skala/pyproject.toml at main · microsoft/skala · GitHub

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[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"

[project]
name = "skala"
version = "2026.8"
description = "Skala Exchange Correlation Functional"
authors = []
license-files = ["LICENSE.txt"]
readme = "README.md"
keywords = []
classifiers = [
    "Programming Language :: Python :: 3",
    "Development Status :: 5 - Production/Stable",
]
requires-python = ">=3.10"
dependencies = [
    "ase",
    "azure-core",
    "azure-identity",
    "dftd3",
    "e3nn",
    "huggingface_hub",
    "numpy",
    "opt_einsum_fx",
    "pyscf>=2.8,<2.14",
    "qcelemental",
    "torch"
]

optional-dependencies.dev = [
    "pre-commit",
    "mypy",
    "pytest",
    "pytest-cov",
    "pytest-randomly",
]
optional-dependencies.doc = [
    "ipywidgets",
    "myst-nb",
    "sphinx",
    "sphinx-book-theme",
    "sphinx-design",
    "sphinxcontrib-bibtex",
    "sphinxcontrib-moderncmakedomain",
    "sphinx-fortran",
]

urls.repository = "https://github.com/microsoft/skala"
urls.documentation = "https://microsoft.github.io/skala"
urls.homepage = "https://aka.ms/dft"

[tool.mypy]
strict = true
ignore_missing_imports = true
no_namespace_packages = true
python_version = "3.12"
exclude = ["third_party/"]
disable_error_code = ["no-any-return"]

# torch.autograd.Function uses dynamic attributes on FunctionCtx (ctx.save_for_backward pattern)
# and Function.apply() is untyped. These are fundamental to PyTorch's autograd API.
[[tool.mypy.overrides]]
module = "skala.pyscf.features"
disable_error_code = ["no-any-return", "attr-defined", "no-untyped-call"]

[tool.ruff]
target-version = "py311"
src = ["src"]
exclude = ["third_party"]

[tool.ruff.lint]
extend-select = [
  "B", # flake8-bugbear
  "D417", # undocumented-param in docstring
  "I", # isort
  "UP", # pyupgrade
]
extend-ignore = [
  "UP015", # redundant-open-modes
  "E741", # variable name l
]

[tool.ruff.lint.per-file-ignores]
# E402: imports must come after CUDA checks and CuPy allocator configuration
"src/skala/gpu4pyscf/__init__.py" = ["E402"]
"src/skala/gpu4pyscf/dft.py" = ["E402"]

[tool.ruff.lint.isort]
detect-same-package = true

[tool.black]
line-length = 100

[tool.pytest.ini_options]
filterwarnings = [
    "error",
    # PyTorch 2.11 deprecated `torch.jit.load`; Skala's pretrained checkpoints
    # are TorchScript archives, so `skala.functional.load` still uses it.
    'ignore:`torch\.jit\.load` is deprecated\. Please switch to `torch\.export`\.:DeprecationWarning',
    'ignore:`torch\.jit\.script` is deprecated\. Please switch to `torch\.compile` or `torch\.export`\.:DeprecationWarning',
    'ignore:`torch\.jit\.save` is deprecated\. Please switch to `torch\.export`\.:DeprecationWarning',
    'ignore:`torch\.jit\.save` is not supported in Python 3\.14+ and may break\. Please switch to `torch\.export`\.:DeprecationWarning',
    # PySCF's `SCF.__init__` (pyscf/scf/hf.py, currently line 1733) creates
    # `self._chkfile = tempfile.NamedTemporaryFile(...)` as its checkpoint file
    # and relies on finalization to close it, which emits ResourceWarning during
    # GC. The warning is emitted by CPython's I/O layer (not from the pyscf
    # module), so we match on the message. Traced via PYTHONTRACEMALLOC.
    "ignore:unclosed file <_io\\.FileIO name='/tmp/tmp.*' mode='rb\\+' closefd=True>:ResourceWarning",
    # On recent pytest versions the same leaked tempfile surfaces during GC at
    # session teardown via the unraisable-exception hook, which re-emits it as
    # `pytest.PytestUnraisableExceptionWarning`. Filter that wrapper too.
    "ignore:Exception ignored in. <_io\\.FileIO name='/tmp/tmp.*' mode='rb\\+' closefd=True>:pytest.PytestUnraisableExceptionWarning",
    # From gpu4pyscf if cutensor is not available
    'ignore:using cupy as the tensor contraction engine\.:UserWarning',
    # Deprecation warning in huggingface_hub package
    'ignore:hf_xet\.download_files\(\) is deprecated\. Use XetSession\(\)\.new_file_download_group\(\)\.start_download_file\(\) instead\.:DeprecationWarning',
    # Upstream deprecations in PySCF / GPU4PySCF are outside this project's control.
    'ignore::DeprecationWarning:pyscf\..*',
    'ignore::DeprecationWarning:gpu4pyscf\..*',
]