shap--shap/pyproject.toml

[build-system]
# Note for maintainers: this numpy constraint is specific to wheels for PyPI. See:
# https://numpy.org/doc/stable/dev/depending_on_numpy.html#numpy-2-abi-handling
requires = [
  "scikit-build-core>=0.10.0",
  "setuptools-scm>=8.0",
  "numpy>=2.0",
  "packaging>20.9",
  "nanobind>=2.0.0",
]
build-backend = "scikit_build_core.build"

[project]
name = "shap"
description = "A unified approach to explain the output of any machine learning model."
readme = "README.md"
license = {text = "MIT License"}
authors = [
  {name = "Scott Lundberg", email = "slund1@cs.washington.edu"},
]
requires-python = ">=3.12"
dependencies = [
  'numpy>=2',
  'scipy',
  'scikit-learn',
  'pandas',
  'tqdm>=4.27.0',
  'packaging>20.9',
  'slicer==0.0.8',
  'numba<0.63; sys_platform == "darwin" and platform_machine == "x86_64"',  # numba 0.63+ dropped macOS x86_64 wheels, see numba/numba#10187
  'numba; sys_platform != "darwin" or platform_machine != "x86_64"',
  'llvmlite<0.46; sys_platform == "darwin" and platform_machine == "x86_64"',  # llvmlite 0.46+ dropped macOS x86_64 wheels, see numba/numba#10187
  'llvmlite; sys_platform != "darwin" or platform_machine != "x86_64"',
  'cloudpickle',
]
classifiers = [
  "Operating System :: Microsoft :: Windows",
  "Operating System :: POSIX",
  "Operating System :: Unix",
  "Operating System :: MacOS",
  "Programming Language :: Python :: 3.12",
  "Programming Language :: Python :: 3.13",
  "Programming Language :: Python :: 3.14",
  "Intended Audience :: Information Technology",
  "Intended Audience :: Science/Research",
  "Topic :: Scientific/Engineering",
  "Topic :: Scientific/Engineering :: Artificial Intelligence",
  "Development Status :: 5 - Production/Stable",
  "License :: OSI Approved :: MIT License",
]
dynamic = ["version"]


[dependency-groups]
plots = ["matplotlib", "ipython"]
download-datasets = [
  # Dependencies needed to download datasets for testing
  # scikit-learn is already in core dependencies, but listed here for clarity
  "scikit-learn",
]
docs = [
  {include-group = "plots"},
  "numpydoc",
  "sphinx_rtd_theme",
  "sphinx",
  "nbsphinx",
  "sphinx_github_changelog",
  "myst-parser",
  "requests",
  "ipywidgets",  # For tqdm in notebooks
]
test-core = [
  "pytest",
  "pytest-mpl",
  "pytest-cov",
  "mypy",
  "pre-commit",
  "ruff",
]
test = [
  {include-group = "test-core"},
  "xgboost",
  "lightgbm",
  'catboost; python_version < "3.14"',  # TODO: pending 3.14 support
  'gpboost==1.6.3.1; python_version < "3.14"',  # TODO: pending 3.14 support, see GH #4210
  "ngboost",
  "pyspark",
  "pyod",
  "transformers < 4.54.0",  # TODO: fix once tests pass for 4.54.0
  "tf-keras",
  "protobuf",  # See GH #3046
  'torch<=2.11.0; python_version < "3.14"',  # TODO: pending 3.14 support, see GH #5016
  'torchvision; python_version < "3.14"',  # TODO: pending 3.14 support
  'tensorflow; python_version < "3.14"',  # TODO: pending 3.14 support
  "sentencepiece",
  "opencv-python",
  # Constraint to prevent the combination of tf<2.15 and numpy>=2.0.
  # See GH #3707, #3768, 3922
  "numpy>=2.0",
  "causalml>=0.15.5",
  # causalml imports private sklearn.ensemble._forest internals (DOUBLE, DTYPE, MAX_INT)
  # that were removed in scikit-learn 1.9. See https://github.com/uber/causalml/issues/926
  "scikit-learn<1.9",
  "selenium",  # needed to test the javascript based plots
]
nbtest = [
  "jupyter",
  "nbconvert",
  "nbformat",
  "nlp",
  "transformers",
  "datasets",
  "keras",
  "nbtest-plugin",
  "nbtest-gen",
  "nbtest-lab-extension"
]

[project.urls]
Repository = 'http://github.com/shap/shap'
Documentation = 'https://shap.readthedocs.io/en/latest/index.html'
"Release Notes" = 'https://shap.readthedocs.io/en/latest/release_notes.html'

[tool.uv]
cache-keys = [
  { file = "shap/cext/*.cc" },
  { file = "shap/cext/*.cu" },
  { file = "shap/cext/*.h" },
  { file = "shap/cutils/*.cpp" },
  { file = "shap/cutils/*.h" },
  { file = "CMakeLists.txt" },
]

[tool.mypy]
check_untyped_defs = true
disallow_untyped_calls = false
disallow_untyped_defs = false
disallow_incomplete_defs = false
exclude = ["shap/benchmark/*", "tests/benchmark/*", "shap/_cutils.pyi"]

# NOTE: numpy.typing.mypy_plugin is deprecated in NumPy 2.3+ and will be removed in a future release
# plugins = ["numpy.typing.mypy_plugin"]

[[tool.mypy.overrides]]
# Disable some checks from certain shap modules
# TODO: get these passing!
# NOTE: Modules with added type hints have been removed from this list
module = [
  # "shap.explainers._additive",       # NOW TYPE CHECKED - type hints added
  "shap.explainers._deep.deep_pytorch",
  "shap.explainers._deep.deep_tf",
  # "shap.explainers._exact",          # NOW TYPE CHECKED - type hints added
  # "shap.explainers._explainer",      # NOW TYPE CHECKED - type hints added
  # "shap.explainers._gradient",       # NOW TYPE CHECKED - type hints added
  # "shap.explainers._kernel",         # NOW TYPE CHECKED - type hints added
  # "shap.explainers._linear",         # NOW TYPE CHECKED - type hints added
  # "shap.explainers._partition",      # NOW TYPE CHECKED - type hints added
  # "shap.explainers._permutation",    # NOW TYPE CHECKED - type hints added
  # "shap.explainers._sampling",       # NOW TYPE CHECKED - type hints added
  # "shap.explainers._tree",           # NOW TYPE CHECKED - type hints added
  # "shap.explainers._coalition",      # NOW TYPE CHECKED - type hints added
  # "shap.explainers.other._random",  # NOW TYPE CHECKED - type hints added
  "shap.explainers.pytree",
  "shap.explainers.tf_utils",
  # "shap.maskers._composite",  # NOW TYPE CHECKED - type hints added
  # "shap.maskers._fixed",      # NOW TYPE CHECKED - type hints added
  "shap.maskers._image",
  # "shap.maskers._masker",     # NOW TYPE CHECKED - type hints added
  "shap.maskers._tabular",
  "shap.maskers._text",
  "shap.plots._benchmark",
  "shap.plots._force_matplotlib",
  "shap.plots._force",
  "shap.plots._text",
  "shap.plots._waterfall",
]
check_untyped_defs = false

[[tool.mypy.overrides]]
# Ignore missing types for 3rd party libraries
module = [
  "catboost.*",
  "cloudpickle",
  "cv2",
  "IPython.*",
  "lightgbm.*",
  "lime.*",
  "numba",
  "pandas",
  "pyod.*",
  "pyspark.*",
  "scipy.*",
  "sklearn.*",
  "slicer",
  "tensorflow.*",
  "transformers.*",
  "torch.*",
  "tqdm.*",
  "xgboost.*",
  "causalml.*",
  "selenium.*",
]
ignore_missing_imports = true

[tool.setuptools_scm]
version_file = "shap/_version.py"
# Use "no-local-version" so dev releases are compatibile with PyPI
local_scheme = "no-local-version"

[tool.scikit-build]
# List of packages to include in the wheel
wheel.packages = [
  'shap',
  'shap.cext',
  'shap.explainers',
  'shap.explainers.other',
  'shap.explainers._deep',
  'shap.plots',
  'shap.plots.colors',
  'shap.plots.resources',
  'shap.benchmark',
  'shap.maskers',
  'shap.utils',
  'shap.actions',
  'shap.models',
]

metadata.version.provider = "scikit_build_core.metadata.setuptools_scm"
sdist.include = ["shap/_version.py"]
sdist.exclude = ["docs/", "notebooks/", ".claude/", "appveyor/"]

# Protect the configuration against future changes in scikit-build-core
minimum-version = "build-system.requires"

# Setuptools-style build caching in a local directory
build-dir = "build/{wheel_tag}"

# Exclude C/C++/CUDA source files from the wheel (compiled .so is sufficient)
wheel.exclude = ["**/*.cc", "**/*.cpp", "**/*.h", "**/*.cu"]

# Build stable ABI wheels for CPython 3.12+
wheel.py-api = "cp312"


[tool.pytest.ini_options]
addopts = "--mpl -m 'not xslow'"
mpl-default-style = "default"
testpaths = ["tests"]
filterwarnings = [
  # Ignore warnings that are entirely from 3rd party libs outside our control
  "ignore:.*distutils Version classes are deprecated.*:DeprecationWarning:.*pandas.*",
  "ignore:.*typing.io is deprecated.*:DeprecationWarning:.*pyspark.*",
  "ignore:.*is_datetime64tz_dtype is deprecated.*:DeprecationWarning:.*pyspark.*",
  "ignore:.*'force_all_finite' was renamed to 'ensure_all_finite' in 1.6.*:FutureWarning:.*sklearn.*",
]
markers = ["xslow: mark test as extremely slow (not run unless explicitly requested)"]

[tool.ruff]
# Careful: when running on pre-commit, ruff's "include" and "exclude" config
# options are ignored! So, instead of "exclude", use the "per-file-ignores"
# config to always disable linting for specific files.
include = ["*.py", "*.pyi", "**/pyproject.toml", "*.ipynb"]
extend-exclude = ["**/tree_shap_paper/**", "docs/user_studies/*"]
line-length = 120

[tool.ruff.lint]
select = [
  "F",  # pyflakes
  "I",  # isort
  "ISC",  # string literal concatenation.
  "UP",  # pyupgrade
  "E",  # pycodestyle
  "W",  # warning
  "D",  # pydocstyle
  "NPY",  # Numpy
  "SIM101",  # flake8-simplify
  "FA",  # future annotations
  "TCH",  # Move type only imports to type-checking condition.
  # D417  # undocumented parameter. FIXME: get this passing
]
ignore = [
  # Recommended rules to disable when using ruff formatter:
  # https://docs.astral.sh/ruff/formatter/#conflicting-lint-rules
  "D206",
  "D300",
  "E111",
  "E114",
  "E117",
  "E501",
  "W191",

  # pydocstyle issues not yet fixed
  "D100",  # Missing docstring in public module
  "D101",  # Missing docstring in public class
  "D102",  # Missing docstring in public method
  "D103",  # Missing docstring in public function
  "D104",  # Missing docstring in public package
  "D105",  # Missing docstring in magic method
  "D205",  # 1 blank line required between summary line and description
  "D400",  # First line should end with a period
  "D401",  # First line of docstring should be in imperative mood: "A basic partial dependence plot function."
  "D404",  # First word of the docstring should not be "This"
  "NPY002",  # Allow numpy RandomState objects in tests
]

[tool.ruff.lint.pydocstyle]
convention = "numpy"

[tool.ruff.lint.per-file-ignores]
# Don't apply linting/formatting to vendored code
"shap/explainers/other/_maple.py" = ["ALL"]

# Ignore notebooks in user_studies, which are not maintained
"docs/user_studies/*.ipynb" = ["ALL"]

# Ignore SHAP Paper, as it is an unmaintained record of a published paper
"notebooks/tabular_examples/tree_based_models/tree_shap_paper/*"  = ["ALL"]

# Disable some unwanted rules on Jupyter notebooks
"*.ipynb" = ["D", "E703", "E402"]  # Allow trailing semicolons, allow imports not at top

# Ignore pycodestyle in tests
"tests/*py" = ["D"]

[tool.coverage.run]
source_pkgs = ["shap"]
omit = ["shap/benchmark/*"]

[tool.coverage.paths]
combine = ["shap", "*/site-packages/shap"]

[tool.cibuildwheel]
# TODO: Should we use uv as build frontend for faster builds?
# build-frontend = "uv"

# Restrict the set of builds to mirror the wheels available in scipy. See #3028
# skip cp314-macosx_x86_64 due to lack of numba and llvmlite support
# skip *t (free-threaded builds) since dependencies like llvmlite don't support it yet
skip = [
  "cp314-macosx_x86_64",
  "cp314t-manylinux_x86_64",
  "cp314t-macosx_x86_64",
  "cp314t-win_amd64",
]
build-verbosity = 2
# Change import-mode to ensure we test against installed package, not local project
test-command = "pytest -v {project}/tests --import-mode=append"
test-groups = ["test-core", "plots"]
# skip tests on *-musllinux*" since llvmlite and numba do not provide musllinux wheels
test-skip = "*-musllinux*"

[tool.cibuildwheel.linux]
archs = ["x86_64", "aarch64"]

[tool.cibuildwheel.windows]
# TODO: Should we support Windows ARM64 too?
archs = ["AMD64"]

[tool.cibuildwheel.macos]
# TODO: Should we build universal2 wheels for macOS to reduce wheel count?
archs = ["x86_64", "arm64"]

[tool.cibuildwheel.macos.environment]
# Needed for C++17 support
MACOSX_DEPLOYMENT_TARGET = "10.13"