Solver Benchmark Website

This repository contains code for benchmarking LP/MILP solvers, and an interactive website for analyzing the results.

Initial Setup

Before you begin, make sure your development environment includes Python.

Preferred use:

• python: 3.12.4
• pip: 24.1.2

We use Python virtual environments to manage the dependencies for each component of this project. This is how to create a virtual environment:

python -m venv venv

This is how to activate one:

• Windows

  .\venv\Scripts\activate

• Linux/MacOS

  source venv/bin/activate

  And this is how to install the required dependencies once a venv is activated:

• Benchmark Runner:

  sudo apt install glpk-utils libglpk-dev  # GLPK solver cannot be installed purely with pip
  pip install -r runner/requirements.txt

• Website:

  pip install -r website/requirements.txt

Development

We use the ruff code linter and formatter, and GitHub Actions runs various pre-commit checks to ensure code and files are clean.

You can install a git pre-commit that will ensure that your changes are formatted and no lint issues are detected before creating new commits:

pip install pre-commit
pre-commit install

If you want to skip these pre-commit steps for a particular commit, you can run:

git commit --no-verify

Run Project

Remember to activate the appropriate virtual environment before running the runner or the website.

1. Run Benchmark Runner

   python runner/run_benchmarks.py

   The app will save the runtime and memory consumption into a CSV file.

2. Run Website

   streamlit run website/app.py

   The website will be running on: http://localhost:8501