storage/pyproject.toml at main · LouisDDN/storage · GitHub

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[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "mlpstorage"
version = "2.0.0b1"
description = "MLPerf Storage Benchmark Suite"
readme = "README.md"
authors = [
    {name = "MLCommons Storage Working Group"}
]
requires-python = ">=3.10.0"
dependencies = [
    "psutil>=5.9",
    "pyarrow",
    "pyyaml>=6.0",
    "packaging>=21.0",  # For PEP 440 version parsing in lockfile validation
    "rich>=13.0",  # Progress indication (UX-04)
]

[project.optional-dependencies]
dlio = [
    "dlio-benchmark @ git+https://github.com/wvaske/dlio_benchmark.git@parquet-support",
]
test = [
    "pytest>=7.0",
    "pytest-cov>=4.0",
    "pytest-mock>=3.0",
]
# Full installation with DLIO for running benchmarks.
# Note: DLIO depends on PyTorch. The [tool.uv] configuration ensures
# CPU-only PyTorch wheels are used to avoid GPU dependencies.
full = [
    "dlio-benchmark @ git+https://github.com/wvaske/dlio_benchmark.git@parquet-support",
]

[project.urls]
"Homepage" = "https://github.com/mlcommons/storage"
"Bug Tracker" = "https://github.com/mlcommons/storage/issues"

[tool.setuptools]
packages = {find = {}}

[tool.setuptools.package-data]
"mlpstorage" = ["../configs/dlio/workload/*.yaml"]

[project.scripts]
mlpstorage = 'mlpstorage.main:main'

[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py"]
python_functions = ["test_*"]
addopts = "-v --tb=short --setup-show"
filterwarnings = [
    "ignore::DeprecationWarning",
]

[tool.coverage.run]
source = ["mlpstorage"]
omit = ["*/tests/*", "*/__pycache__/*"]

[tool.coverage.report]
exclude_lines = [
    "pragma: no cover",
    "def __repr__",
    "raise NotImplementedError",
    "if __name__ == .__main__.:",
]

# =============================================================================
# UV Configuration for CPU-only builds
# =============================================================================
# MLPerf Storage is a storage benchmark and does not require GPU support.
# These settings ensure CPU-only PyTorch wheels are used, avoiding large
# CUDA downloads and nvidia-* package dependencies.

[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true

[tool.uv.sources]
torch = [{ index = "pytorch-cpu" }]
torchvision = [{ index = "pytorch-cpu" }]
torchaudio = [{ index = "pytorch-cpu" }]