Installation and Setup

This guide covers all aspects of installing py3plex and setting up your environment.

Basic Installation

Install from GitHub (Recommended)

The latest version is always available on GitHub:

pip install git+https://github.com/SkBlaz/py3plex.git

This installs the core py3plex library with all required dependencies.

Install from Source

For development or to access the latest features:

git clone https://github.com/SkBlaz/py3plex.git
cd py3plex
pip install -e .

The -e flag installs in “editable” mode, so changes to the source code are immediately available.

Optional Dependencies

py3plex offers several optional feature sets that can be installed separately:

Advanced Community Detection

Install Infomap for advanced overlapping community detection:

pip install git+https://github.com/SkBlaz/py3plex.git#egg=py3plex[infomap]

Additional Algorithms

Install extra community detection algorithms (Louvain, cdlib):

pip install git+https://github.com/SkBlaz/py3plex.git#egg=py3plex[algos]

Advanced Visualization

Install Plotly and igraph for interactive and advanced visualizations:

pip install git+https://github.com/SkBlaz/py3plex.git#egg=py3plex[viz]

Multiple Extras

Install multiple feature sets at once:

pip install git+https://github.com/SkBlaz/py3plex.git#egg=py3plex[infomap,viz,algos]

Development Installation

For contributors, install with development tools (testing, linting):

git clone https://github.com/SkBlaz/py3plex.git
cd py3plex
pip install -e ".[dev]"

This installs:

pytest and coverage tools
black, ruff, isort for code formatting
mypy for type checking
sphinx for documentation building

System Requirements

Python Version

py3plex requires Python 3.8 or higher. We test on:

Python 3.8
Python 3.9
Python 3.10
Python 3.11
Python 3.12

Platform Support

py3plex is cross-platform and tested on:

Linux (Ubuntu 20.04, 22.04)
macOS (macOS 11, 12, 13)
Windows (Windows Server 2019, 2022)

Core Dependencies

These are automatically installed with py3plex:

networkx>=2.5 - Graph data structures and algorithms
numpy>=0.8 - Numerical computing
scipy>=1.1.0 - Scientific computing and sparse matrices
pandas - Data manipulation
matplotlib - Static visualization
scikit-learn - Machine learning utilities
tqdm - Progress bars
rdflib>=0.1 - Semantic web support
bitarray>=2.0.0 - Efficient boolean arrays

External Binaries (Optional)

Note: As of October 2025, py3plex no longer bundles external binaries to reduce repository size and improve licensing clarity.

Infomap Community Detection

For advanced community detection using Infomap:

Option 1: Use the bundled Python implementation (recommended):

pip install git+https://github.com/SkBlaz/py3plex.git#egg=py3plex[infomap]

Option 2: Download the C++ binary from the official source:

Website: https://www.mapequation.org/infomap/
Follow platform-specific installation instructions

Alternative: Use the built-in Louvain algorithm (no binary needed):

from py3plex.algorithms.community_detection import community_louvain
communities = community_louvain.best_partition(network.core_network)

Node2Vec Embeddings

For Node2Vec node embeddings, use pure Python alternatives:

Option 1: Use pecanpy (fast parallel implementation):

pip install pecanpy

Option 2: Use node2vec package:

pip install node2vec

Option 3: Use py3plex’s built-in random walk implementation:

from py3plex.algorithms.general.walkers import node2vec_walk, generate_walks
walks = generate_walks(network.core_network, num_walks=10, walk_length=80)

See bin/README.md for detailed installation instructions and alternatives.

Virtual Environment Setup

We strongly recommend using a virtual environment:

Using venv

# Create virtual environment
python3 -m venv py3plex-env

# Activate (Linux/macOS)
source py3plex-env/bin/activate

# Activate (Windows)
py3plex-env\Scripts\activate

# Install py3plex
pip install git+https://github.com/SkBlaz/py3plex.git

Using conda

# Create conda environment
conda create -n py3plex python=3.10

# Activate
conda activate py3plex

# Install py3plex
pip install git+https://github.com/SkBlaz/py3plex.git

Common Installation Issues

Issue: “No module named ‘numpy’”

Solution: Install numpy first:

pip install numpy
pip install git+https://github.com/SkBlaz/py3plex.git

Issue: Compilation errors on Windows

Solution: Install Visual C++ Build Tools:

Download from: https://visualstudio.microsoft.com/visual-cpp-build-tools/
Install “Desktop development with C++”
Retry installation

Issue: “Permission denied” on Linux/macOS

Solution: Use pip install with –user flag:

pip install --user git+https://github.com/SkBlaz/py3plex.git

Or use a virtual environment (recommended).

Issue: Old version installed

Solution: Upgrade to latest version:

pip install --upgrade git+https://github.com/SkBlaz/py3plex.git

Verifying Installation

Test that py3plex is correctly installed:

import py3plex
print(py3plex.__version__)

from py3plex.core import multinet
network = multinet.multi_layer_network()
print("py3plex installed successfully!")

Run the test suite:

# Clone repository (if not already)
git clone https://github.com/SkBlaz/py3plex.git
cd py3plex

# Run tests
python run_tests.py

License Considerations

Main Library License

py3plex core is distributed under the MIT License (permissive, commercial-friendly).

Bundled Code Licenses

Important: The repository contains AGPLv3-licensed code in py3plex/algorithms/community_detection/infomap/.

If you use Infomap-based community detection functions, your application may be subject to AGPLv3 requirements (copyleft).

License Matrix

Feature Category	License	Commercial Use	Notes
Core multilayer functionality	MIT	✅ Yes	Safe for proprietary use
Network visualization	MIT	✅ Yes	Safe for proprietary use
I/O operations	MIT	✅ Yes	Safe for proprietary use
Louvain community detection	BSD-3-Clause	✅ Yes	Safe for proprietary use
Label propagation	MIT	✅ Yes	Safe for proprietary use
Infomap community detection	AGPLv3	⚠️ Restricted	Viral license - requires open-sourcing derived works

Recommendations

For commercial/proprietary projects: Avoid Infomap functions or use the pure Python infomap package separately
For open-source projects: All features are safe to use
When in doubt: Use alternative algorithms (Louvain, label propagation) which are BSD/MIT licensed

Next Steps

After installation, proceed to:

Quickstart Guide - Quick introduction to basic features
10-Minute Tutorial: Getting Started with Py3plex - Comprehensive 10-minute tutorial
Quick Start Guide - Detailed usage guide

Getting Help

If you encounter installation issues:

Check GitHub Issues
Search for similar problems
Open a new issue with:
- Your operating system and version
- Python version (python --version)
- Error message and full traceback
- Installation command used

For any errors, please open an issue at https://github.com/SkBlaz/py3plex/issues