pyproject.toml

[tool.poetry]
name = "torch-conduit"
version = "0.4.3a0"
description = "Lightweight framework for dataloading with PyTorch and channeling the power of PyTorch Lightning"
authors = ["PAL <info@predictive-analytics-lab.com>"]
license = "Apache License 2.0"
packages = [{ include = "conduit" }]
include = ["conduit/py.typed"]
classifiers = [
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "License :: OSI Approved :: Apache Software License",
    "Operating System :: OS Independent",
    "Typing :: Typed",
]
keywords = [
    "typing",
    "python",
    "pytorch",
    "datasets",
    "pytorch-lightning",
    "lightning-bolts",
]
repository = "https://github.com/wearepal/conduit"
readme = "README.md"

[tool.poetry.dependencies]
numpy = "^1.22.3"
pandas = ">=1.3.3,<3.0"
python = ">=3.10,<3.13"
ranzen = ">=2.4.1"
scikit-learn = "^1.2.0"
typing-extensions = ">=4.4.0"

# download
gdown = { version = "^3.13.0", optional = true }
kaggle = { version = "^1.5.12", optional = true }
# image
albumentations = { version = "^1.0.0", optional = true }
opencv-python = { version = "^4.5.3", optional = true }
# audio
soundfile = { version = "*", markers = "platform_system == 'Windows'", optional = true }
sox = { version = "*", markers = "platform_system == 'Linux' or platform_system == 'macOS'", optional = true }
# hydra
hydra-core = { version = "^1.1.1", optional = true }
# logging
rich = { version = "^12.5.1", optional = true }
# fair
ethicml = { version = "^1.2.1", extras = ["data"], optional = true }
folktables = { version = "^0.0.12", optional = true }

[tool.poetry.extras]
download = ["gdown", "kaggle"]
image = ["albumentations", "opencv-python"]
audio = ["soundfile", "sox"]
hydra = ["hydra-core"]
logging = ["rich"]
fair = ["ethicml", "folktables"]
all = [
    "gdown",
    "kaggle",         # download
    "albumentations",
    "opencv-python",  # image
    "soundfile",
    "sox",            # audio
    "hydra-core",     # hydra
    "rich",           # logging
    "ethicml",
    "folktables",     # fair
]

[[tool.poetry.source]]
name = "torchcpu"
url = "https://download.pytorch.org/whl/cpu"
priority = "explicit"

[tool.poetry.group.torchcpu]
optional = true

[tool.poetry.group.torchcpu.dependencies]
pytorch-lightning = "^2.0.1.post0"
torch = { version = "*", source = "torchcpu", markers = "sys_platform == 'linux'" }
torchvision = { version = "*", source = "torchcpu", markers = "sys_platform == 'linux'" }
torchaudio = { version = "*", source = "torchcpu", markers = "sys_platform == 'linux'" }

[tool.poetry.group.dev.dependencies]
pre-commit = "*"
neoconfigen = { version = ">=2.3.3" }

[tool.poetry.group.test.dependencies]
pytest = "*"

[tool.poetry.group.typecheck.dependencies]
pandas-stubs = "*"
types-tqdm = "*"
types-pillow = "^9.5.0.4"
python-type-stubs = { git = "https://github.com/wearepal/python-type-stubs.git", rev = "8d5f608" }

[tool.poetry.group.lint.dependencies]
darglint = "^1.8.0"
ruff = ">=0.2.2"

[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

[tool.ruff]
line-length = 100
target-version = "py310"

[tool.ruff.format]
quote-style = "preserve"
exclude = ["conduit/hydra/**"]

[tool.ruff.lint]
select = [
    "E", # pycodestyle
    "F", # pyflakes
    "I", # isort
    # "N", # naming
    "NPY", # numpy
    "PIE",
    "PLC", # pylint convention
    "PLE", # pylint error
    # "PLR", # pylint refactor
    "PLW", # pylint warning
    "PTH", # use-pathlib
    "SIM", # simplify
    "UP", # pyupgrade
    "W",
]
ignore = [
    "E501",    # line length
    "E721",    # `isinstance()` vs `type() == type()`
    "E741",    # ambiguous variable name
    "F541",    # f-string without placeholder
    "NPY002",  # np.random
    "PLW2901", # overwriting loop variable
    "PLC0105", # covariant typevars have to end in "_co"
    "SIM108",  # ternary operator
    "UP038",  # isinstance calls with `X | Y`
]

[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["F403"]

[tool.ruff.lint.isort]
known-third-party = [
    "PIL",
    "albumentations",
    "attr",
    "cv2",
    "ethicml",
    "hydra",
    "numpy",
    "omegaconf",
    "pandas",
    "pytest",
    "pytorch_lightning",
    "ranzen",
    "requests",
    "rich",
    "sklearn",
    "torch",
    "torchaudio",
    "torchmetrics",
    "torchvision",
    "tqdm",
]
extra-standard-library = ["typing_extensions"]
no-lines-before = ["future", "standard-library"]
force-sort-within-sections = true
split-on-trailing-comma = false
classes = ["MISSING", "NICO", "PACS", "SSRP", "ISIC"]
case-sensitive = true

[tool.pyright]
typeCheckingMode = "strict"
pythonVersion = "3.10"
reportMissingTypeArgument = "none"
reportCallInDefaultInitializer = "warning"
reportPropertyTypeMismatch = "none"
reportUninitializedInstanceVariable = "warning"
reportPrivateUsage = "none"
reportUnnecessaryTypeIgnoreComment = "warning"
reportUnnecessaryIsInstance = "warning"
reportUnnecessaryCast = "warning"
reportUnnecessaryComparison = "warning"
reportMissingTypeStubs = "warning"
# these errors are a bit annoying
reportUnknownMemberType = "none"
reportUnknownVariableType = "none"
reportUnknownParameterType = "none"
reportUnknownArgumentType = "none"
reportUnknownLambdaType = "none"
ignore = ["conduit/hydra/**"]

[tool.mypy]
python_version = "3.10"
no_implicit_optional = true
allow_redefinition = true
strict_equality = true
check_untyped_defs = true
warn_unreachable = true
disallow_any_unimported = false
disallow_untyped_defs = true
disallow_incomplete_defs = true
show_error_codes = true
warn_unused_ignores = false
warn_redundant_casts = true
exclude = ["conf.py"]

[[tool.mypy.overrides]]
module = [
    "albumentations.*",
    "flash.*",
    "gdown.*",
    "git.*",
    "pl_bolts.*",
    "requests.*",
    "torchmetrics.*",
    "torchvision.*",
    "typing_inspect.*",
    "wandb.*",
]
ignore_missing_imports = true

[[tool.mypy.overrides]]
module = ["torchmetrics.*"]
follow_imports = "skip"
#follow_imports_for_stubs = true