337 lines
12 KiB
ReStructuredText
337 lines
12 KiB
ReStructuredText
.. highlight:: c
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.. _embedding:
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***************************************
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Embedding Python in Another Application
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***************************************
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The previous chapters discussed how to extend Python, that is, how to extend the
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functionality of Python by attaching a library of C functions to it. It is also
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possible to do it the other way around: enrich your C/C++ application by
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embedding Python in it. Embedding provides your application with the ability to
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implement some of the functionality of your application in Python rather than C
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or C++. This can be used for many purposes; one example would be to allow users
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to tailor the application to their needs by writing some scripts in Python. You
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can also use it yourself if some of the functionality can be written in Python
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more easily.
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Embedding Python is similar to extending it, but not quite. The difference is
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that when you extend Python, the main program of the application is still the
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Python interpreter, while if you embed Python, the main program may have nothing
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to do with Python --- instead, some parts of the application occasionally call
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the Python interpreter to run some Python code.
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So if you are embedding Python, you are providing your own main program. One of
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the things this main program has to do is initialize the Python interpreter. At
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the very least, you have to call the function :c:func:`Py_Initialize`. There are
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optional calls to pass command line arguments to Python. Then later you can
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call the interpreter from any part of the application.
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There are several different ways to call the interpreter: you can pass a string
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containing Python statements to :c:func:`PyRun_SimpleString`, or you can pass a
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stdio file pointer and a file name (for identification in error messages only)
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to :c:func:`PyRun_SimpleFile`. You can also call the lower-level operations
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described in the previous chapters to construct and use Python objects.
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.. seealso::
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:ref:`c-api-index`
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The details of Python's C interface are given in this manual. A great deal of
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necessary information can be found here.
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.. _high-level-embedding:
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Very High Level Embedding
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=========================
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The simplest form of embedding Python is the use of the very high level
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interface. This interface is intended to execute a Python script without needing
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to interact with the application directly. This can for example be used to
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perform some operation on a file. ::
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#define PY_SSIZE_T_CLEAN
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#include <Python.h>
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int
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main(int argc, char *argv[])
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{
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wchar_t *program = Py_DecodeLocale(argv[0], NULL);
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if (program == NULL) {
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fprintf(stderr, "Fatal error: cannot decode argv[0]\n");
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exit(1);
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}
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Py_SetProgramName(program); /* optional but recommended */
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Py_Initialize();
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PyRun_SimpleString("from time import time,ctime\n"
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"print('Today is', ctime(time()))\n");
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if (Py_FinalizeEx() < 0) {
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exit(120);
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}
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PyMem_RawFree(program);
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return 0;
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}
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The :c:func:`Py_SetProgramName` function should be called before
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:c:func:`Py_Initialize` to inform the interpreter about paths to Python run-time
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libraries. Next, the Python interpreter is initialized with
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:c:func:`Py_Initialize`, followed by the execution of a hard-coded Python script
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that prints the date and time. Afterwards, the :c:func:`Py_FinalizeEx` call shuts
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the interpreter down, followed by the end of the program. In a real program,
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you may want to get the Python script from another source, perhaps a text-editor
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routine, a file, or a database. Getting the Python code from a file can better
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be done by using the :c:func:`PyRun_SimpleFile` function, which saves you the
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trouble of allocating memory space and loading the file contents.
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.. _lower-level-embedding:
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Beyond Very High Level Embedding: An overview
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=============================================
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The high level interface gives you the ability to execute arbitrary pieces of
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Python code from your application, but exchanging data values is quite
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cumbersome to say the least. If you want that, you should use lower level calls.
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At the cost of having to write more C code, you can achieve almost anything.
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It should be noted that extending Python and embedding Python is quite the same
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activity, despite the different intent. Most topics discussed in the previous
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chapters are still valid. To show this, consider what the extension code from
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Python to C really does:
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#. Convert data values from Python to C,
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#. Perform a function call to a C routine using the converted values, and
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#. Convert the data values from the call from C to Python.
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When embedding Python, the interface code does:
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#. Convert data values from C to Python,
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#. Perform a function call to a Python interface routine using the converted
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values, and
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#. Convert the data values from the call from Python to C.
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As you can see, the data conversion steps are simply swapped to accommodate the
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different direction of the cross-language transfer. The only difference is the
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routine that you call between both data conversions. When extending, you call a
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C routine, when embedding, you call a Python routine.
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This chapter will not discuss how to convert data from Python to C and vice
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versa. Also, proper use of references and dealing with errors is assumed to be
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understood. Since these aspects do not differ from extending the interpreter,
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you can refer to earlier chapters for the required information.
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.. _pure-embedding:
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Pure Embedding
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==============
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The first program aims to execute a function in a Python script. Like in the
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section about the very high level interface, the Python interpreter does not
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directly interact with the application (but that will change in the next
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section).
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The code to run a function defined in a Python script is:
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.. literalinclude:: ../includes/run-func.c
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This code loads a Python script using ``argv[1]``, and calls the function named
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in ``argv[2]``. Its integer arguments are the other values of the ``argv``
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array. If you :ref:`compile and link <compiling>` this program (let's call
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the finished executable :program:`call`), and use it to execute a Python
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script, such as:
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.. code-block:: python
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def multiply(a,b):
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print("Will compute", a, "times", b)
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c = 0
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for i in range(0, a):
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c = c + b
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return c
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then the result should be:
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.. code-block:: shell-session
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$ call multiply multiply 3 2
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Will compute 3 times 2
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Result of call: 6
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Although the program is quite large for its functionality, most of the code is
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for data conversion between Python and C, and for error reporting. The
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interesting part with respect to embedding Python starts with ::
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Py_Initialize();
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pName = PyUnicode_DecodeFSDefault(argv[1]);
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/* Error checking of pName left out */
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pModule = PyImport_Import(pName);
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After initializing the interpreter, the script is loaded using
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:c:func:`PyImport_Import`. This routine needs a Python string as its argument,
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which is constructed using the :c:func:`PyUnicode_FromString` data conversion
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routine. ::
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pFunc = PyObject_GetAttrString(pModule, argv[2]);
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/* pFunc is a new reference */
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if (pFunc && PyCallable_Check(pFunc)) {
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...
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}
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Py_XDECREF(pFunc);
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Once the script is loaded, the name we're looking for is retrieved using
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:c:func:`PyObject_GetAttrString`. If the name exists, and the object returned is
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callable, you can safely assume that it is a function. The program then
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proceeds by constructing a tuple of arguments as normal. The call to the Python
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function is then made with::
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pValue = PyObject_CallObject(pFunc, pArgs);
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Upon return of the function, ``pValue`` is either ``NULL`` or it contains a
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reference to the return value of the function. Be sure to release the reference
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after examining the value.
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.. _extending-with-embedding:
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Extending Embedded Python
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=========================
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Until now, the embedded Python interpreter had no access to functionality from
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the application itself. The Python API allows this by extending the embedded
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interpreter. That is, the embedded interpreter gets extended with routines
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provided by the application. While it sounds complex, it is not so bad. Simply
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forget for a while that the application starts the Python interpreter. Instead,
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consider the application to be a set of subroutines, and write some glue code
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that gives Python access to those routines, just like you would write a normal
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Python extension. For example::
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static int numargs=0;
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/* Return the number of arguments of the application command line */
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static PyObject*
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emb_numargs(PyObject *self, PyObject *args)
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{
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if(!PyArg_ParseTuple(args, ":numargs"))
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return NULL;
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return PyLong_FromLong(numargs);
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}
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static PyMethodDef EmbMethods[] = {
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{"numargs", emb_numargs, METH_VARARGS,
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"Return the number of arguments received by the process."},
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{NULL, NULL, 0, NULL}
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};
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static PyModuleDef EmbModule = {
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PyModuleDef_HEAD_INIT, "emb", NULL, -1, EmbMethods,
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NULL, NULL, NULL, NULL
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};
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static PyObject*
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PyInit_emb(void)
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{
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return PyModule_Create(&EmbModule);
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}
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Insert the above code just above the :c:func:`main` function. Also, insert the
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following two statements before the call to :c:func:`Py_Initialize`::
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numargs = argc;
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PyImport_AppendInittab("emb", &PyInit_emb);
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These two lines initialize the ``numargs`` variable, and make the
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:func:`emb.numargs` function accessible to the embedded Python interpreter.
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With these extensions, the Python script can do things like
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.. code-block:: python
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import emb
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print("Number of arguments", emb.numargs())
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In a real application, the methods will expose an API of the application to
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Python.
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.. TODO: threads, code examples do not really behave well if errors happen
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(what to watch out for)
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.. _embeddingincplusplus:
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Embedding Python in C++
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=======================
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It is also possible to embed Python in a C++ program; precisely how this is done
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will depend on the details of the C++ system used; in general you will need to
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write the main program in C++, and use the C++ compiler to compile and link your
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program. There is no need to recompile Python itself using C++.
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.. _compiling:
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Compiling and Linking under Unix-like systems
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=============================================
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It is not necessarily trivial to find the right flags to pass to your
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compiler (and linker) in order to embed the Python interpreter into your
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application, particularly because Python needs to load library modules
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implemented as C dynamic extensions (:file:`.so` files) linked against
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it.
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To find out the required compiler and linker flags, you can execute the
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:file:`python{X.Y}-config` script which is generated as part of the
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installation process (a :file:`python3-config` script may also be
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available). This script has several options, of which the following will
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be directly useful to you:
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* ``pythonX.Y-config --cflags`` will give you the recommended flags when
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compiling:
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.. code-block:: shell-session
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$ /opt/bin/python3.4-config --cflags
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-I/opt/include/python3.4m -I/opt/include/python3.4m -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes
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* ``pythonX.Y-config --ldflags`` will give you the recommended flags when
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linking:
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.. code-block:: shell-session
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$ /opt/bin/python3.4-config --ldflags
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-L/opt/lib/python3.4/config-3.4m -lpthread -ldl -lutil -lm -lpython3.4m -Xlinker -export-dynamic
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.. note::
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To avoid confusion between several Python installations (and especially
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between the system Python and your own compiled Python), it is recommended
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that you use the absolute path to :file:`python{X.Y}-config`, as in the above
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example.
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If this procedure doesn't work for you (it is not guaranteed to work for
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all Unix-like platforms; however, we welcome :ref:`bug reports <reporting-bugs>`)
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you will have to read your system's documentation about dynamic linking and/or
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examine Python's :file:`Makefile` (use :func:`sysconfig.get_makefile_filename`
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to find its location) and compilation
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options. In this case, the :mod:`sysconfig` module is a useful tool to
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programmatically extract the configuration values that you will want to
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combine together. For example:
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.. code-block:: pycon
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>>> import sysconfig
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>>> sysconfig.get_config_var('LIBS')
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'-lpthread -ldl -lutil'
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>>> sysconfig.get_config_var('LINKFORSHARED')
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'-Xlinker -export-dynamic'
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.. XXX similar documentation for Windows missing
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