Metadata-Version: 2.1
Name: scinet-JoshGoA
Version: 0.3.1
Summary: Network science abstract data types
Home-page: https://github.com/JoshGoA/scinet.git
Author: JoshGoA
License: UNKNOWN
Description: # SCINET
        
        ![Build](https://img.shields.io/badge/build-passing-blue) ![Author](https://img.shields.io/badge/author-JoshGoA-green) ![License](https://img.shields.io/badge/license-MIT-red) ![PyPi](https://img.shields.io/badge/pypi-v0.3.1-yellow) ![Python](https://img.shields.io/badge/python->=3.8-orange)
        
        Graph theory abstract data type.
        
        **scinet.Graph** is designed upon the [graph (abstract data type)](https://en.wikipedia.org/wiki/Graph_(abstract_data_type)) definition and functions as a bare bones skeletal graph data mapping, containing abstract vertices and edges.
        
        ## Installation
        
        1. Install [Python >= 3.8](https://www.python.org/downloads/)
        2. Install [scinet]()
        ```sh
        $ pip install scinet
        ```
        
        ## Usage
        
        Import **scinet**
        ```py
        import scinet as sn
        ```
        
        Create graph
        ```py
        G = sn.Graph()
        ```
        
        Manipulate data
        
        * add_vertex
        ```py
        G.add_vertex(vertex := "foo")
        ```
        
        * remove_vertex
        ```py
        G.remove_vertex(vertex := "foo")
        ```
        
        * add_edge
        ```py
        G.add_edge(edge := "foobar", source_vertex="foo", target_vertex="bar")
        ```
        
        * remove_edge
        ```py
        G.remove_edge(edge := "foobar", source_vertex="foo", target_vertex="bar")
        ```
        
        * adjacent
        ```py
        (target_vertex := "bar") in G[(source_vertex := "foo")]
        ```
        
        * neighbors
        ```py
        G[(vertex := "foo")].keys()
        ```
        
        See [docs](docs/scinet.html) for further details.
        
        ## Contributors
        
        * **JoshGoA** - *Main contributor* - [GitHub](https://github.com/JoshGoA)
        
        ### TODO
        
        1. Undirected graph
        > Add "directed" mappable property to edge data
        2. Network visualization
        > Create "matplotlib.pyplot" supported API
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
