Here's a quick and dirty ctypes tutorial.
First, write your C library. Here's a simple Hello world example:
testlib.c
#include <stdio.h>
void myprint(void);
void myprint()
{
printf("hello world\n");
}
Now compile it as a shared library (mac fix found here):
$ gcc -shared -Wl,-soname,testlib -o testlib.so -fPIC testlib.c
# or... for Mac OS X
$ gcc -shared -Wl,-install_name,testlib.so -o testlib.so -fPIC testlib.c
Then, write a wrapper using ctypes:
testlibwrapper.py
import ctypes
testlib = ctypes.CDLL('/full/path/to/testlib.so')
testlib.myprint()
Now execute it:
$ python testlibwrapper.py
And you should see the output
Hello world
$
If you already have a library in mind, you can skip the non-python part of the tutorial. Make sure ctypes can find the library by putting it in /usr/lib or another standard directory. If you do this, you don't need to specify the full path when writing the wrapper. If you choose not to do this, you must provide the full path of the library when calling ctypes.CDLL().
This isn't the place for a more comprehensive tutorial, but if you ask for help with specific problems on this site, I'm sure the community would help you out.
PS: I'm assuming you're on Linux because you've used ctypes.CDLL('libc.so.6'). If you're on another OS, things might change a little bit (or quite a lot).
Here's a quick and dirty ctypes tutorial.
First, write your C library. Here's a simple Hello world example:
testlib.c
#include <stdio.h>
void myprint(void);
void myprint()
{
printf("hello world\n");
}
Now compile it as a shared library (mac fix found here):
$ gcc -shared -Wl,-soname,testlib -o testlib.so -fPIC testlib.c
# or... for Mac OS X
$ gcc -shared -Wl,-install_name,testlib.so -o testlib.so -fPIC testlib.c
Then, write a wrapper using ctypes:
testlibwrapper.py
import ctypes
testlib = ctypes.CDLL('/full/path/to/testlib.so')
testlib.myprint()
Now execute it:
$ python testlibwrapper.py
And you should see the output
Hello world
$
If you already have a library in mind, you can skip the non-python part of the tutorial. Make sure ctypes can find the library by putting it in /usr/lib or another standard directory. If you do this, you don't need to specify the full path when writing the wrapper. If you choose not to do this, you must provide the full path of the library when calling ctypes.CDLL().
This isn't the place for a more comprehensive tutorial, but if you ask for help with specific problems on this site, I'm sure the community would help you out.
PS: I'm assuming you're on Linux because you've used ctypes.CDLL('libc.so.6'). If you're on another OS, things might change a little bit (or quite a lot).
The answer by Chinmay Kanchi is excellent but I wanted an example of a function which passes and returns a variables/arrays to a C++ code. I though I'd include it here in case it is useful to others.
Passing and returning an integer
The C++ code for a function which takes an integer and adds one to the returned value,
extern "C" int add_one(int i)
{
return i+1;
}
Saved as file test.cpp, note the required extern "C" (this can be removed for C code).
This is compiled using g++, with arguments similar to Chinmay Kanchi answer,
g++ -shared -o testlib.so -fPIC test.cpp
The Python code uses load_library from the numpy.ctypeslib assuming the path to the shared library in the same directory as the Python script,
import numpy.ctypeslib as ctl
import ctypes
libname = 'testlib.so'
libdir = './'
lib=ctl.load_library(libname, libdir)
py_add_one = lib.add_one
py_add_one.argtypes = [ctypes.c_int]
value = 5
results = py_add_one(value)
print(results)
This prints 6 as expected.
Passing and printing an array
You can also pass arrays as follows, for a C code to print the element of an array,
extern "C" void print_array(double* array, int N)
{
for (int i=0; i<N; i++)
cout << i << " " << array[i] << endl;
}
which is compiled as before and the imported in the same way. The extra Python code to use this function would then be,
import numpy as np
py_print_array = lib.print_array
py_print_array.argtypes = [ctl.ndpointer(np.float64,
flags='aligned, c_contiguous'),
ctypes.c_int]
A = np.array([1.4,2.6,3.0], dtype=np.float64)
py_print_array(A, 3)
where we specify the array, the first argument to print_array, as a pointer to a Numpy array of aligned, c_contiguous 64 bit floats and the second argument as an integer which tells the C code the number of elements in the Numpy array. This then printed by the C code as follows,
1.4
2.6
3.0
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