stag/pyproject.toml at main · zerotonin/stag · GitHub

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[build-system]
requires = ["setuptools>=68.0", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "stag"
version = "0.2.0"
description = "Sensor-based Tracking and Analysis of Gait — unsupervised behaviour classification from wearable accelerometers."
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.10"
authors = [
    {name = "Alexander R. H. Matthews"},
    {name = "Lindsay R. Matthews"},
    {name = "Bart R. H. Geurten", email = "bart.geurten@otago.ac.nz"},
]
keywords = [
    "accelerometer",
    "behaviour-classification",
    "markov-transition-model",
    "deer",
    "precision-livestock-farming",
    "unsupervised-learning",
]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: MIT License",
    "Programming Language :: Python :: 3",
    "Topic :: Scientific/Engineering :: Bio-Informatics",
]

dependencies = [
    "numpy>=1.24",
    # pandas>=1.5 — keeps the package installable into the RAPIDS 24.02
    # env on Aoraki, which pins cudf <-> pandas<2.0.  STAG itself does
    # not use any pandas-2.x-only feature; the workstation env will
    # happily satisfy this with whichever 2.x is already installed.
    "pandas>=1.5",
    "scipy>=1.10",
    "scikit-learn>=1.3",
    "sqlalchemy>=2.0",
    "matplotlib>=3.7",
    "seaborn>=0.12",
    "tqdm>=4.65",
    "kneed>=0.8",
    "astral>=3.0",
]

[project.optional-dependencies]
gpu = [
    "cupy-cuda12x",
    # cuml must be installed via conda/rapids — listed here for reference
]
gps = [
    "pyproj>=3.5",
    "tables>=3.8",
]
docs = [
    "sphinx>=7.0",
    "sphinx-rtd-theme>=2.0",
    "sphinx-autodoc-typehints>=1.23",
]
dev = [
    "pytest>=7.0",
    "pytest-cov>=4.0",
    "ruff>=0.3",
]

[project.urls]
Repository = "https://github.com/zerotonin/stag"
Documentation = "https://zerotonin.github.io/stag/"

[tool.setuptools.packages.find]
include = ["stag*"]

[tool.ruff]
line-length = 120
target-version = "py310"
exclude = [
    "stag/_legacy",        # archived pre-refactor code, intentional rot
    "docs/_build",         # Sphinx output
    "results",             # generated figures/tables
    "stag/embedded/benchmark/*/build",
]

[tool.ruff.lint]
select = ["E", "F", "I", "W", "D"]
ignore = [
    "D100",  # missing-docstring-in-public-module (covered by ASCII banner)
    "D104",  # missing-docstring-in-public-package
    "D203",  # one-blank-line-before-class (mutually exclusive with D211)
    "D213",  # multi-line-summary-second-line (mutually exclusive with D212)
]

[tool.ruff.lint.per-file-ignores]
# Test files: the test name and class name ARE the documentation; the
# discovery-by-prefix convention makes a separate docstring redundant.
"tests/**/*.py" = ["D101", "D102", "D103", "D106", "D107"]
# CLI / driver scripts are self-documenting via argparse --help; do not
# require per-function docstrings on every helper used inside a script.
"scripts/**/*.py" = ["D101", "D102", "D103", "D107"]
# SLURM-orchestration scripts inside the package are entry points, not
# library API; same exemption as scripts/.
"stag/slurm/**/*.py" = ["D101", "D102", "D103", "D107"]
# Embedded benchmark runners are emulator drivers (called from Make
# targets), not library API; same exemption as scripts/.
"stag/embedded/benchmark/**/*.py" = ["D101", "D102", "D103", "D107"]

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

[tool.pytest.ini_options]
testpaths = ["tests"]