python 中使用c++ lib

参考:
https://zhuanlan.zhihu.com/p/20152309
https://pgi-jcns.fz-juelich.de/portal/pages/using-c-from-python.html

eg:
1.
*.h
extern "C" int  __attribute__((visibility("default"))) NLibMEx(int argc, char *argv[])

lib_test.py

#-*- encoding:utf8 -*-
#!/usr/bin/python

#from ctypes import *
import sys
from ctypes import *
import ctypes
import time

if __name__ =="__main__":
    print "*** " * 20
    so = ctypes.CDLL("libNLibMEx.so")
    so.NexusLibMainEntry.argtypes = (ctypes.c_int, ctypes.POINTER(ctypes.c_char_p))
    print "*** " * 20
    print "len(sys.argv) "+ str( len(sys.argv))

    print "sys.argv "+str( sys.argv)

    num_numbers = len(sys.argv)
    array_type = ctypes.c_char_p * num_numbers
    print array_type
    so.NLibMEx(ctypes.c_int(num_numbers), array_type(*sys.argv))
    while 1:
        time.sleep(1)

$ python py_lib.py -cfg=a.cfg -help
[popexizhi:
这里是把python的argv转回给c使用了:)
相关参考

]

2.

Basics

This is a short tutorial on using C from Python with the help of a ctypes wrapper module. Let's say we have a small C library for calculating sums and want to use it in Python.

sum.c:

int our_function(int num_numbers, int *numbers) {
    int i;
    int sum;
    for (i = 0; i < num_numbers; i++) {
        sum += numbers[i];
    }
    return sum;
}

Compile it:

cc -fPIC -shared -o libsum.so sum.c

Now to the main part, first the complete listing and then a line by line explanation: sum.py:

import ctypes

_sum = ctypes.CDLL('libsum.so')
_sum.our_function.argtypes = (ctypes.c_int, ctypes.POINTER(ctypes.c_int))

def our_function(numbers):
    global _sum
    num_numbers = len(numbers)
    array_type = ctypes.c_int * num_numbers
    result = _sum.our_function(ctypes.c_int(num_numbers), array_type(*numbers))
    return int(result)

We import the ctypes module in the first line, then the shared library is loaded (usually you would want to include a check for the operating system here and name a dll instead, if running on windows). It is stored in the variable _sum and the functions in this library can be accessed as members (e.g. _sum.our_functions). In the next line, we set the argument types for the function. The function ctypes.POINTER creates a pointer datatype, so ctypes.POINTER(ctypes.c_int) is the ctypes datatype for int *. When using the functions, ctypes will check if the arguments fit to these types.

The real function definition follows in the next lines. We don't need the num_numbers argument as the length of Python sequences can be queried. This is the first thing we do in the function (after quickly stating that _sum is global to help the interpreter find it). Next, we need to define a ctypes array type, which is binary compatible to what the library expects. This can be done by 'multiplying' the type ctypes.c_int with an integer. To create an array with this type, we use:

array_type(*numbers)

The type expects each array element as an argument, so we use the asterisk notation with numbers. The result has the type ctypes.c_int and we want to return a python integer, therefore int(result) is returned.

[popexizhi：

1.array_type = ctypes.c_int * num_numbers 是py中的数组参数指针位置

2._sum.our_function(ctypes.c_int(num_numbers), array_type(*numbers))

这里的array_type(*numbers) 一定要使用指针方式，是在为int *numbers做地址位置，这里步骤1中应该就已经是c的转换了，看来python对c的写法还是和包容的:)

]

Using this wrapper module is quite straight-forward:

import sum
print sum.our_function([1,2,-3,4,-5,6])