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        "author": "Eric V. Smith",
        "author_email": "eric@trueblade.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "========\ntoposort\n========\n\nOverview\n========\n\nImplements a topological sort algorithm.\n\n>From `Wikipedia <http://en.wikipedia.org/wiki/Topological_sorting>`_:\nIn computer science, a topological sort (sometimes abbreviated topsort\nor toposort) or topological ordering of a directed graph is a linear\nordering of its vertices such that for every directed edge uv from\nvertex u to vertex v, u comes before v in the ordering.\n\nInput data description\n======================\n\nThe input to the toposort function is a dict describing the\ndependencies among the input nodes. Each key is a dependent node, the\ncorresponding value is a set containing the dependent nodes.\n\nNote that toposort does not care what the input node values mean: it\njust compares them for equality. The examples here usually use\nintegers, but they could be any hashable type.\n\nTypical usage\n=============\n\nThe interpretation of the input data here is: If 2 depends on 11; 9\ndepends on 11, 8 and 10; 10 depends on 11 and 3 (and so on), then in what\norder should we process the items such that all nodes are processed\nbefore any of their dependencies?::\n\n    >>> from toposort import toposort, toposort_flatten\n    >>> list(toposort({2: {11},\n    ...                9: {11, 8, 10},\n    ...                10: {11, 3},\n    ...                11: {7, 5},\n    ...                8: {7, 3},\n    ...               }))\n    [{3, 5, 7}, {8, 11}, {2, 10}, {9}]\n\nAnd the answer is: process 3, 5, and 7 (in any order); then process 8\nand 11; then process 2 and 10; then process 9. Note that 3, 5, and 7\nare returned first because they do not depend on anything. They are\nthen removed from consideration, and then 8 and 11 don't depend on\nanything remaining. This process continues until all nodes are\nreturned, or a circular dependency is detected.\n\nCircular dependencies\n=====================\n\nA circular dependency will raise a CyclicDependencyError, which is\nderived from ValueError.  Here 1 depends on 2, and 2 depends on 1::\n\n    >>> list(toposort({1: {2},\n    ...                2: {1},\n    ...               }))\n    Traceback (most recent call last):\n        ...\n    toposort.CircularDependencyError: Circular dependencies exist among these items: {1:{2}, 2:{1}}\n\nIn addition, the 'data' attribute of the raised CyclicDependencyError\nwill contain a dict containing the subset of the input data involved\nin the circular dependency.\n\n\nModule contents\n===============\n\n``toposort(data)``\n\nReturns an iterator describing the dependencies among nodes in the\ninput data. Each returned item will be a set. Each member of this set\nhas no dependencies in this set, or in any set previously returned.\n\n``toposort_flatten(data, sort=True)``\n\nLike toposort(data), except that it returns a list of all of the\ndepend values, in order. If sort is true, the returned nodes are sorted within\neach group before they are appended to the result::\n\n    >>> toposort_flatten({2: {11},\n    ...                   9: {11, 8, 10},\n    ...                   10: {11, 3},\n    ...                   11: {7, 5},\n    ...                   8: {7, 3},\n    ...                  })\n    [3, 5, 7, 8, 11, 2, 10, 9]\n\nNote that this result is the same as the first example: ``[{3, 5, 7}, {8, 11}, {2, 10}, {9}]``,\nexcept that the result is flattened, and within each set the nodes\nare sorted.\n\n\nTesting\n=======\n\nTo test, run 'python setup.py test'. On python >= 3.0, this also runs the doctests.\n\nChange log\n==========\n\n1.5 2016-10-24 Eric V. Smith\n----------------------------\n\n* When a circular dependency error is detected, raise a specific\n  exception, CircularDependencyError, which is a subclass of\n  ValueError.  The 'data' attribute of the exception will contain the\n  data involved in the circular dependency (issue #2).  Thanks\n  lilydjwg for the initial patch.\n\n* To make building wheels easier, always require setuptools in\n  setup.py (issue #5).\n\n* Mark wheel as being universal, that is, supporting both Python 2.7\n  and 3.x (issue #7).\n\n1.4 2015-05-16 Eric V. Smith\n----------------------------\n\n* Removed 'test' package, so it won't get installed by bdist_*. It's still\n  included in sdists.\n\n* No code changes.\n\n1.3 2015-05-15 Eric V. Smith\n----------------------------\n\n* Fixed change log date.\n\n* No code changes.\n\n1.2 2015-05-15 Eric V. Smith\n----------------------------\n\n* Changed RPM name to python3-toposort if running with python 3.\n\n* No code changes.\n\n1.1 2014-07-24 Eric V. Smith\n----------------------------\n\n* Release version 1.1. No code changes.\n\n* Add a README.txt entry on running the test suite.\n\n* Fix missing test/__init__.py in the sdist.\n\n1.0 2014-03-14 Eric V. Smith\n----------------------------\n\n* Release version 1.0. The API is stable.\n\n* Add MANIFEST.in to MANIFEST.in, so that it is created in the sdist\n  (issue #1).\n\n0.2 2014-02-11 Eric V. Smith\n----------------------------\n\n* Modify setup.py to produce a RPM name of python-toposort for bdist_rpm.\n\n0.1 2014-02-10 Eric V. Smith\n----------------------------\n\n* Initial release.\n\n\n",
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