通过ctypes扩展python组件可能是最简单的python扩展了。
sample.h和sample.c的源码这里不重复了,需要的请参考:
https://blog.csdn.net/tanmx219/article/details/86665706
目录结构是这样的
dev
|__sample.h
|__sample.c
|__Makefile
|__sub01
|__sample.py
|__libsample.so
Makefile
osx:
gcc -shared -undefined dynamic_lookup sample.c -o libsample.so
linux:
gcc -g -Wall -shared -fPIC sample.c -o libsample.so
因为我使用的是Ubuntu18.04,所以直接在dev目录下输入命令
$ make linux
即可得到libsample.so,如果要在sub01目录下使用,则需要把该文件拷贝到sub01目录下去。
sample.py
# sample.py
import ctypes
import os
from ctypes import util, cdll
# .so file is located in the directory above. See Makefile for
# build instructions
#_path = '../libsample.so'
test_path = util.find_library('/home/matthew/dev/libsample.so')
prev_path = ctypes.util.find_library('../libsample.so')
dir_path = os.path.dirname(os.path.realpath(__file__)) + '/libsample.so'
_mod = ctypes.cdll.LoadLibrary(dir_path)
# int gcd(int, int)
gcd = _mod.gcd
gcd.argtypes = (ctypes.c_int, ctypes.c_int)
gcd.restype = ctypes.c_int
# int in_mandel(double, double, int)
in_mandel = _mod.in_mandel
in_mandel.argtypes = (ctypes.c_double, ctypes.c_double, ctypes.c_int)
in_mandel.restype = ctypes.c_int
# int divide(int, int, int *)
_divide = _mod.divide
_divide.argtypes = (ctypes.c_int, ctypes.c_int, ctypes.POINTER(ctypes.c_int))
_divide.restype = ctypes.c_int
def divide(x, y):
rem = ctypes.c_int()
quot = _divide(x,y,rem)
return quot,rem.value
# void avg(double *, int n)
# Define a special type for the 'double *' argument
class DoubleArrayType:
def from_param(self, param):
typename = type(param).__name__
if hasattr(self, 'from_'+typename):
return getattr(self, 'from_'+typename)(param)
elif isinstance(param, ctypes.Array):
return param
else:
raise TypeError("Can't convert %s" % typename)
# Cast from array.array objects
def from_array(self, param):
if param.typecode != 'd':
raise TypeError('must be an array of doubles')
ptr, _ = param.buffer_info()
return ctypes.cast(ptr, ctypes.POINTER(ctypes.c_double))
# Cast from lists/tuples
def from_list(self, param):
val = ((ctypes.c_double)*len(param))(*param)
return val
from_tuple = from_list
# Cast from a numpy array
def from_ndarray(self, param):
return param.ctypes.data_as(ctypes.POINTER(ctypes.c_double))
DoubleArray = DoubleArrayType()
_avg = _mod.avg
_avg.argtypes = (DoubleArray, ctypes.c_int)
_avg.restype = ctypes.c_double
def avg(values):
return _avg(values, len(values))
# struct Point { }
class Point(ctypes.Structure):
_fields_ = [('x', ctypes.c_double),
('y', ctypes.c_double)]
# double distance(Point *, Point *)
distance = _mod.distance
distance.argtypes = (ctypes.POINTER(Point), ctypes.POINTER(Point))
distance.restype = ctypes.c_double
在sub01目录下,就可以这样使用了,
$ python
>>>import sample
>>>print(sample.gcd(35,42))
下面相同,都是测试代码,请自行验证
print( sample.in_mandel(0,0,500))
print( sample.in_mandel(2.0,1.0,500))
print( sample.divide(42,8) )
print( sample.avg([1,2,3]) )
p1 = sample.Point(1,2)
p2 = sample.Point(4,5)
print(p1 )
print(p2 )
print( sample.distance(p1,p2) )
这里要注意,在sample.py中,通过ctypes.cdll加载组件时,我使用了三个路径,如果你的libsample.so在dev目录下,则应该使用prev_path;如果你和我一样,把libsample.so拷贝到了sub01目录下面,那么就可以使用dir_path,
_mod = ctypes.cdll.LoadLibrary(dir_path)
函数的数据类型必须说明,例如
gcd = _mod.gcd #表示最大公约数函数gcd
gcd.argtypes = (ctypes.c_int, ctypes.c_int) #gcd 输入函数的数据类型
gcd.restype = ctypes.c_int #gcd 输出函数的数据类型