Networks Python Packages

graphframes

GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs

graphframes-py

GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs

osmnx

Download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap.

graspologic

Python package for graph statistics

cityseer

Computational tools for urban analysis

graphframes-latest

GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs

nrel-routee-compass

An energy-aware vehicle routing engine

pybel

🌶️ An ecosystem in Python for working with the Biological Expression Language (BEL)

iplotx

Visualise networks and trees in Python, with style.

markov-clustering

markov clustering in python

nxontology

NetworkX-based Python library for representing ontologies

pynets

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

lanet-vi

Visualize large networks by k-core, k-dense and d-core decomposition. Python rewrite of the LaNet-vi C++ tool, with CLI and API.

agentpy

AgentPy is an open-source framework for the development and analysis of agent-based models in Python.

ilayoutx

Graph layout algorithms in Rust/Python

nemtropy

A python3 module for maximum entropy models on networks.

pybel-tools

A PyBEL extension for analyzing BEL graphs

gp3sequencespy

Transparent, reproducible sequence analysis in Python. Audit ordered categorical data, discover recurring structure, compare trajectories, model transitions and latent states, test group differences, and report every analytical choice.

graph-tiger

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

kgcnn

Graph convolutions in Keras with TensorFlow, PyTorch or Jax.

boolforge

Generates and analyzes random Boolean functions and networks with a focus on the concept of canalization

torch-geometric-signed-directed

PyTorch Geometric Signed Directed is a signed/directed graph neural network extension library for PyTorch Geometric. The paper is accepted by LoG 2023.

graspy

Python package for graph statistics

graphdml

Causal effects on networks with double machine learning: ATE, direct and peer (spillover) effects with confidence intervals that account for network dependence. scikit-learn and Neo4j integration.