用cython简单包装C代码

Question

我有很多C函数,我想从python中调用它们.cython似乎是要走的路,但我无法真正找到一个如何做到这一点的例子.我的C函数看起来像这样:

void calculate_daily ( char *db_name, int grid_id, int year,
                       double *dtmp, double *dtmn, double *dtmx, 
                       double *dprec, double *ddtr, double *dayl, 
                       double *dpet, double *dpar ) ;

我想要做的就是指定前三个参数(一个字符串和两个整数),并恢复8个numpy数组(或python列表.所有双数组都有N个元素).我的代码假设指针指向已经分配的内存块.此外,生成的C代码应该链接到一些外部库.

Answer 1

这是一个很小但完整的例子,将numpy数组传递给外部C函数,逻辑上

fc( int N, double* a, double* b, double* z )  # z = a + b

使用Cython.(对于那些了解它的人来说,这肯定是众所周知的.欢迎提出意见.最后修改:2011年2月23日,Cython 0.14.)

首先阅读或浏览 Cython构建 和使用NumPy进行Cython.

2个步骤:

• python f-setup.py build_ext --inplace
  接通f.pyx和fc.cpp- > f.so中,动态库
• python test-f.py
import f负载f.so; f.fpy( ... )调用C fc( ... ).

python f-setup.py用于distutils运行cython,编译和链接:
cython f.pyx -> f.cpp
compile f.cpp和fc.cpp
link f.o fc.o- > f.so,一个python import f将加载的动态库.

对于学生,我建议:制作这些步骤的图表,查看下面的文件,然后下载并运行它们.

(distutils是一个巨大的,错综复杂的包,用于制作Python包以进行分发,并安装它们.这里我们只使用它的一小部分来编译和链接f.so.这一步与Cython无关,但它可能令人困惑; .pyx中的简单错误可能导致来自g ++编译和链接的错误错误消息页面.另请参阅 distutils doc 和/或 有关distutils的SO问题.)

比如make,setup.py将重新运行 cython f.pyx,g++ -c ... f.cpp 如果f.pyx比新的更新f.cpp.
要清理,rm -r build/.

另一种方法setup.py是在脚本或Makefile中单独运行步骤:
cython --cplus f.pyx -> f.cpp # see cython -h
g++ -c ... f.cpp -> f.o
g++ -c ... fc.cpp -> fc.o
cc-lib f.o fc.o -> dynamic library f.so.
修改cc-lib-mac你的平台和安装下面的包装器:它不漂亮,但很小.

有关Cython包装C的真实示例,请查看几乎任何SciKit中的 .pyx文件 .

另请参阅: NumPy用户的Cython 和SO问题/标记/ cython.

要解压缩以下文件,请将批次剪切粘贴到一个大文件中cython-numpy-c-demo,然后在Unix(在干净的新目录中)运行sh cython-numpy-c-demo.

#--------------------------------------------------------------------------------
cat >f.pyx <<\!
# f.pyx: numpy arrays -> extern from "fc.h"
# 3 steps:
# cython f.pyx  -> f.c
# link: python f-setup.py build_ext --inplace  -> f.so, a dynamic library
# py test-f.py: import f gets f.so, f.fpy below calls fc()

import numpy as np
cimport numpy as np

cdef extern from "fc.h": 
    int fc( int N, double* a, double* b, double* z )  # z = a + b

def fpy( N,
    np.ndarray[np.double_t,ndim=1] A,
    np.ndarray[np.double_t,ndim=1] B,
    np.ndarray[np.double_t,ndim=1] Z ):
    """ wrap np arrays to fc( a.data ... ) """
    assert N <= len(A) == len(B) == len(Z)
    fcret = fc( N, <double*> A.data, <double*> B.data, <double*> Z.data )
        # fcret = fc( N, A.data, B.data, Z.data )  grr char*
    return fcret

!

#--------------------------------------------------------------------------------
cat >fc.h <<\!
// fc.h: numpy arrays from cython , double*

int fc( int N, const double a[], const double b[], double z[] );
!

#--------------------------------------------------------------------------------
cat >fc.cpp <<\!
// fc.cpp: z = a + b, numpy arrays from cython

#include "fc.h"
#include <stdio.h>

int fc( int N, const double a[], const double b[], double z[] )
{
    printf( "fc: N=%d a[0]=%f b[0]=%f \n", N, a[0], b[0] );
    for( int j = 0;  j < N;  j ++ ){
        z[j] = a[j] + b[j];
    }
    return N;
}
!

#--------------------------------------------------------------------------------
cat >f-setup.py <<\!
# python f-setup.py build_ext --inplace
#   cython f.pyx -> f.cpp
#   g++ -c f.cpp -> f.o
#   g++ -c fc.cpp -> fc.o
#   link f.o fc.o -> f.so

# distutils uses the Makefile distutils.sysconfig.get_makefile_filename()
# for compiling and linking: a sea of options.

# http://docs.python.org/distutils/introduction.html
# http://docs.python.org/distutils/apiref.html  20 pages ...
# https://stackoverflow.com/questions/tagged/distutils+python

import numpy
from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
# from Cython.Build import cythonize

ext_modules = [Extension(
    name="f",
    sources=["f.pyx", "fc.cpp"],
        # extra_objects=["fc.o"],  # if you compile fc.cpp separately
    include_dirs = [numpy.get_include()],  # .../site-packages/numpy/core/include
    language="c++",
        # libraries=
        # extra_compile_args = "...".split(),
        # extra_link_args = "...".split()
    )]

setup(
    name = 'f',
    cmdclass = {'build_ext': build_ext},
    ext_modules = ext_modules,
        # ext_modules = cythonize(ext_modules)  ? not in 0.14.1
    # version=
    # description=
    # author=
    # author_email=
    )

# test: import f
!

#--------------------------------------------------------------------------------
cat >test-f.py <<\!
#!/usr/bin/env python
# test-f.py

import numpy as np
import f  # loads f.so from cc-lib: f.pyx -> f.c + fc.o -> f.so

N = 3
a = np.arange( N, dtype=np.float64 )
b = np.arange( N, dtype=np.float64 )
z = np.ones( N, dtype=np.float64 ) * np.NaN

fret = f.fpy( N, a, b, z )
print "fpy -> fc z:", z

!

#--------------------------------------------------------------------------------
cat >cc-lib-mac <<\!
#!/bin/sh
me=${0##*/}
case $1 in
"" )
    set --  f.cpp fc.cpp ;;  # default: g++ these
-h* | --h* )
    echo "
$me [g++ flags] xx.c yy.cpp zz.o ...
    compiles .c .cpp .o files to a dynamic lib xx.so
"
    exit 1
esac

# Logically this is simple, compile and link,
# but platform-dependent, layers upon layers, gloom, doom

base=${1%.c*}
base=${base%.o}
set -x

g++ -dynamic -arch ppc \
    -bundle -undefined dynamic_lookup \
    -fno-strict-aliasing -fPIC -fno-common -DNDEBUG `# -g` -fwrapv \
    -isysroot /Developer/SDKs/MacOSX10.4u.sdk \
    -I/Library/Frameworks/Python.framework/Versions/2.6/include/python2.6 \
    -I${Pysite?}/numpy/core/include \
    -O2 -Wall \
    "$@" \
    -o $base.so

# undefs: nm -gpv $base.so | egrep '^ *U _+[^P]'
!

# 23 Feb 2011 13:38

Answer 2

来自http://article.gmane.org/gmane.comp.python.cython.user/5625的以下Cython代码 不需要显式强制转换,也可以处理非连续数组:

def fpy(A):
    cdef np.ndarray[np.double_t, ndim=2, mode="c"] A_c
    A_c = np.ascontiguousarray(A, dtype=np.double)
    fc(&A_c[0,0])