Flask-Neo4jDriver

Flask-Neo4jDriver is a flask extension that provides integration with the official neo4j python drivers.

Flask-Neo4jDriver > 0.2.0 requires python 3_. Experimental graph mapping models are introduced in version 0.2.0.

.. _python 3: https://docs.python.org/3/

Introduction

This extension provides basic integration with the official python driver_.

Flask-Neo4jDriver is designed to provide an interface to the Neo4j_ graph database. This extension exposes the neo4j.v1.GraphDatabase.Driver object for direct manipulation.

Additionally, this extension provides a handful of helper utility methods including the following:

• session. Return a GraphDatabase.Session
• query(). Run a cypher query within a session() context.

.. _python driver: https://github.com/neo4j/neo4j-python-driverk .. _Neo4j: https://neo4j.com

Installation

Flask-Neo4jDriver can be installed from PyPI.

.. code:: bash

pip install Flask-Neo4jDriver

To install the latest development version, use:

.. code:: bash

pip install git+https://github.com/scbunn/flask-neo4jdriver.git@develop

Usage

In order to use this extension you need to initialize it with the flask application. This can be done directly or via an application factory. Once the extension has been initialized it is available through the db object.

Configuration

Flask-Neo4jDriver supports the following configuration options.

+-------------------+-------------------------------------+-----------------------+
| Configuration Key | Description                         | Default               |
+===================+=====================================+=======================+
| GRAPHDB_URI       | URI of the Neo4j Database           | bolt://localhost:7687 |
+-------------------+-------------------------------------+-----------------------+
| GRAPHDB_USER      | Username to connect to the database | neo4j                 |
+-------------------+-------------------------------------+-----------------------+
| GRAPHDB_PASS      | Password for the user               | neo4j                 |
+-------------------+-------------------------------------+-----------------------+

Example:

.. code-block:: python

   import os
   from flask import Flask
   from flask.ext.neo4jdriver import Neo4jDriver

   app = Flask(__name__)
   app.config['GRAPHDB_URI'] = 'bolt://neo4j.host:7687'
   app.config['GRAPHDB_USER'] = 'appuser'
   app.config['GRAPHDB_PASS'] = os.getenv('GRAPHDB_PASS', '')

   db = Neo4jDriver(app)

Direct Initialization

If you are not using an application factory, then you can initialize this extension directly.

.. code-block:: python

from flask import Flask from flask.ext.neo4jdriver import Neo4jDriver

app = Flask(name) db = Neo4jDriver(app)

Application Factories

If you are using an application factory, then you can initialize this 
extension within your `create_app()` method.

in models.py

.. code-block:: python

   from flask.ext.neo4jdriver import Neo4jDriver

   db = Neo4jDriver()

At your application factory

.. code-block:: python

   from flask import Flask

   def create_app(config_filename):
       app = Flask(__name__)
       app.config.from_pyfile(config_filename)

       from yourapplication.models import db
       db.init_app(app)

Testing
-------

You can execute the test suite using setup.py

.. code:: bash

   python setup.py test

Contributing
------------

Have features you want to add? Fork this repository and send me a pull 
request.  Please make sure you include test cases for any additional features.

Looking for something to do? Here is of open TODO items.

- Move Validators to Properties
- implement equality for Nodes (i.e. Node1 == Node2)
- implement hash for Node
- Fully implement logger
- Implement the Relationship model.
  - should be simple: r = Relationship(node1, 'LINKED', node2)
  - r.save()
- Implement Query
  - First model is simple. Just an execute() method that supports pagination.
  - implement other useful methods...

I'm currently not trying to implement a fully OGM type of setup with the model
system.  I expect the application to still have to execute raw cypher for
most queries.  The model system is intended to help, primarily, with the 
lifecycle of Nodes.