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        "author": "Idin",
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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# Abstract\nAbstract is a Python library for creating and drawing graphs \nand taking advantage of graph properties.\n\n## Installation\n\n```bash\npip install abstract\n```\nor\n```bash\npip install git+https://github.com/idin/abstract.git\n```\n\n\n## Graph\n\nIn computer science, a graph is an abstract data type that \nis meant to implement the undirected graph and directed graph \nconcepts from mathematics; specifically, the field of graph theory. \n[[1]](https://en.wikipedia.org/wiki/Graph_(abstract_data_type))\n\nA graph data structure consists of a finite (and possibly mutable) \nset of vertices or nodes or points, together with a set of \nunordered pairs of these vertices for an undirected graph or \na set of ordered pairs for a directed graph. These pairs are known \nas edges, arcs, or lines for an undirected graph and as arrows, \ndirected edges, directed arcs, or directed lines for a directed graph. \nThe vertices may be part of the graph structure, or may be external \nentities represented by integer indices or references. \n[[1]](https://en.wikipedia.org/wiki/Graph_(abstract_data_type))\n\n## Usage\n\nThe *Graph* class allows you to create nodes and edges and \nvisualize the resulting graph. Edges can have direction which\nindicates parent-child relationship.\n\n### *Graph*: Constructing a New Graph\n```python\nfrom abstract import Graph\n\ngraph = Graph()\n```\n\n### *add_node*: Adding a New Node\nThe *add_node* method returns a *GraphNode* object. \n\n```python\nnode_order = [\n    'scissors', 'paper', 'rock', 'lizard', 'Spock', 'scissors',\n    'lizard', 'paper', 'Spock', 'rock', 'scissors'\n]\n\n# add nodes (avoid duplicates)\nfor node in set(node_order):\n    node = graph.add_node(name=node)\n```\n\n### *connect*: Adding Edges\nThe *connect* method creates an edge from a *start* node to an *end* node. \n\n```python\nfor index in range(len(node_order)-1):\n    edge = graph.connect(start=node_order[index], end=node_order[index+1])\n```\n\n### *get_node*\nTo retrieve a node from the graph you can use the *get_node* method.\n```python\nrock = graph.get_node('rock')\n```\n\n### *draw* (*render*)\nThe *render* method visualizes the graph and if a *path* is provided it saves it\nto an image file that can be a *pdf* or *png*. The file format is infered from \nthe *path* argument. The *draw* method is just an alias for *render*.\n\n```python\n# just visualize the graph\ngraph.draw()\n```\n![image of the graph](https://raw.githubusercontent.com/idin/abstract/master/pictures/rock_paper.png)\n\n\n```python\n# save as a png file and view the file\ngraph.draw(path='my_graph.png', view=True)\n\n```\n\n## Future Features\n\n* Create a graph from:\n  * list of dictionaries\n  * dataframe\n* Create a new graph by filtering a graph\n\n\n",
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