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Simple and flexible graph database analysis

Project description

Grandas

Grandas as a library that allows simplified, flexible analysis of the nodes and relationships stored in a graph database. It allows a user to search for and filter information and connections contained in a subgraph of a graph database.

Data Structures

Node

A Node object is the basic entity object and identifies any noun in your graph dataset.

Relationship

A Relationship stores the way that any two nodes in your dataset are related. Bi-directional relationships here are stored as two independent relationships.

NodeFrame

Nodeframes allow users to see the nodes in their graph databases, and further enable them to filter and resolve redundant nodes.

RelationshipFrame

The RelationshipFrame object stores a series of Relationship objects as a pandas DataFrame, using the hashed value of the full node to identify where the start and ending points for each relationship are.

GraphFrame

A GraphFrame is comprised of a NodeFrame (attribute: nodes) and a RelationshipFrame (attribute: rels).


Getting Started

To get started using grandas, you can install it using pip:

pip install grandas

From there, load in nodes and relationships to a GraphFrame object, similar to how you would use a pandas DataFrame.

import grandas as gd

nodes = [
  Node(label='PERSON',name='Alice',age='27'),
  Node(label='PERSON',name='Bob',age='24'),
  ]
alice, bob = nodes
rels = [
  Relationship(start=alice, end=bob, label='owes_money_to',amount=10)
]
gf = GraphFrame(nodes=nodes, relationships=rels)

node_frame = gf.nodes
relationship_frame =  gf.rels

Contributing

Contributions are more than welcome! Please just submit a pull request to the develop branch.

Project details


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grandas-0.0.1.tar.gz (4.3 kB view hashes)

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