SCINET

Graph theory abstract data type.

scinet.Graph is designed upon the graph (abstract data type) definition and functions as a bare bones skeletal graph data mapping, containing abstract vertices and edges.

Includes DiGraph and MultiGraph support, with HyperGraph capabilities.

Installation

1. Install Python >= 3.8
2. Install scinet

$ pip install scinet

Usage

Import scinet

import scinet as sn

Create graph

G = sn.Graph()

Manipulate data

• add_vertex

G.add_vertex(vertex := "foo")

• add_edge

Edges must be assigned using hashable keys so that no name conflicts exist between source_vertex and target_vertex edges

key = G.add_edge(source_vertex := "foo", target_vertex := "bar"[, edge := "foobar"])

• remove_vertex

G.remove_vertex(vertex := "foo")

• remove_edge

G.remove_edge(source_vertex := "foo", target_vertex := "bar"[, edge := "foobar"])")

• adjacent

(target_vertex := "bar") in G[(source_vertex := "foo")]
>>> True

• neighbors

set(G[(vertex := "foo")])
>>> { "neighbor_1", "neighbor_2", ... }

See docs for further details.

Contributors

• JoshGoA - Main contributor - GitHub

TODO

1. Graph visualization

Create "matplotlib.pyplot" supported API