ccc-gpu/pyproject.toml at main · pivlab/ccc-gpu · GitHub

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[build-system]
requires = [
    "scikit-build-core",
    "pybind11>=2.11.0",
    "cmake>=4.0",
    "ninja",
    "setuptools",
    "wheel",
]
build-backend = "scikit_build_core.build"

[project]
name = "cccgpu"
version = "0.2.4"
description = "The Clustermatch Correlation Coefficient (CCC) with GPU acceleration"
readme = "README.md"
requires-python = ">=3.10"
license = { text = "BSD-2-Clause Plus Patent" }
authors = [
    { name = "Milton Pividori", email = "milton.pividori@cuanschutz.edu" },
    { name = "Haoyu Zhang", email = "haoyu_z@outlook.com" },
]
dependencies = ["numpy", "scipy", "numba", "pandas", "scikit-learn"]
classifiers = [
    "Programming Language :: Python :: 3",
    "License :: OSI Approved :: BSD License",
    "Operating System :: OS Independent",
    "Development Status :: 5 - Production/Stable",
    "Environment :: Console",
]

[project.urls]
Homepage = "https://github.com/pivlab/ccc-gpu"
Issues = "https://github.com/pivlab/ccc-gpu/issues"

[project.optional-dependencies]
test = ["pytest", "pytest-cov"]

[tool.scikit-build]
# Configure scikit-build-core
cmake.version = ">=4.0"
cmake.args = [
    "-DCMAKE_CUDA_ARCHITECTURES=75", # Adjust for your target CUDA architecture
]
build.verbose = true
wheel.packages = ["libs/ccc"] # Directory containing your Python packages
wheel.exclude = ["*.cpp", "*.h"] # Exclude C++ headers from wheel
# Note: wheel.py-api removed to support multiple Python versions (3.10-3.15)
wheel.platlib = true # Contains compiled extensions

[tool.pytest.ini_options]
minversion = "6.0"
addopts = "-ra -q"
testpaths = ["tests"]

[tool.cibuildwheel]
build = "cp3{10,11,12,13,14}-manylinux_x86_64"
manylinux-x86_64-image = "manylinux_2_28"

[tool.cibuildwheel.linux]
# Install CUDA toolkit before building wheels[tool.cibuildwheel.linux]
before-all = [
    # Install yum-utils to get yum-config-manager
    "yum install -y yum-utils",
    # Add NVIDIA CUDA repository for RHEL 8 (manylinux_2_28 is based on AlmaLinux 8)
    "yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo",
    # Clean yum cache
    "yum clean all",
    # Install GCC 13 toolset (provides GCC 13.2 under /opt/rh/gcc-toolset-13)
    "yum install -y gcc-toolset-13",
    # Install CUDA 12.9 toolkit (supports GCC 6.x - 15.x, compatible with GCC 14 in manylinux_2_28)
    "yum install -y cuda-toolkit-12-5",
    # Print nvcc version with green prefix
    "echo -e '\\033[32m[cccgpu-info]:\\033[0m'",
    "nvcc --version",
    # Print gcc version with green prefix
    "echo -e '\\033[32m[cccgpu-info]:\\033[0m'",
    "/opt/rh/gcc-toolset-13/root/usr/bin/gcc --version",
]

# Set CUDA and GCC 13 environment variables (prefer gcc-toolset-13 in PATH)
environment = { CUDA_HOME = "/usr/local/cuda", CUDACXX = "/usr/local/cuda/bin/nvcc", CC = "/opt/rh/gcc-toolset-13/root/usr/bin/gcc", CXX = "/opt/rh/gcc-toolset-13/root/usr/bin/g++", CUDAHOSTCXX = "/opt/rh/gcc-toolset-13/root/usr/bin/g++", CMAKE_C_COMPILER = "/opt/rh/gcc-toolset-13/root/usr/bin/gcc", CMAKE_CXX_COMPILER = "/opt/rh/gcc-toolset-13/root/usr/bin/g++", PATH = "/opt/rh/gcc-toolset-13/root/usr/bin:/usr/local/cuda/bin:$PATH", LD_LIBRARY_PATH = "/usr/local/cuda/lib64:/opt/rh/gcc-toolset-13/root/usr/lib64:$LD_LIBRARY_PATH" }

# Set CUDA environment variables
# environment = { CUDA_HOME="/usr/local/cuda-12.6", PATH="/usr/local/cuda-12.6/bin:$PATH", LD_LIBRARY_PATH="/usr/local/cuda-12.6/lib64:$LD_LIBRARY_PATH" }

# Test the built wheels (optional, can be disabled)
# test-requires = ["pytest", "numpy", "scipy"]
# test-command = "pytest {project}/tests -v"