anomrank

This is a Python implementation of the original C++ code of the paper Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach.

Building

To improve performance, some parts of the library are written using Rust.

We use the PyO3 crate for exporting Rust functions as a Python module. The recommended tool for developing and packaging the library is maturin.

Setting up a development environment

Create a new Python virtual environment:

python3 -m venv .venv

Build the Rust library and make it available to Python using maturin:

maturin develop