scenarios/clibs

Interfacing with C/C++ Libraries

C Foreign Function Interface

`CFFI <https://cffi.readthedocs.org/en/latest/>`_ provides a simple to use

mechanism for interfacing with C from both CPython and PyPy. It supports two

modes: an inline ABI compatibility mode (example provided below), which allows

you to dynamically load and run functions from executable modules (essentially

exposing the same functionality as LoadLibrary or dlopen), and an API mode,

which allows you to build C extension modules.

ABI Interaction

.. code-block:: python

ctypes

`ctypes <https://docs.python.org/3/library/ctypes.html>`_ is the de facto

library for interfacing with C/C++ from CPython, and it provides not only

full access to the native C interface of most major operating systems (e.g.,

kernel32 on Windows, or libc on \*nix), but also provides support for loading

and interfacing with dynamic libraries, such as DLLs or shared objects at

runtime. It does bring along with it a whole host of types for interacting

with system APIs, and allows you to rather easily define your own complex

types, such as structs and unions, and allows you to modify things such as

padding and alignment, if needed. It can be a bit crufty to use, but in

conjunction with the `struct <https://docs.python.org/3.5/library/struct.html>`_

module, you are essentially provided full control over how your data types get

translated into something something usable by a pure C(++) method.

Struct Equivalents

:file:`MyStruct.h`

.. code-block:: c

:file:`MyStruct.py`

.. code-block:: python

SWIG

`SWIG <http://www.swig.org>`_, though not strictly Python focused (it supports a

large number of scripting languages), is a tool for generating bindings for

interpreted languages from C/C++ header files. It is extremely simple to use:

the consumer simply needs to define an interface file (detailed in the

tutorial and documentations), include the requisite C/C++ headers, and run

the build tool against them. While it does have some limits, (it currently

seems to have issues with a small subset of newer C++ features, and getting

template-heavy code to work can be a bit verbose), it provides a great deal

of power and exposes lots of features to Python with little effort.

Additionally, you can easily extend the bindings SWIG creates (in the

interface file) to overload operators and built-in methods, effectively re-

cast C++ exceptions to be catchable by Python, etc.

Example: Overloading __repr__

:file:`MyClass.h`

.. code-block:: c++

:linenos:

#include <string>

class MyClass {

private:

std::string name;

public:

std::string getName();

};

:file:`myclass.i`

.. code-block:: c++

:linenos:

%include "string.i"

%module myclass

%{

#include <string>

#include "MyClass.h"

%}

%extend MyClass {

std::string __repr__()

{

return $self->getName();

}

}

%include "MyClass.h"

Boost.Python

`Boost.Python <http://www.boost.org/doc/libs/1_59_0/libs/python/doc/>`_

requires a bit more manual work to expose C++ object functionality, but

it is capable of providing all the same features SWIG does and then some,

to include providing wrappers to access PyObjects in C++, extracting SWIG-

wrapper objects, and even embedding bits of Python into your C++ code.