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    "info": {
        "author": "Claudia Lazara Poiet Sampedro, Igor Neves Faustino, Leticia Mazzo Portela",
        "author_email": "clp.sampedro@gmail.com, igornfaustino@gmail.com, leticiaportela@alunos.utfpr.edu.br",
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        "description": "# graphpy\n\nThis is a package for the manipulation of graphs\nmade for a class of graphs in the Brazilian university 'Universidade Tecnologica Federal do Paran\u00e1'\n\n## Installation\n\n```\npip install graphpython\n```\n\n## Complete Documentation\n\n### Graph\n\nto use this class, the main element is `Graph class`. With this class, you will be able to fill the graph with vertex and edges and do all the necessary operations\n\n- `Graph([directed])`: create a graph\n    - `directed`: Defaults to False.\n                tells if the graph is directed or not\n\n#### Code example\n\n``` python\n# Create a new graph\nfrom graphpy.graph import Graph\n\ngp = Graph()\n# add a new vertex\ngp.add_vertex('vertex1')\n\n# to get the create vertex, you can use the [] operator\nvertex1 = gp['vertex1']\n```\n\n### Vertex operations\n\nThe base of all graph is the vertex, to create a new vertex you got to use the follow functions\n\n- `gp.add_vertex(name, [value])`: create a new vertex and insert to the graph\n    - `name`: Unique identification to the vertex inside the graph\n    - `value`: optional value to the vertex\n\n- `gp.get_vertex(name)` or `gp[name]`: return the vertex from the graph\n    - `name`: Unique identification to the vertex inside the graph\n\n- `gp.get_all_vertex()`: get a list with all vertex from the graph\n\n- `gp.adjacents_vertex(vtx)`: get all adjacent vertex from one vertex\n    - `vtx`: vertex you want to know the adjacent\n\n- `gp.remove_vertex(vertex_to_remove)`: Remove a vertex and all the connections he have\n    - `vertex_to_remove`: vertex you want to remove\n\n#### Code example\n\n```python\nfrom graphpy.graph import Graph\n\ngp = Graph()\ngp.add_vertex('01')\ngp.remove_vertex(gp['01'])\n```\n\n## Search in the graph\n\nThe main class has a search method and to use, you need to pass a by params an strategy to make the search.\n\n#### Implement a new search strategy\n\nIn the class has two class strategies already implemented:\n\n- BFSstrategy\n- DFSstrategy\n\n```python\nfrom graphpy.graph import Graph\nfrom graphpy.BFSstrategy import BFSstrategy\n\ngraph = Graph()\ngraph.search(BFSstrategy(INITIAL_VERTEX))\n```\n\nTo extend all the search types you can create a new strategy extending the SearchStrategy class from search_strategy.\n\n```python\nfrom graphpy.search_strategy import SearchStrategy\n\n\nclass DFSstrategy(SearchStrategy):\n    def __init__(self):\n\n        self.__predecessors = {}\n        self.__firstSee = {}\n        self.__close = {}\n        self.__time = 0\n\n    def __dfs_visit(self, vertex):\n        self.__time = self.__time + 1\n        self.__firstSee[vertex] = self.__time\n        vertex.set_color(1)\n\n        for adjacent in self.get_adjacent_list()[vertex]:\n            if adjacent.get_color() == 0:\n                self.__predecessors[adjacent] = vertex\n                self.__dfs_visit(adjacent)\n        vertex.set_color(2)\n        self.__time += 1\n        self.__close[vertex] = self.__time\n\n    def search(self):\n        # colors:\n        #   white: not visited\n        #   grey: in the queue\n        #   black: nothing more to do\n        for key in self.get_adjacent_list():\n            # set color for all vertices to white\n            key.set_color(0)\n            self.__predecessors[key] = None\n        self.__time = 0\n        for key in self.get_adjacent_list():\n            if key.get_color() == 0:\n                self.__dfs_visit(key)\n\n        return self.__firstSee, self.__close, self.__predecessors\n```\n\n",
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