# Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. ALL RIGHTS RESERVED.
#
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception

[build-system]
# cmake>=3.30 is needed for FindCUDAToolkit's CUDA::nvfatbin /
# CUDA::nvfatbin_static imported targets, which the v2 (HostJIT) backend links
# against. Listed here so isolated builds (pip's default) pick it up.
requires = ["scikit-build-core>=0.10", "setuptools_scm", "cython>=3.1.0", "cmake>=3.30"]
build-backend = "scikit_build_core.build"

[project]
name = "cuda-cccl"
description = "CUDA Core Compute Libraries for Python"
authors = [{ name = "NVIDIA Corporation" }]
classifiers = [
  "Development Status :: 4 - Beta",
  "Intended Audience :: Developers",
  "Topic :: Software Development :: Libraries :: Python Modules",
  "Programming Language :: Python :: 3 :: Only",
  "Programming Language :: Python :: 3.10",
  "Programming Language :: Python :: 3.11",
  "Programming Language :: Python :: 3.12",
  "Programming Language :: Python :: 3.13",
  "Programming Language :: Python :: 3.14",
  "Environment :: GPU :: NVIDIA CUDA",
  "License :: OSI Approved :: Apache Software License",
  "Operating System :: POSIX :: Linux",
  "Operating System :: Microsoft :: Windows",
]
requires-python = ">=3.10"

dependencies = [
  "numpy",
  "cuda-pathfinder>=1.2.3",
  "cuda-core",
  "typing_extensions",
]

dynamic = ["version"]
readme = { file = "README.md", content-type = "text/markdown" }

[project.optional-dependencies]
minimal-cu12 = [
  "cuda-bindings>=12.9.1,<13.0.0",
  "cuda-toolkit[nvrtc,nvjitlink,cudart,nvcc]==12.*",
]
minimal-cu13 = [
  "cuda-bindings>=13.0.0,<14.0.0",
  "cuda-toolkit[nvrtc,nvjitlink,cudart,nvcc,nvvm]==13.*",
]
# sysctk variants: like cu12/cu13 but without cuda-toolkit — the user is
# responsible for providing a compatible CUDA toolkit
minimal-sysctk12 = [
  "cuda-bindings>=12.9.1,<13.0.0",
]
minimal-sysctk13 = [
  "cuda-bindings>=13.0.0,<14.0.0",
]
cu12 = [
  "cuda-cccl[minimal-cu12]",
  # numba-cuda currently expects numba.cuda.types.NPDatetime, removed in numba 0.66.
  "numba>=0.60.0,<0.66",
  "numba-cuda[cu12]>=0.23.0,!=0.27.*,!=0.28.*,!=0.29.*,!=0.30.0",
]
cu13 = [
  "cuda-cccl[minimal-cu13]",
  # numba-cuda currently expects numba.cuda.types.NPDatetime, removed in numba 0.66.
  "numba>=0.60.0,<0.66",
  "numba-cuda[cu13]>=0.23.0,!=0.27.*,!=0.28.*,!=0.29.*,!=0.30.0"
]
sysctk12 = [
  "cuda-cccl[minimal-sysctk12]",
  # numba-cuda currently expects numba.cuda.types.NPDatetime, removed in numba 0.66.
  "numba>=0.60.0,<0.66",
  # plain numba-cuda (no [cu12]) so it relies on the system-provided CUDA toolkit
  # instead of pulling the toolkit from pip -- the whole point of the sysctk extra.
  "numba-cuda>=0.23.0,!=0.27.*,!=0.28.*,!=0.29.*,!=0.30.0"
]
sysctk13 = [
  "cuda-cccl[minimal-sysctk13]",
  # numba-cuda currently expects numba.cuda.types.NPDatetime, removed in numba 0.66.
  "numba>=0.60.0,<0.66",
  # plain numba-cuda (no [cu13]) so it relies on the system-provided CUDA toolkit
  # instead of pulling the toolkit from pip -- the whole point of the sysctk extra.
  "numba-cuda>=0.23.0,!=0.27.*,!=0.28.*,!=0.29.*,!=0.30.0",
]
# The test extras do not include CuPy. The cuda.compute examples (run via
# tests/test_examples.py) require it; install it separately (e.g.
# `pip install cupy-cuda13x`).
test-cu12 = [
  # an undocumented way to inherit the dependencies of the cu12 extra.
  # GH pypa #11296
  "cuda-cccl[cu12]",
  "pytest",
  "pytest-xdist",
]
test-cu13 = ["cuda-cccl[cu13]", "pytest", "pytest-xdist"]
test-sysctk12 = [
  "cuda-cccl[sysctk12]",
  "pytest",
  "pytest-xdist",
]
test-sysctk13 = [
  "cuda-cccl[sysctk13]",
  "pytest",
  "pytest-xdist",
]
bench-cu12 = [
  "cuda-cccl[cu12]",
  "cuda-bench[cu12]",
  "cupy-cuda12x",
  "pytest-benchmark",
]
bench-cu13 = [
  "cuda-cccl[cu13]",
  "cuda-bench[cu13]",
  "cupy-cuda13x",
  "pytest-benchmark",
]
bench-sysctk12 = [
  "cuda-cccl[sysctk12]",
  "cuda-bench[cu12]",
  "cupy-cuda12x",
  "pytest-benchmark",
]
bench-sysctk13 = [
  "cuda-cccl[sysctk13]",
  "cuda-bench[cu13]",
  "cupy-cuda13x",
  "pytest-benchmark",
]

[project.urls]
Homepage = "https://github.com/NVIDIA/cccl"
Repository = "https://github.com/NVIDIA/cccl"
Documentation = "https://nvidia.github.io/cccl"
Issues = "https://github.com/NVIDIA/cccl/issues"

[tool.scikit-build]
minimum-version = "build-system.requires"
build-dir = "build/{wheel_tag}"

[tool.scikit-build.cmake]
version = ">=3.30"
args = []
build-type = "Release"
source-dir = "."

[tool.scikit-build.ninja]
version = ">=1.11"
make-fallback = true

[tool.scikit-build.metadata.version]
provider = "scikit_build_core.metadata.setuptools_scm"

[tool.setuptools_scm]
root = "../.."
git_describe_command = ["git", "describe", "--tags", "--match", "v[0-9]*"]


[tool.scikit-build.wheel.packages]
"cuda" = "cuda"

[tool.mypy]
cache_dir = "../../.cache/mypy"
python_version = "3.10"

[[tool.mypy.overrides]]
module = [
  # numpy>=2.3 stubs use PEP 695 syntax that mypy can't parse under
  # python_version=3.10; skip following its imports to keep the 3.10 target.
  "numpy",
  "numpy.*",
  "numba.*",
  "llvmlite.*",
  "cuda.cccl.*",
  "cuda.bindings.*",
  "cuda.core.*",
  "cuda.pathfinder.*",
]
ignore_missing_imports = true
follow_imports = "skip"

[tool.ruff]
extend = "../../pyproject.toml"

[tool.ruff.lint.isort]
known-first-party = [
  "cuda.cccl",
  "cuda.cccl.headers",
  "cuda.compute",
]

[tool.pytest.ini_options]
# Make shared helpers in tests/_utils importable when pytest runs outside tests/.
pythonpath = ["tests"]
markers = [
  "no_verify_sass: skip SASS verification check",
  "large: tests requiring large device memory allocations",
  "no_numba: tests that should not import numba or numba.cuda",
  "free_threading: tests requiring free-threaded CPython with the GIL disabled",
  "serialization: serialize/deserialize tests (skipped on the v2 HostJIT backend)",
]