Hands-On Graph Neural Networks Using Python — Second Edition

Companion code for Hands-On Graph Neural Networks Using Python, Second Edition, published by Packt.

This repository contains per-chapter runnable scripts, figure generators, and pinned requirements so you can reproduce the examples from the book.

Table of Contents

• Chapter03/ — Creating Node Representations with DeepWalk
• Chapter04/ — Improving Embeddings with Biased Random Walks in Node2Vec
• Chapter05/ — Including Node Features with Vanilla Neural Networks

Each chapter folder contains:

• run.py — the main script for the chapter
• requirements.txt — pinned Python dependencies
• figures/ — scripts that regenerate the figures used in the book

Setup

The code targets Python 3.10+.

1. Clone the repository:

   git clone https://github.com/PacktPublishing/Hands-On-Graph-Neural-Networks-Using-Python-Second-Edition.git
   cd Hands-On-Graph-Neural-Networks-Using-Python-Second-Edition

2. Create and activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate   # on Windows: .venv\Scripts\activate

3. Install the dependencies for the chapter you want to run:

   pip install -r Chapter03/requirements.txt

Running a chapter

From the repository root:

python Chapter03/run.py

To regenerate the figures for a chapter:

python Chapter03/figures/generate_figures.py

License

See LICENSE.