Metadata-Version: 2.1
Name: pydot
Version: 1.4.2
Summary: Python interface to Graphviz's Dot
Home-page: https://github.com/pydot/pydot
Author: Ero Carrera
Author-email: ero.carrera@gmail.com
Maintainer: Peter Nowee
Maintainer-email: peter@peternowee.com
License: MIT
Project-URL: Changelog, https://github.com/pydot/pydot/blob/master/ChangeLog
Project-URL: Bug Tracker, https://github.com/pydot/pydot/issues
Description: [![Build Status](https://www.travis-ci.com/pydot/pydot.svg?branch=master)](https://www.travis-ci.com/pydot/pydot)
        [![PyPI](https://img.shields.io/pypi/v/pydot.svg)](https://pypi.org/project/pydot/)
        
        
        About
        =====
        
        `pydot`:
        
          - is an interface to [Graphviz][1]
          - can parse and dump into the [DOT language][2] used by GraphViz,
          - is written in pure Python,
        
        and [`networkx`][3] can convert its graphs to `pydot`.
        
        Development occurs at [GitHub][11], where you can report issues and
        contribute code.
        
        
        Examples
        ========
        
        The examples here will show you the most common input, editing and
        output methods.
        
        Input
        -----
        
        No matter what you want to do with `pydot`, it will need some input to
        start with. Here are 3 common options:
        
        1. Import a graph from an existing DOT-file.
        
            Use this method if you already have a DOT-file describing a graph,
            for example as output of another program. Let's say you already
            have this `example.dot` (based on an [example from Wikipedia][12]):
        
            ```dot
            graph my_graph {
               bgcolor="yellow";
               a [label="Foo"];
               b [shape=circle];
               a -- b -- c [color=blue];
            }
            ```
        
            Just read the graph from the DOT-file:
        
            ```python
            import pydot
        
            graphs = pydot.graph_from_dot_file('example.dot')
            graph = graphs[0]
            ```
        
        2. or: Parse a graph from an existing DOT-string.
        
            Use this method if you already have a DOT-string describing a
            graph in a Python variable:
        
            ```python
            import pydot
        
            dot_string = """graph my_graph {
                bgcolor="yellow";
                a [label="Foo"];
                b [shape=circle];
                a -- b -- c [color=blue];
            }"""
        
            graphs = pydot.graph_from_dot_data(dot_string)
            graph = graphs[0]
            ```
        
        3. or: Create a graph from scratch using pydot objects.
        
            Now this is where the cool stuff starts. Use this method if you
            want to build new graphs from Python.
        
            ```python
            import pydot
        
            graph = pydot.Dot('my_graph', graph_type='graph', bgcolor='yellow')
        
            # Add nodes
            my_node = pydot.Node('a', label='Foo')
            graph.add_node(my_node)
            # Or, without using an intermediate variable:
            graph.add_node(pydot.Node('b', shape='circle'))
        
            # Add edges
            my_edge = pydot.Edge('a', 'b', color='blue')
            graph.add_edge(my_edge)
            # Or, without using an intermediate variable:
            graph.add_edge(pydot.Edge('b', 'c', color='blue'))
            ```
        
            Imagine using these basic building blocks from your Python program
            to dynamically generate a graph. For example, start out with a
            basic `pydot.Dot` graph object, then loop through your data while
            adding nodes and edges. Use values from your data as labels, to
            determine shapes, edges and so forth. This way, you can easily
            build visualizations of thousands of interconnected items.
        
        4. or: Convert a NetworkX graph to a pydot graph.
        
            NetworkX has conversion methods for pydot graphs:
        
            ```python
            import networkx
            import pydot
        
            # See NetworkX documentation on how to build a NetworkX graph.
        
            graph = networkx.drawing.nx_pydot.to_pydot(my_networkx_graph)
            ```
        
        Edit
        ----
        
        You can now further manipulate your graph using pydot methods:
        
        - Add further nodes and edges:
        
          ```python
          graph.add_edge(pydot.Edge('b', 'd', style='dotted'))
          ```
        
        - Edit attributes of graph, nodes and edges:
        
          ```python
          graph.set_bgcolor('lightyellow')
          graph.get_node('b')[0].set_shape('box')
          ```
        
        Output
        ------
        
        Here are 3 different output options:
        
        1. Generate an image.
        
            To generate an image of the graph, use one of the `create_*()` or
            `write_*()` methods.
        
            - If you need to further process the output in Python, the
              `create_*` methods will get you a Python bytes object:
        
              ```python
              output_graphviz_svg = graph.create_svg()
              ```
        
            - If instead you just want to save the image to a file, use one of
              the `write_*` methods:
        
              ```python
              graph.write_png('output.png')
              ```
        
        2. Retrieve the DOT string.
        
            There are two different DOT strings you can retrieve:
        
            - The "raw" pydot DOT: This is generated the fastest and will
              usually still look quite similar to the DOT you put in. It is
              generated by pydot itself, without calling Graphviz.
        
              ```python
              # As a string:
              output_raw_dot = graph.to_string()
              # Or, save it as a DOT-file:
              graph.write_raw('output_raw.dot')
              ```
        
            - The Graphviz DOT: You can use it to check how Graphviz lays out
              the graph before it produces an image. It is generated by
              Graphviz.
        
              ```python
              # As a bytes literal:
              output_graphviz_dot = graph.create_dot()
              # Or, save it as a DOT-file:
              graph.write_dot('output_graphviz.dot')
              ```
        
        3. Convert to a NetworkX graph.
        
            Here as well, NetworkX has a conversion method for pydot graphs:
        
            ```python
            my_networkx_graph = networkx.drawing.nx_pydot.from_pydot(graph)
            ```
        
        More help
        ---------
        
        For more help, see the docstrings of the various pydot objects and
        methods. For example, `help(pydot)`, `help(pydot.Graph)` and
        `help(pydot.Dot.write)`.
        
        More [documentation contributions welcome][13].
        
        
        Installation
        ============
        
        From [PyPI][4] using [`pip`][5]:
        
        `pip install pydot`
        
        From source:
        
        `python setup.py install`
        
        
        Dependencies
        ============
        
        - [`pyparsing`][6]: used only for *loading* DOT files,
          installed automatically during `pydot` installation.
        
        - GraphViz: used to render graphs as PDF, PNG, SVG, etc.
          Should be installed separately, using your system's
          [package manager][7], something similar (e.g., [MacPorts][8]),
          or from [its source][9].
        
        
        License
        =======
        
        Distributed under an [MIT license][10].
        
        
        Contacts
        ========
        
        Maintainers:
        - Sebastian Kalinowski <sebastian@kalinowski.eu> (GitHub: @prmtl)
        - Peter Nowee <peter@peternowee.com> (GitHub: @peternowee)
        
        Original author: Ero Carrera <ero.carrera@gmail.com>
        
        
        [1]: https://www.graphviz.org
        [2]: https://en.wikipedia.org/wiki/DOT_%28graph_description_language%29
        [3]: https://github.com/networkx/networkx
        [4]: https://pypi.python.org/pypi
        [5]: https://github.com/pypa/pip
        [6]: https://github.com/pyparsing/pyparsing
        [7]: https://en.wikipedia.org/wiki/Package_manager
        [8]: https://www.macports.org
        [9]: https://gitlab.com/graphviz/graphviz
        [10]: https://github.com/pydot/pydot/blob/master/LICENSE
        [11]: https://github.com/pydot/pydot
        [12]: https://en.wikipedia.org/w/index.php?title=DOT_(graph_description_language)&oldid=1003001464#Attributes
        [13]: https://github.com/pydot/pydot/issues/130
        
Keywords: graphviz dot graphs visualization
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
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Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*
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