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:

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
pip install git+https://github.com/PyPSA/linopy.git@40a27f9e7f5d33acd1d256334a1b193899b166ad
```
NOTE: The last line is required to install the master branch of linopy, which includes updates from the merged PR that support reading LP files. Once a new version of linopy is released, we can remove this line and rely on the latest version of linopy from PyPI instead.
Website:
```
pip install -r website/requirements.txt
```

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

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

Run Benchmark Runner
```
python runner/run_benchmarks.py
```
The app will save the runtime and memory consumption into a CSV file.
Run Website
```
streamlit run website/app.py
```
The website will be running on: http://localhost:8501