通过 `scikit-build` 使用#

scikit-build 提供了两个独立的概念,旨在面向 Python 扩展模块的用户.

一个 setuptools 替换（传统行为）
一系列 cmake 模块,带有帮助构建 Python 扩展的定义

备注

可以使用 scikit-build 的 cmake 模块来完全绕过 cmake 设置机制 ,并编写调用 f2py -c 的目标.由于这些构建系统文档的目的是远离内部的 numpy.distutils 方法,因此**不推荐**这种用法.

在不需要或不想要 setuptools 替代方案的情况下（即如果不需要 wheels ）,建议改为使用通过 cmake 使用中描述的原始 cmake 设置.

斐波那契演练 (F77)#

我们将考虑来自三种包裹方式 - 入门部分的 fib 示例.

C FILE: FIB1.F
      SUBROUTINE FIB(A,N)
C
C     CALCULATE FIRST N FIBONACCI NUMBERS
C
      INTEGER N
      REAL*8 A(N)
      DO I=1,N
         IF (I.EQ.1) THEN
            A(I) = 0.0D0
         ELSEIF (I.EQ.2) THEN
            A(I) = 1.0D0
         ELSE 
            A(I) = A(I-1) + A(I-2)
         ENDIF
      ENDDO
      END
C END FILE FIB1.F

`CMake` 模块仅#

考虑使用以下 CMakeLists.txt.

### setup project ###
cmake_minimum_required(VERSION 3.9)

project(fibby
  VERSION 1.0
  DESCRIPTION "FIB module"
  LANGUAGES C Fortran
  )

# Safety net
if(PROJECT_SOURCE_DIR STREQUAL PROJECT_BINARY_DIR)
  message(
    FATAL_ERROR
      "In-source builds not allowed. Please make a new directory (called a build directory) and run CMake from there.\n"
  )
endif()

# Ensure scikit-build modules
if (NOT SKBUILD)
  find_package(PythonInterp 3.8 REQUIRED)
  # Kanged --> https://github.com/Kitware/torch_liberator/blob/master/CMakeLists.txt
  # If skbuild is not the driver; include its utilities in CMAKE_MODULE_PATH
  execute_process(
    COMMAND "${PYTHON_EXECUTABLE}"
    -c "import os, skbuild; print(os.path.dirname(skbuild.__file__))"
    OUTPUT_VARIABLE SKBLD_DIR
    OUTPUT_STRIP_TRAILING_WHITESPACE
  )
  list(APPEND CMAKE_MODULE_PATH "${SKBLD_DIR}/resources/cmake")
  message(STATUS "Looking in ${SKBLD_DIR}/resources/cmake for CMake modules")
endif()

# scikit-build style includes
find_package(PythonExtensions REQUIRED) # for ${PYTHON_EXTENSION_MODULE_SUFFIX}

# Grab the variables from a local Python installation
# NumPy headers
execute_process(
  COMMAND "${PYTHON_EXECUTABLE}"
  -c "import numpy; print(numpy.get_include())"
  OUTPUT_VARIABLE NumPy_INCLUDE_DIRS
  OUTPUT_STRIP_TRAILING_WHITESPACE
)
# F2PY headers
execute_process(
  COMMAND "${PYTHON_EXECUTABLE}"
  -c "import numpy.f2py; print(numpy.f2py.get_include())"
  OUTPUT_VARIABLE F2PY_INCLUDE_DIR
  OUTPUT_STRIP_TRAILING_WHITESPACE
)

# Prepping the module
set(f2py_module_name "fibby")
set(fortran_src_file "${CMAKE_SOURCE_DIR}/fib1.f")
set(f2py_module_c "${f2py_module_name}module.c")

# Target for enforcing dependencies
add_custom_target(genpyf
  DEPENDS "${fortran_src_file}"
)
add_custom_command(
  OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/${f2py_module_c}"
  COMMAND ${PYTHON_EXECUTABLE}  -m "numpy.f2py"
                   "${fortran_src_file}"
                   -m "fibby"
                   --lower # Important
  DEPENDS fib1.f # Fortran source
)

add_library(${CMAKE_PROJECT_NAME} MODULE
            "${f2py_module_name}module.c"
            "${F2PY_INCLUDE_DIR}/fortranobject.c"
            "${fortran_src_file}")

target_include_directories(${CMAKE_PROJECT_NAME} PUBLIC
                           ${F2PY_INCLUDE_DIR}
                           ${NumPy_INCLUDE_DIRS}
                           ${PYTHON_INCLUDE_DIRS})
set_target_properties(${CMAKE_PROJECT_NAME} PROPERTIES SUFFIX "${PYTHON_EXTENSION_MODULE_SUFFIX}")
set_target_properties(${CMAKE_PROJECT_NAME} PROPERTIES PREFIX "")

# Linker fixes
if (UNIX)
  if (APPLE)
    set_target_properties(${CMAKE_PROJECT_NAME} PROPERTIES
    LINK_FLAGS  '-Wl,-dylib,-undefined,dynamic_lookup')
  else()
    set_target_properties(${CMAKE_PROJECT_NAME} PROPERTIES
  LINK_FLAGS  '-Wl,--allow-shlib-undefined')
  endif()
endif()

add_dependencies(${CMAKE_PROJECT_NAME} genpyf)

install(TARGETS ${CMAKE_PROJECT_NAME} DESTINATION fibby)

大部分逻辑与通过 cmake 使用相同,但值得注意的是,这里通过 sysconfig.get_config_var("SO") 生成了适当的模块后缀.生成的扩展可以在标准工作流程中构建和加载.

ls .
# CMakeLists.txt fib1.f
cmake -S . -B build
cmake --build build
cd build
python -c "import numpy as np; import fibby; a = np.zeros(9); fibby.fib(a); print (a)"
# [ 0.  1.  1.  2.  3.  5.  8. 13. 21.]

`setuptools` 替换#

备注

截至2021年11月

这里描述的驱动 cmake 模块构建的行为被认为是遗留行为,不应依赖于此.

scikit-build 的实用性在于能够驱动生成不仅仅是扩展模块,特别是常见的使用模式是生成 Python 可分发包（例如用于 PyPI）.

使用 scikit-build 的工作流程直接支持这些打包需求.考虑按照定义的方式为项目添加一个 setup.py:

from skbuild import setup

setup(
    name="fibby",
    version="0.0.1",
    description="a minimal example package (fortran version)",
    license="MIT",
    packages=['fibby'],
    python_requires=">=3.7",
)

与相应的 pyproject.toml 一起

[build-system]
requires = ["setuptools>=42", "wheel", "scikit-build", "cmake>=3.9", "numpy>=1.21"]
build-backend = "setuptools.build_meta"

这些一起可以使用 cmake 与其他标准的 setuptools 输出一起构建扩展.通过 setup.py 运行 cmake 主要用于需要与未使用 cmake 构建的扩展模块集成时.

ls .
# CMakeLists.txt fib1.f pyproject.toml setup.py
python setup.py build_ext --inplace
python -c "import numpy as np; import fibby.fibby; a = np.zeros(9); fibby.fibby.fib(a); print (a)"
# [ 0.  1.  1.  2.  3.  5.  8. 13. 21.]

我们已经修改了模块的路径,因为 --inplace 将扩展模块放置在子文件夹中.

通过 scikit-build 使用#

斐波那契演练 (F77)#

CMake 模块仅#

setuptools 替换#

通过 `scikit-build` 使用#

`CMake` 模块仅#

`setuptools` 替换#