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        "author": "Kuan Butts",
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        "description": "=============\npeartree \ud83c\udf50\ud83c\udf33\n=============\n\n.. image:: https://img.shields.io/gitter/room/nwjs/nw.js.svg\n        :target: https://gitter.im/peartree_transit\n\n.. image:: https://img.shields.io/pypi/v/peartree.svg\n        :target: https://pypi.python.org/pypi/peartree\n\n.. image:: https://img.shields.io/travis/kuanb/peartree.svg?branch=master\n        :target: https://travis-ci.org/kuanb/peartree\n\n.. image:: https://codecov.io/gh/kuanb/peartree/branch/master/graph/badge.svg\n  :target: https://codecov.io/gh/kuanb/peartree\n\npeartree is a library for converting `GTFS <https://developers.google.com/transit/gtfs/>`_ feed schedules into a representative directed network graph. The tool uses `Partridge <https://github.com/remix/partridge>`__ to convert the target operator schedule data into `Pandas <https://github.com/pandas-dev/pandas>`__ dataframes and then `NetworkX <https://networkx.github.io/>`_ to hold the manipulated schedule data as a directed multigraph.\n\n.. image:: https://raw.githubusercontent.com/kuanb/peartree/master/examples/example.gif\n\nAbove, an example of multiple Bay Area transit operators being incrementally loaded into peartree.\n\nInstallation\n------------\n\n.. code:: console\n\n    pip install peartree\n\nUsage\n-----\n\nSee a full notebook at `this gist <https://gist.github.com/kuanb/c54d0ae7ee353cac3d56371d3491cf56>`_ to see a simple, step-by-step iPython Notebook pulling in an AC Transit GTFS feed and converting it to a NetworkX graph.\n\n.. code:: python\n\n    import peartree as pt\n\n    path = 'path/to/actransit_gtfs.zip'\n\n    # Automatically identify the busiest day and\n    # read that in as a Partidge feed\n    feed = pt.get_representative_feed(path)\n\n    # Set a target time period to\n    # use to summarize impedance\n    start = 7*60*60  # 7:00 AM\n    end = 10*60*60  # 10:00 AM\n\n    # Converts feed subset into a directed\n    # network multigraph\n    G = pt.load_feed_as_graph(feed, start, end)\n\nExamples\n--------\n\nI've yet to produce a full how-to guide for this library, but will begin to populate this section with any blog posts or notebooks that I or others produce, that include workflows using peartree.\n\n`Calculating betweeness centrality with Brooklyn bus network <http://kuanbutts.com/2017/12/13/betweenness-centrality-peartree/>`_\n\n`Combining a peartree transit network and an OpenStreetMap walk network <http://kuanbutts.com/2018/12/24/peartree-with-walk-network/>`_\n\n`Generating comparative acyclic route graphs <http://kuanbutts.com/2018/03/15/comparative-routes-mpl/>`_\n\n`Coalescing transit network graphs and spectral clustering methods <http://kuanbutts.com/2018/04/01/spectral-cluster-transit/>`_\n\n`Exploratory graph analysis with betweenness and load centrality <http://simplistic.me/playing-with-gtfs-iii-geo-graphs.html>`_\n\n\n",
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