Exposing Functions to Embedded Python

So far, instead of exposing functions to Python, we have (the reverse I guess) embedded the Python interpreter in our process using Boost::Python. So, running Python from within our process is all good and well but we want the Python code to interact with our C++ code as well.

We’ll add to the previous example:

<code>const char* greet()
	return "Hello World from C++";

	def("greet", greet);

Here we have defined a python module embed_test which we will now expose to our embedded Python interpreter. The module has one function, “greet” in the Python module calls the C++ greet function.

Now we add to the main function:

<code>if(PyImport_AppendInittab("embed_test", initembed_test) == -1)
		throw std::runtime_error("Failed to add test module to builtins");</code>

The initembed_test reference is the function name generated by the BOOST_PYTHON_MODULE macro. Once we have made Python aware of this built-in module, we can modify the python code we run in the example to print out the result of the greet function:

<code>handle<> ignored((PyRun_String(
	"import embed_test\n"
	"print embed_test.greet()"

	, Py_file_input
	, main_namespace.ptr()
	, main_namespace.ptr())

The techniques used here are all based around the basic functionality available in the Python C API. However, the Boost::Python library does make it easier to expose your own code to the Python interpreter. Next we’ll look at exposing classes and then move on to the use of SWIG.