使用ctypes在Python中调用C++动态库
入门操作
使用ctypes库可以直接调用C语言编写的动态库，而如果是调用C++编写的动态库，需要使用extern关键字对动态库的函数进行声明：
#include <iostream>
using namespace std;
extern "C" {
void greet() {
cout << "hello python" << endl;
}
}
将上述的C++程序编译成动态链接库：
g++ hello.cpp -fPIC -shared -o hello.so
在Python代码中使用ctypes导入动态库，调用函数：
# -*- coding: utf-8 -*- #
from ctypes import CDLL
hello = CDLL('./hello.so')
if __name__ == '__main__':
hello.greet()
运行上述Python程序：
xujijun@pc:~/codespace/python$ python3 hello.py
hello python
参数传递
编写一个整数加法函数
#include <iostream>
using namespace std;
extern "C" {
int add(int a, int b) {
return a + b;
}
}
编译得到动态库，在Python代码中调用：
# -*- coding: utf-8 -*- #
from ctypes import CDLL
hello = CDLL('./hello.so')
if __name__ == '__main__':
a = input('input num1: ')
b = input('input num2: ')
print('output: %d' % hello.add(int(a), int(b)))
运行上述代码，得到输出：
xujijun@pc:~/codespace/python$ python3 hello.py
input num1: 12
input num2: 34
output: 46
尝试传递字符串参数
#include <iostream>
#include <cstdio>
using namespace std;
extern "C" {
void print_name(const char* name) {
printf("%s\n", name);
}
}
Python代码调用：
# -*- coding: utf-8 -*- #
from ctypes import CDLL
hello = CDLL('./hello.so')
if __name__ == '__main__':
name = input('input name: ')
hello.print_name(name.encode('utf-8')) # 此处需要将Python中的字符串按照utf8编码成bytes
查看输出：
xujijun@pc:~/codespace/python$ python3 hello.py
input name: yanhewu
yanhewu
面向对象
使用C++编写动态链接库我们肯定会想到如何在Python中调用C++的类，由于ctypes只能调用C语言函数（C++中采用extern "C"声明的函数），我们需要对接口进行一定的处理：
C++代码示例
#include <iostream>
#include <cstdio>
#include <string>
using namespace std;
class Student {
private:
string name;
public:
Student(const char* n);
void PrintName();
};
Student::Student(const char* n) {
this->name.assign(n);
}
void Student::PrintName() {
cout << "My name is " << this->name << endl;
}
extern "C" {
Student* new_student(const char* name) {
return new Student(name);
}
void print_student_name(Student* stu) {
stu->PrintName();
}
}
Python代码中调用：
# -*- coding: utf-8 -*- #
from ctypes import CDLL
hello = CDLL('./hello.so')
class Student(object):
def __init__(self, name):
self.stu = hello.new_student(name.encode('utf-8'))
def print_name(self):
hello.print_student_name(self.stu)
if __name__ == '__main__':
name = input('input student name: ')
s = Student(name)
s.print_name()
输出：
xujijun@pc:~/codespace/python$ python3 hello.py
input student name: yanhewu
My name is yanhewu
内存泄漏？
上一部分我们我们尝试了如何使用ctypes调用带有类的C++动态库，这里我们不禁会想到一个问题，我们在动态库中使用new动态申请的内存是否会被Python的GC清理呢？这里我们完全可以猜想，C++动态库中的动态内存并不是使用Python中的内存申请机制申请的，Python不应该对这部分内存进行GC，如果真的是这样，C++的动态库就会出现内存泄漏的问题了。那事实是不是这样呢？我们可以使用内存检查工具Valgrind来检查上面的Python代码：
命令：
valgrind python3 hello.py
最终结果输出：
==17940== HEAP SUMMARY:
==17940== in use at exit: 647,194 bytes in 631 blocks
==17940== total heap usage: 8,914 allocs, 8,283 frees, 5,319,963 bytes allocated
==17940==
==17940== LEAK SUMMARY:
==17940== definitely lost: 32 bytes in 1 blocks
==17940== indirectly lost: 0 bytes in 0 blocks
==17940== possibly lost: 4,008 bytes in 7 blocks
==17940== still reachable: 643,154 bytes in 623 blocks
==17940== suppressed: 0 bytes in 0 blocks
==17940== Rerun with --leak-check=full to see details of leaked memory
==17940==
==17940== For counts of detected and suppressed errors, rerun with: -v
==17940== Use --track-origins=yes to see where uninitialised values come from
==17940== ERROR SUMMARY: 795 errors from 86 contexts (suppressed: 0 from 0)
可以看到，definitely lost了32字节，确实出现了内存泄漏，但是是不是动态库的问题我们还要进一步验证:
C++代码加入析构函数定义：
#include <iostream>
#include <cstdio>
#include <string>
using namespace std;
class Student {
private:
string name;
public:
Student(const char* n);
~Student();
void PrintName();
};
Student::Student(const char* n) {
this->name.assign(n);
}
Student::~Student() {
cout << "Student's destructor called" << endl;
}
void Student::PrintName() {
cout << "My name is " << this->name << endl;
}
extern "C" {
Student* new_student(const char* name) {
return new Student(name);
}
void print_student_name(Student* stu) {
stu->PrintName();
}
}
运行相同的Python代码：
xujijun@pc:~/codespace/python$ python3 hello.py
input student name: yanhewu
My name is yanhewu
从输出可以看到，Student的析构函数并没有被调用。这里可以确定，Python的GC并没有对动态库中申请的内存进行处理，也确实不能进行处理（毕竟不是Python环境下申请的内存，在C++动态库中可能会先释放这部分内存，如果GC再次释放就会出现内存问题）。但是内存泄漏的问题还是需要解决的，可以参照以下做法：
C++代码中添加内存释放接口：
#include <iostream>
#include <cstdio>
#include <string>
using namespace std;
class Student {
private:
string name;
public:
Student(const char* n);
~Student();
void PrintName();
};
Student::Student(const char* n) {
this->name.assign(n);
}
Student::~Student() {
cout << "Student's destructor called" << endl;
}
void Student::PrintName() {
cout << "My name is " << this->name << endl;
}
extern "C" {
Student* new_student(const char* name) {
return new Student(name);
}
// 释放对象内存函数
void del_student(Student* stu) {
delete stu;
}
void print_student_name(Student* stu) {
stu->PrintName();
}
}
Python代码中，在Student类中调用内存释放函数：
# -*- coding: utf-8 -*- #
from ctypes import CDLL
hello = CDLL('./hello.so')
class Student(object):
def __init__(self, name):
self.stu = hello.new_student(name.encode('utf-8'))
def __del__(self):
# Python的对象在被GC时调用__del__函数
hello.del_student(self.stu)
def print_name(self):
hello.print_student_name(self.stu)
if __name__ == '__main__':
name = input('input student name: ')
s = Student(name)
s.print_name()
运行Python代码：
xujijun@pc:~/codespace/python$ python3 hello.py
input student name: yanhewu
My name is yanhewu
Student's destructor called
可以看到，C++动态库中的Student类的析构函数被调用了。再次使用Valgrind检查内存使用情况：
==23780== HEAP SUMMARY:
==23780== in use at exit: 647,162 bytes in 630 blocks
==23780== total heap usage: 8,910 allocs, 8,280 frees, 5,317,023 bytes allocated
==23780==
==23780== LEAK SUMMARY:
==23780== definitely lost: 0 bytes in 0 blocks
==23780== indirectly lost: 0 bytes in 0 blocks
==23780== possibly lost: 4,008 bytes in 7 blocks
==23780== still reachable: 643,154 bytes in 623 blocks
==23780== suppressed: 0 bytes in 0 blocks
==23780== Rerun with --leak-check=full to see details of leaked memory
==23780==
==23780== For counts of detected and suppressed errors, rerun with: -v
==23780== Use --track-origins=yes to see where uninitialised values come from
==23780== ERROR SUMMARY: 793 errors from 87 contexts (suppressed: 0 from 0)
可以看到，definitely lost已经变为0，可以确定动态库申请的内存被成功释放。