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C++¤

This example shows how to access a 32-bit C++ library from 64-bit Python. Cpp32 is the 32-bit server and Cpp64 is the 64-bit client.

The source code of the C++ program is available here.

Attention

If you have issues running the example make sure that you have the prerequisites installed.

Important

By default, ctypes treats all input argument types and the return type of a library function to be a c_int. Therefore, the argtypes and the restype should be defined for each function in the library. The Cpp32 class shows various examples of defining the argtypes and the restype value.

Create a Cpp64 client to communicate with the 32-bit library from 64-bit Python

>>> from msl.examples.loadlib import Cpp64
>>> cpp = Cpp64()

Numeric types¤

Add two integers, see Cpp64.add

>>> cpp.add(3, 14)
17

Subtract two C++ floating-point numbers, see Cpp64.subtract

>>> cpp.subtract(43.2, 3.2)
40.0

Add or subtract two C++ double-precision numbers, see Cpp64.add_or_subtract

>>> cpp.add_or_subtract(1.0, 2.0, do_addition=True)
3.0
>>> cpp.add_or_subtract(1.0, 2.0, do_addition=False)
-1.0

Arrays¤

Multiply a 1D array by a number, see Cpp64.scalar_multiply

Attention

The Cpp64.scalar_multiply function takes a pointer to an array as an input argument, see the source code. One cannot pass pointers from Client64 to Server32 because a 64-bit process cannot share the same memory space as a 32-bit process. All 32-bit pointers must be created (using ctypes) in the class that is a subclass of Server32 and only the value that is stored at that address can be returned to Client64 for use in the 64-bit program.

>>> a = [float(val) for val in range(10)]
>>> cpp.scalar_multiply(2.0, a)
[0.0, 2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0]

If you have a numpy.ndarray in 64-bit Python then you cannot pass the ndarray object to Server32 because the 32-bit server would need to load the ndarray in a 32-bit version of numpy (which is not included by default in the 32-bit server, but could be — see refreeze for more details). To simplify the procedure you could convert the ndarray to a list using the numpy.ndarray.tolist method

>>> import numpy as np
>>> a = np.arange(9.)
>>> cpp.scalar_multiply(3.1, a.tolist())
[0.0, 3.1, 6.2, 9.3, 12.4, 15.5, 18.6, 21.7, 24.8]

or you could use the builtin array.array class

>>> from array import array
>>> b = array("d", a.tobytes())
>>> cpp.scalar_multiply(3.1, b)
[0.0, 3.1, 6.2, 9.3, 12.4, 15.5, 18.6, 21.7, 24.8]

If you want the returned value from scalar_multiply to be an ndarray use

>>> np.array(cpp.scalar_multiply(3.1, b))
array([ 0. ,  3.1,  6.2,  9.3, 12.4, 15.5, 18.6, 21.7, 24.8])

Strings¤

In this example the memory for the reversed string is allocated in Python, see Cpp64.reverse_string_v1

>>> cpp.reverse_string_v1("hello world!")
'!dlrow olleh'

In this example the memory for the reversed string is allocated in C++, see Cpp64.reverse_string_v2

>>> cpp.reverse_string_v2("uncertainty")
'ytniatrecnu'

Structs¤

It is possible to pickle a ctypes.Structure and pass the struct object between Cpp64 and Cpp32 provided that the struct is a fixed size in memory (i.e., the struct does not contain any pointers). If the struct contains pointers then you must create the struct within Cpp32 and you can only pass the values of the struct back to Cpp64.

The source code of the C++ library contains the following structs

struct Point {
    double x;
    double y;
};

struct FourPoints {
    Point points[4];
};

struct NPoints {
    int n;
    Point *points;
};

The Cpp64.distance_4_points method uses the FourPoints struct to calculate the total distance connecting 4 Point structs. Since the FourPoints struct is a fixed size it can be created in 64-bit Python, pickled and then unpickled in Cpp32

>>> from msl.examples.loadlib import FourPoints
>>> fp = FourPoints((0, 0), (0, 1), (1, 1), (1, 0))
>>> cpp.distance_4_points(fp)
4.0

The Cpp32.circumference method uses the NPoints struct to calculate the circumference of a circle using n Point structs. Since the NPoints struct is not a fixed size it must be created in the Cpp32.circumference method. The Cpp64.circumference method takes the values of the radius and n as input arguments to pass to the Cpp32.circumference method.

>>> for i in range(16):
...     print(cpp.circumference(0.5, 2**i))
...
0.0
2.0
2.828427124746...
3.061467458920...
3.121445152258...
3.136548490545...
3.140331156954...
3.141277250932...
3.141513801144...
3.141572940367...
3.141587725277...
3.141591421511...
3.141592345569...
3.141592576584...
3.141592634337...
3.141592648775...

You have access to the server's stdout and stderr streams when you shut down the server

>>> stdout, stderr = cpp.shutdown_server32()