vert 1.0.1
Universal Graph Interface for Python
License: MIT
Keywords: graph vertex edge node link network semantic database

Vert
====

*Universal Graph Interface for Python*

About
-----

Vert is a Python package which attempts to provide a standardized
interface for graphs. It does so by separating the graph into two
separate layers of abstraction:

-  The graph store: This is where the graph is actually stored and
   represented. It may be a graph database, another graph library's data
   structure, or one of vert's built-in graph store objects.
-  The graph interface: This is where you, the programmer, can access
   the graph via an intuitive object-oriented interface using familiar
   data types such as Graph, Vertex, and Edge.

Because vert is structured along these distinct layers of abstraction,
it is possible to write code that utilizes and operates on a graph
without regard for the underlying storage mechanisms. Storage mechanisms
can be freely swapped out for each other at the point where the graph
object is initialized, and, aside from differences in performance and
persistence, the rest of your code will never know the difference.
Support for new graph storage mechanisms can be added simply by creating
a class that supports the GraphStore interface. This means you never
have to worry about vendor lock-in, and updating your code to use the
latest technology is as simple as a one-line change.

Copyright/License
-----------------

All content copyright 2017 Aaron M. Hosford. Use of this software is
governed by the MIT license. See LICENSE.txt for the full license
agreement.

Package Structure
-----------------

-  **test\_vert**: Unit tests for vert

   -  **test\_stores**: Unit tests for vert.stores

      -  **\_\_init\_\_.py**: Empty placeholder.
      -  **\_base.py**: Contains base class for vert.stores test cases.
      -  **test\_dbm.py**: Unit tests for vert.stores.dbm.
      -  **test\_memory.py**: Unit tests for vert.stores.memory.

   -  **\_\_init\_\_.py**: Empty placeholder.

-  **vert**: The package root

   -  **stores**: Subpackage containing implementations of various graph
      stores that the vert package supports out of the box.

      -  **\_\_init\_\_.py**: Empty placeholder.
      -  **base.py**: Defines the GraphStore interface that all graph
         stores have to implement. The GraphStore interface hides the
         implementation details for each graph store, providing a
         consistent, albeit clunky, means of accessing and modifying the
         contents of a graph.
      -  **dbm.py**: Defines DBMGraphStore, a DBM-backed persistent
         graph store.
      -  **memory.py**: Defines the MemoryGraphStore, a non-persistent,
         memory-only graph store.

   -  **\_\_init\_\_.py**: Exports the publicly visible symbols for the
      vert package. Nothing is actually defined in this module.
   -  **graphs.py**: Defines the Graph, Vertex, and Edge, classes, along
      with other supporting infrastructure. This module's classes
      transform the clunky interface provided by GraphStore into a
      convenient and versatile object-oriented interface designed to
      make it easy to work with graphs in a consistent manner regardless
      of how the underlying storage mechanisms work.

Examples
--------

Non-Persistent
^^^^^^^^^^^^^^

::

    from vert import Graph

    with Graph() as g:
        dog = g.vertices['dog'].add()
        cat = g.vertices['cat'].add()
        edge = g.edges['dog', 'cat']
        print(edge.exists)  # False
        edge.add()
        print(edge.exists)  # True
        edge.labels.add('chases')
        print('chases' in edge.labels)  # True

    with Graph() as g:
        edge = g.edges['dog', 'cat']
        print(edge.exists)  # False

DBM-Backed Persistence
^^^^^^^^^^^^^^^^^^^^^^

::

    from vert import Graph

    with Graph('test.db') as g:
        dog = g.vertices['dog'].add()
        cat = g.vertices['cat'].add()
        edge = g.edges['dog', 'cat']
        print(edge.exists)  # False
        edge.add()
        print(edge.exists)  # True
        edge.labels.add('chases')
        print('chases' in edge.labels)  # True

    with Graph('test.db') as g:
        edge = g.edges['dog', 'cat']
        print(edge.exists)  # Still true
        print('chases' in edge.labels)  # Still true

Defining Your Own Storage Mechanism
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

::

    from vert import Graph, GraphStore

    class MyGraphStore(GraphStore):
        # Implement each of GraphStore's abstract methods here
        ...

    with Graph(MyGraphStore(...)) as g:
        # Now the graph consults your back end for storage and retrieval
        ...

TODO:
-----

-  Test cases for undirected edges.
-  Add separately installable graph stores for neo4j, tinkerpop,
   networkx, sqlite, and other back ends.
-  Add an example for creating a third-party module to provide support
   for new kinds of graph stores.
-  Add algorithms such as path finding and pattern matching. Whenever
   possible, these should be implemented by the graph store, rather than
   at the interface level. By having the interface classes inspect the
   graph store for the method before calling it, it should be possible
   to fall back on a slower default client-side implementation when the
   store does not provide one. An alternate approach would be to add the
   methods to the GraphStore class but have them raise a special
   sentinel exception if the particular implementation doesn't provide
   the algorithm.
-  Add support for transactions and make the code thread-safe.
-  Add support for reading & writing common graph file formats.
-  Add support for transferring from one graph store to another.
-  100% code coverage for unit testing.
-  Continuous integration for unit testing.
-  Prettify the string representations for Edges and Vertices.
-  Make the DBM graph store more efficient.
-  Support older versions of Python.
-  Consider adding flags to ``GraphStore.iter_edges()`` for independent
   inclusion/exclusion of directed & undirected edges.
-  Add a ``rebuild()`` method to ``DBMGraphStore`` which ensures the
   stored graph is in a consistent state through minimum modifications,
   allowing recovery from disk or power failure.