Until now, the embedded Python interpreter had no access to
functionality from the application itself. The Python API allows this
by extending the embedded interpreter. That is, the embedded
interpreter gets extended with routines provided by the application.
While it sounds complex, it is not so bad. Simply forget for a while
that the application starts the Python interpreter. Instead, consider
the application to be a set of subroutines, and write some glue code
that gives Python access to those routines, just like you would write
a normal Python extension. For example:
static int numargs=0;
/* Return the number of arguments of the application command line */
static PyObject*
emb_numargs(PyObject *self, PyObject *args)
{
if(!PyArg_ParseTuple(args, ":numargs"))
return NULL;
return Py_BuildValue("i", numargs);
}
static PyMethodDef EmbMethods[] = {
{"numargs", emb_numargs, METH_VARARGS,
"Return the number of arguments received by the process."},
{NULL, NULL, 0, NULL}
};
Insert the above code just above the main() function.
Also, insert the following two statements directly after
Py_Initialize():
numargs = argc;
Py_InitModule("emb", EmbMethods);
These two lines initialize the numargs variable, and make the
emb.numargs() function accessible to the embedded Python
interpreter. With these extensions, the Python script can do things
like
import emb
print "Number of arguments", emb.numargs()
In a real application, the methods will expose an API of the
application to Python.
