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Python package (work in progress) implementing sampling policies (known and new) for (contextual) bandits and valid statistical inference methods

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ramonVDAKKER/research-bandits-methods

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research-bandits-methods

Python package implementing sampling policies for contextual bandits and statistical inference methods.

Requirements

  • Python 3.13+
  • uv package manager
  • Make

Installation

# Clone the repository
git clone https://github.com/ramonvdakker/research-bandits-methods.git
cd research-bandits-methods

# Install dependencies
uv sync

# Install with development dependencies
uv sync --group dev

Usage

TODO

Development

TODO

Running Tests

# Run all tests with coverage
make test

# Run specific test
uv run --group dev pytest tests/test_main.py::test_main

# View coverage report
open htmlcov/index.html

Linting and Code Quality

# Run all pre-commit hooks
make lint

# Install pre-commit hooks (runs automatically on commit)
uv run --with pre-commit pre-commit install

The project enforces code quality through pre-commit hooks:

  • ruff: Linting and formatting
  • isort: Import sorting
  • mypy: Type checking
  • pydocstyle: Docstring conventions
  • interrogate: Docstring coverage
  • bandit: Security checks
  • detect-secrets: Secret detection

License

See LICENSE file for details.

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Python package (work in progress) implementing sampling policies (known and new) for (contextual) bandits and valid statistical inference methods

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