings from C code.
Linking to an existing igraph C library can lead to stability issues with experimental functions, and the Python interface is only guaranteed with the vendored version, adding complexity.