{ "info": { "author": "Jeremy Lain\u00e9", "author_email": "jeremy@getwemap.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: ISC License (ISCL)", "Programming Language :: C++", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering :: GIS" ], "description": "pysupercluster\n==============\n\n|travis|\n\n.. |travis| image:: https://img.shields.io/travis/wemap/pysupercluster.svg\n :target: https://travis-ci.org/wemap/pysupercluster\n\nA fast Python 3 module for geospatial point clustering.\n\nThis is a port of https://github.com/mapbox/supercluster to C++, conveniently\nwrapped in a Python module. Initial benchmarks show it to be an order of\nmagnitude (10x) faster than the original JavaScript implementation.\n\nInstalling pysupercluster\n-------------------------\n\nThe easiest way to install pysupercluster is to use pip:\n\n pip install pysupercluster\n\nUsing pysupercluster\n--------------------\n\n.. code-block:: pycon\n\n >>> import numpy\n >>> import pysupercluster\n >>> points = numpy.array([\n ... (2.3522, 48.8566), # paris\n ... (-0.1278, 51.5074), # london\n ... 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