python-graphviz-plus 0.1.1

Graph and network visualization utilities extending graphviz and networkx

python-graphviz-plus

A set of graph and network visualization utilities that extend graphviz, networkx, and pandas. Highly optimized for generating clean, elegant, and styled graphs in both Jupyter Notebooks and standard Python scripts.

Github

https://github.com/Santt997/python-graphviz-plus

Key Features

• AdjacencyList: Parse edge lists (traditional ll representation) or dictionaries of neighbor tuples. Easily convert these structures into Pandas DataFrames for quick inspection and tabular formatting.
• BlackNeatoGraph: An elegant Graphviz-based class using the neato layout engine. Renders beautiful dark-themed networks with circular nodes, custom positioning (pos), overlap prevention, and automatic styling. Provides direct helpers to check graph properties (e.g., maximum/minimum degrees, regularity).
• ValencyList: A specialized helper class to calculate, analyze, and manage the degrees (valency) of all nodes in a graph. Features handshake lemma validation, regular graph detection, and sorted list exports.

Installation

You can install python-graphviz-plus directly from PyPI:

pip install python-graphviz-plus

Quick Start

1. Generating a Black Neato Graph

from graph import BlackNeatoGraph

# Define an edge list (source, destination)
edges = [
    ("A", "B"),
    ("B", "C"),
    ("C", "A"),
    ("C", "D")
]

# Position mapping for nodes (optional)
positions = [
    ("A", "0,0!"),
    ("B", "1,1!"),
    ("C", "2,0!"),
    ("D", "3,-1!")
]

# Create and render the black graph
g = BlackNeatoGraph(ll=edges, lp=positions, name="MyBeautifulGraph")

# Inside a Jupyter Notebook, it will render inline:
# g
# Or save to a file:
g.render("graph_output", format="png", cleanup=True)

2. Inspecting Node Valencies

from graph import ValencyList

# Analyze the valencies from the edge list
valencies = ValencyList(edges)

print("Degrees mapping:", valencies.raw())
print("Is regular graph?", valencies.is_regular())
print("Handshake lemma holds?", valencies.sum_check())

3. Converting to a Tabular Adjacency Matrix / DataFrame

from graph import AdjacencyList

adj = AdjacencyList(edges)
df = adj.to_dataframe()

# Display as pandas DataFrame
print(df)

Requirements

• Python >= 3.8
• graphviz
• networkx
• pandas

Note: Ensure that the Graphviz system binaries (dot, neato, etc.) are installed on your system path.