pyproject.toml

[build-system]
requires = [
  "setuptools >= 61.0.0",
  "wheel",
  "setuptools_scm[toml] >= 6.2"
]
build-backend = "setuptools.build_meta"

[project]
name = "julearn"
description = "Juelich Machine Learning Library"
readme = "README.md"
requires-python = ">=3.8"
license = {text = "AGPL-3.0-only"}
authors = [
    { name = "Fede Raimondo", email = "f.raimondo@fz-juelich.de" },
    { name = "Sami Hamdan", email = "s.hamdan@fz-juelich.de" },
]
maintainers = [
    {name = "Sami Hamdan", email = "s.hamdan@fz-juelich.de"},
]
keywords = [
    "machine-learning",
]
classifiers = [
    "Development Status :: 5 - Production/Stable",
    "Intended Audience :: Science/Research",
    "Intended Audience :: Developers",
    "License :: OSI Approved",
    "Natural Language :: English",
    "Topic :: Software Development",
    "Topic :: Scientific/Engineering",
    "Operating System :: OS Independent",
    "Programming Language :: Python :: 3.8",
    "Programming Language :: Python :: 3.9",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
]
dependencies = [
    "numpy>=1.24,<1.27",
    "pandas>=1.5.0,<2.3",
    "statsmodels>=0.13,<0.15",
    "scikit-learn>=1.2.0,<1.6.0",
]
dynamic = ["version"]

[project.urls]
homepage = "https://juaml.github.io/julearn"
documentation = "https://juaml.github.io/julearn"
repository = "https://github.com/juaml/julearn"

[project.optional-dependencies]
dev = ["tox", "pre-commit"]
docs = [
    "seaborn>=0.12.2,<0.13",
    "sphinx>=5.3.0,<7.3",
    "sphinx-gallery>=0.13.0,<0.15",
    "furo>=2022.9.29,<2024.0.0",
    "sphinx_copybutton>=0.5.0,<0.6",
    "numpydoc>=1.5.0,<1.6",
    "towncrier<24",
    "scikit-optimize>=0.10.0,<0.11",
    "optuna>=3.6.0,<3.7",
    "optuna_integration>=3.6.0,<4.1",
]
deslib = ["deslib>=0.3.5,<0.4"]
viz = [
    "panel>=1.3.0",
    "bokeh>=3.0.0",
    "param>=2.0.0",
]
skopt = ["scikit-optimize>=0.10.0,<0.11"]
optuna = [
    "optuna>=3.6.0,<3.7",
    "optuna_integration>=3.6.0,<4.1",
]
# Add all optional functional dependencies (skip deslib until its fixed)
# This does not include dev/docs building dependencies
all = ["julearn[viz,skopt,optuna]"]

################
# Tool configs #
################

[tool.setuptools]
packages = ["julearn"]

[tool.setuptools_scm]
version_scheme = "guess-next-dev"
local_scheme = "no-local-version"
write_to = "julearn/_version.py"

[tool.black]
line-length = 79
target-version = ["py38", "py39", "py310", "py311"]

[tool.codespell]
skip = "*/auto_examples/*,*.html,.git/,*.pyc,*/_build/*,*/api/generated/*.examples,julearn/external/*"
count = ""
quiet-level = 3
ignore-words = "ignore_words.txt"
interactive = 0
builtin = "clear,rare,informal,names,usage,code"

[tool.ruff]
line-length = 79
extend-exclude = [
    "__init__.py",
    "docs",
    "examples",
    "external",
]

[tool.ruff.lint]
select = [
    # flake8-bugbear
    "B",
    # flake8-blind-except
    "BLE",
    # flake8-comprehensions
    "C4",
    # mccabe
    "C90",
    # pydocstyle
    "D",
    # pycodestyle errors
    "E",
    # pyflakes
    "F",
    # isort
    "I",
    # pep8-naming
    "N",
    # pygrep-hooks
    "PGH",
    # ruff
    "RUF",
    # flake8-type-checking
    "TCH",
    # pyupgrade
    "UP",
    # pycodestyle warnings
    "W",
    # flake8-2020
    "YTT",
]
extend-ignore = [
    # Use of `functools.lru_cache` or `functools.cache` on methods can lead to
    # memory leaks. The cache may retain instance references, preventing garbage
    # collection.
    "B019",
    # abstract class with no abstract methods
    "B024",
    "D202",
    # missing docstring in __init__, incompatible with numpydoc
    "D107",
    # use r""" if any backslashes in a docstring
    "D301",
    # class names should use CapWords convention
    "N801",
    # function name should be lowercase
    "N802",
    # variable in function should be lowercase
    "N806",
    # use specific rule codes when ignoring type issues
    "PGH003",
]

[tool.ruff.lint.isort]
lines-after-imports = 2
known-first-party = ["julearn"]
known-third-party =[
    "numpy",
    "pandas",
    "sklearn",
    "statsmodels",
    "bokeh",
    "panel",
    "param",
    "deslib",
    "pytest",
]

[tool.ruff.lint.mccabe]
max-complexity = 20

[tool.towncrier]
directory = "docs/changes/newsfragments"
filename = "docs/whats_new.rst"
package = "julearn"
# to use gh_substitutions
issue_format = ":gh:`{issue}`"
# modify to have proper toctree
underlines = "-^~"
# set line length to 79
wrap = true

# Need to put default explicitly as custom is not combined with default

[tool.towncrier.fragment.bugfix]
name = "Bugfixes"
showcontent = true

[tool.towncrier.fragment.doc]
name = "Improved Documentation"
showcontent = true

[tool.towncrier.fragment.feature]
name = "Features"
showcontent = true

[tool.towncrier.fragment.misc]
name = "Misc"
showcontent = true

[tool.towncrier.fragment.removal]
name = "Deprecations and Removals"
showcontent = true

# Add custom towncrier fragment for enhancements
[tool.towncrier.fragment.enh]
name = "Enhancements"
showcontent = true

# Add custom towncrier fragment for API changes
[tool.towncrier.fragment.change]
name = "API Changes"
showcontent = true

## Configure pyright to ignore assignment types until scikit-learn stubs are updated
[tool.pyright]
reportAssignmentType = "none"
exclude = [
    "docs/auto_examples/",
    "*.html",
    ".git/",
    "*.pyc,",
    "*/_build/*",
    "*/api/generated/*.examples",
    "build/",
    "examples/XX_disabled/",
    ".tox",
    ".eggs",
    "examples/",  # Lots of problems due to bad stubs, avoid filling the example with # type:ignore
    "julearn/external",  # External code, not to be checked
    "scratch/",  # place to prototype, not to be checked
]