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Rework information (#499)
* updated some little inconsistencies across the codebase * updated github actions to cancel in progress * updated some little inconsistencies across the codebase * updated github actions to cancel in progress
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.github/CONTRIBUTING.md

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environment with the following command:
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```sh
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uv sync --all-extras --dev
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uv sync
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```
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Now you are all set up and ready to go.
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Then, you can build the documentation from the root of the repository with:
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```sh
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uv run sphinx-build docs/source docs/build
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uv run sphinx-build -b html docs/source docs/build/html
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```
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This will render the documentation in the `docs/build` directory. You can open the `index.html` file
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#### Static Type Checking and Code Quality
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Currently, we do not have static type checking in place. We use `pre-commit` to run some code quality
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checks. These checks **absolutely need to pass**. You can run the checks with the following command:
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We use [`ty`](https://github.com/astral-sh/ty) for static type checking on the `src/shapiq/` package.
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You can run the type checker with:
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```sh
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uv run ty check src/shapiq
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```
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We also use `pre-commit` to run code quality checks. These checks **absolutely need to pass**. You
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can run the checks with the following command:
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```sh
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uv run pre-commit run --all-files

.github/workflows/ci.yml

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push:
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branches: [main]
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workflow_dispatch:
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concurrency:
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group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
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cancel-in-progress: true
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jobs:
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# ----------------------------------------------------------------------------------------------
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# Code Quality Checks and Linting

.gitignore

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src/shapiq/_version.py
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docs/source/auto_examples/
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docs/source/sg_execution_times.rst
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.claude

AGENTS.md

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# CLAUDE.md
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# AGENTS.md
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Guidance for Claude Code when working in this repository.
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README.md

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Shapley Interaction Quantification (`shapiq`) is a Python package for (1) approximating any-order Shapley interactions, (2) benchmarking game-theoretical algorithms for machine learning, (3) explaining feature interactions of model predictions. `shapiq` extends the well-known [shap](https://github.com/shap/shap) package for both researchers working on game theory in machine learning, as well as the end-users explaining models. SHAP-IQ extends individual Shapley values by quantifying the **synergy** effect between entities (aka **players** in the jargon of game theory) like explanatory features, data points, or weak learners in ensemble models. Synergies between players give a more comprehensive view of machine learning models.
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## 🛠️ Install
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`shapiq` is intended to work with **Python 3.10 and above**.
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`shapiq` is intended to work with **Python 3.12 and above**.
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Installation can be done via `uv` :
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```sh
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uv add shapiq

pyproject.toml

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"nbconvert", # notebook support for sphinx
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"nbsphinx", # notebook support for sphinx
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"commonmark", # Markdown parser and renderer
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# TODO(mmschlk): remove the pin in ipython when we drop python 3.10 support and pin to
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# ipython>=9.0.0, since ipython==8.7.0 introduces a bug with parsing notebooks also discussed
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# here: https://github.com/spatialaudio/nbsphinx/issues/24
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"ipython<8.39.0", # for code execution in notebooks
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"ipython>=9.0.0", # for code execution in notebooks
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"sphinx-gallery", # gallery of examples from Python scripts
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"matplotlib", # required for sphinx-gallery thumbnails
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]

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