1. Embedding Python in Another Application
******************************************

The previous chapters discussed how to extend Python, that is, how to
extend the functionality of Python by attaching a library of C
functions to it.  It is also possible to do it the other way around:
enrich your C/C++ application by embedding Python in it.  Embedding
provides your application with the ability to implement some of the
functionality of your application in Python rather than C or C++. This
can be used for many purposes; one example would be to allow users to
tailor the application to their needs by writing some scripts in
Python.  You can also use it yourself if some of the functionality can
be written in Python more easily.

Embedding Python is similar to extending it, but not quite.  The
difference is that when you extend Python, the main program of the
application is still the Python interpreter, while if you embed
Python, the main program may have nothing to do with Python — instead,
some parts of the application occasionally call the Python interpreter
to run some Python code.

So if you are embedding Python, you are providing your own main
program.  One of the things this main program has to do is initialize
the Python interpreter.  At the very least, you have to call the
function "Py_Initialize()".  There are optional calls to pass command
line arguments to Python.  Then later you can call the interpreter
from any part of the application.

There are several different ways to call the interpreter: you can pass
a string containing Python statements to "PyRun_SimpleString()", or
you can pass a stdio file pointer and a file name (for identification
in error messages only) to "PyRun_SimpleFile()".  You can also call
the lower-level operations described in the previous chapters to
construct and use Python objects.

See also:

  Python/C API Reference Manual
     The details of Python’s C interface are given in this manual. A
     great deal of necessary information can be found here.


1.1. Very High Level Embedding
==============================

The simplest form of embedding Python is the use of the very high
level interface. This interface is intended to execute a Python script
without needing to interact with the application directly. This can
for example be used to perform some operation on a file.

   #define PY_SSIZE_T_CLEAN
   #include <Python.h>

   int
   main(int argc, char *argv[])
   {
       wchar_t *program = Py_DecodeLocale(argv[0], NULL);
       if (program == NULL) {
           fprintf(stderr, "Fatal error: cannot decode argv[0]\n");
           exit(1);
       }
       Py_SetProgramName(program);  /* optional but recommended */
       Py_Initialize();
       PyRun_SimpleString("from time import time,ctime\n"
                          "print('Today is', ctime(time()))\n");
       if (Py_FinalizeEx() < 0) {
           exit(120);
       }
       PyMem_RawFree(program);
       return 0;
   }

The "Py_SetProgramName()" function should be called before
"Py_Initialize()" to inform the interpreter about paths to Python run-
time libraries.  Next, the Python interpreter is initialized with
"Py_Initialize()", followed by the execution of a hard-coded Python
script that prints the date and time.  Afterwards, the
"Py_FinalizeEx()" call shuts the interpreter down, followed by the end
of the program.  In a real program, you may want to get the Python
script from another source, perhaps a text-editor routine, a file, or
a database.  Getting the Python code from a file can better be done by
using the "PyRun_SimpleFile()" function, which saves you the trouble
of allocating memory space and loading the file contents.


1.2. Beyond Very High Level Embedding: An overview
==================================================

The high level interface gives you the ability to execute arbitrary
pieces of Python code from your application, but exchanging data
values is quite cumbersome to say the least. If you want that, you
should use lower level calls. At the cost of having to write more C
code, you can achieve almost anything.

It should be noted that extending Python and embedding Python is quite
the same activity, despite the different intent. Most topics discussed
in the previous chapters are still valid. To show this, consider what
the extension code from Python to C really does:

1. Convert data values from Python to C,

2. Perform a function call to a C routine using the converted
   values, and

3. Convert the data values from the call from C to Python.

When embedding Python, the interface code does:

1. Convert data values from C to Python,

2. Perform a function call to a Python interface routine using the
   converted values, and

3. Convert the data values from the call from Python to C.

As you can see, the data conversion steps are simply swapped to
accommodate the different direction of the cross-language transfer.
The only difference is the routine that you call between both data
conversions. When extending, you call a C routine, when embedding, you
call a Python routine.

This chapter will not discuss how to convert data from Python to C and
vice versa.  Also, proper use of references and dealing with errors is
assumed to be understood.  Since these aspects do not differ from
extending the interpreter, you can refer to earlier chapters for the
required information.


1.3. Pure Embedding
===================

The first program aims to execute a function in a Python script. Like
in the section about the very high level interface, the Python
interpreter does not directly interact with the application (but that
will change in the next section).

The code to run a function defined in a Python script is:

   #define PY_SSIZE_T_CLEAN
   #include <Python.h>

   int
   main(int argc, char *argv[])
   {
       PyObject *pName, *pModule, *pFunc;
       PyObject *pArgs, *pValue;
       int i;

       if (argc < 3) {
           fprintf(stderr,"Usage: call pythonfile funcname [args]\n");
           return 1;
       }

       Py_Initialize();
       pName = PyUnicode_DecodeFSDefault(argv[1]);
       /* Error checking of pName left out */

       pModule = PyImport_Import(pName);
       Py_DECREF(pName);

       if (pModule != NULL) {
           pFunc = PyObject_GetAttrString(pModule, argv[2]);
           /* pFunc is a new reference */

           if (pFunc && PyCallable_Check(pFunc)) {
               pArgs = PyTuple_New(argc - 3);
               for (i = 0; i < argc - 3; ++i) {
                   pValue = PyLong_FromLong(atoi(argv[i + 3]));
                   if (!pValue) {
                       Py_DECREF(pArgs);
                       Py_DECREF(pModule);
                       fprintf(stderr, "Cannot convert argument\n");
                       return 1;
                   }
                   /* pValue reference stolen here: */
                   PyTuple_SetItem(pArgs, i, pValue);
               }
               pValue = PyObject_CallObject(pFunc, pArgs);
               Py_DECREF(pArgs);
               if (pValue != NULL) {
                   printf("Result of call: %ld\n", PyLong_AsLong(pValue));
                   Py_DECREF(pValue);
               }
               else {
                   Py_DECREF(pFunc);
                   Py_DECREF(pModule);
                   PyErr_Print();
                   fprintf(stderr,"Call failed\n");
                   return 1;
               }
           }
           else {
               if (PyErr_Occurred())
                   PyErr_Print();
               fprintf(stderr, "Cannot find function \"%s\"\n", argv[2]);
           }
           Py_XDECREF(pFunc);
           Py_DECREF(pModule);
       }
       else {
           PyErr_Print();
           fprintf(stderr, "Failed to load \"%s\"\n", argv[1]);
           return 1;
       }
       if (Py_FinalizeEx() < 0) {
           return 120;
       }
       return 0;
   }

This code loads a Python script using "argv[1]", and calls the
function named in "argv[2]".  Its integer arguments are the other
values of the "argv" array.  If you compile and link this program
(let’s call the finished executable **call**), and use it to execute a
Python script, such as:

   def multiply(a,b):
       print("Will compute", a, "times", b)
       c = 0
       for i in range(0, a):
           c = c + b
       return c

then the result should be:

   $ call multiply multiply 3 2
   Will compute 3 times 2
   Result of call: 6

Although the program is quite large for its functionality, most of the
code is for data conversion between Python and C, and for error
reporting.  The interesting part with respect to embedding Python
starts with

   Py_Initialize();
   pName = PyUnicode_DecodeFSDefault(argv[1]);
   /* Error checking of pName left out */
   pModule = PyImport_Import(pName);

After initializing the interpreter, the script is loaded using
"PyImport_Import()".  This routine needs a Python string as its
argument, which is constructed using the "PyUnicode_FromString()" data
conversion routine.

   pFunc = PyObject_GetAttrString(pModule, argv[2]);
   /* pFunc is a new reference */

   if (pFunc && PyCallable_Check(pFunc)) {
       ...
   }
   Py_XDECREF(pFunc);

Once the script is loaded, the name we’re looking for is retrieved
using "PyObject_GetAttrString()".  If the name exists, and the object
returned is callable, you can safely assume that it is a function.
The program then proceeds by constructing a tuple of arguments as
normal.  The call to the Python function is then made with:

   pValue = PyObject_CallObject(pFunc, pArgs);

Upon return of the function, "pValue" is either "NULL" or it contains
a reference to the return value of the function.  Be sure to release
the reference after examining the value.


1.4. Extending Embedded Python
==============================

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 PyLong_FromLong(numargs);
   }

   static PyMethodDef EmbMethods[] = {
       {"numargs", emb_numargs, METH_VARARGS,
        "Return the number of arguments received by the process."},
       {NULL, NULL, 0, NULL}
   };

   static PyModuleDef EmbModule = {
       PyModuleDef_HEAD_INIT, "emb", NULL, -1, EmbMethods,
       NULL, NULL, NULL, NULL
   };

   static PyObject*
   PyInit_emb(void)
   {
       return PyModule_Create(&EmbModule);
   }

Insert the above code just above the "main()" function. Also, insert
the following two statements before the call to "Py_Initialize()":

   numargs = argc;
   PyImport_AppendInittab("emb", &PyInit_emb);

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.


1.5. Embedding Python in C++
============================

It is also possible to embed Python in a C++ program; precisely how
this is done will depend on the details of the C++ system used; in
general you will need to write the main program in C++, and use the
C++ compiler to compile and link your program.  There is no need to
recompile Python itself using C++.


1.6. Compiling and Linking under Unix-like systems
==================================================

It is not necessarily trivial to find the right flags to pass to your
compiler (and linker) in order to embed the Python interpreter into
your application, particularly because Python needs to load library
modules implemented as C dynamic extensions (".so" files) linked
against it.

To find out the required compiler and linker flags, you can execute
the "python*X.Y*-config" script which is generated as part of the
installation process (a "python3-config" script may also be
available).  This script has several options, of which the following
will be directly useful to you:

* "pythonX.Y-config --cflags" will give you the recommended flags
  when compiling:

     $ /opt/bin/python3.4-config --cflags
     -I/opt/include/python3.4m -I/opt/include/python3.4m -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes

* "pythonX.Y-config --ldflags" will give you the recommended flags
  when linking:

     $ /opt/bin/python3.4-config --ldflags
     -L/opt/lib/python3.4/config-3.4m -lpthread -ldl -lutil -lm -lpython3.4m -Xlinker -export-dynamic

Note: To avoid confusion between several Python installations (and
  especially between the system Python and your own compiled Python),
  it is recommended that you use the absolute path to
  "python*X.Y*-config", as in the above example.

If this procedure doesn’t work for you (it is not guaranteed to work
for all Unix-like platforms; however, we welcome bug reports) you will
have to read your system’s documentation about dynamic linking and/or
examine Python’s "Makefile" (use "sysconfig.get_makefile_filename()"
to find its location) and compilation options.  In this case, the
"sysconfig" module is a useful tool to programmatically extract the
configuration values that you will want to combine together.  For
example:

   >>> import sysconfig
   >>> sysconfig.get_config_var('LIBS')
   '-lpthread -ldl  -lutil'
   >>> sysconfig.get_config_var('LINKFORSHARED')
   '-Xlinker -export-dynamic'
