1. Incorporando o Python numa Outra Aplicação¶
Os capítulos anteriores discutiram como estender o Python, ou seja, como expandir a funcionalidade do Python anexando uma biblioteca de funções em C a ele. Também é possível fazer o inverso: enriquecer sua aplicação em C/C++ incorporando o Python nela. A incorporação fornece à sua aplicação a capacidade de implementar parte da funcionalidade da aplicação em Python em vez de C ou C++. Isso pode ser usado para diversos propósitos; um exemplo seria permitir que os usuários personalizem a aplicação de acordo com suas necessidades escrevendo alguns scripts em Python. Você também pode usá-la se parte da funcionalidade puder ser escrita em Python mais facilmente.
Incorporar o Python é semelhante a estendê-lo, mas não exatamente. A diferença é que, ao estender o Python, o programa principal da aplicação ainda é o interpretador Python, enquanto que, se você incorporar o Python, o programa principal pode não ter nada a ver com o Python — em vez disso, algumas partes da aplicação chamam ocasionalmente o interpretador Python para executar algum código Python.
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.
Ver também
- Manual de referência da API Python/C
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[])
{
PyStatus status;
PyConfig config;
PyConfig_InitPythonConfig(&config);
/* optional but recommended */
status = PyConfig_SetBytesString(&config, &config.program_name, argv[0]);
if (PyStatus_Exception(status)) {
goto exception;
}
status = Py_InitializeFromConfig(&config);
if (PyStatus_Exception(status)) {
goto exception;
}
PyConfig_Clear(&config);
PyRun_SimpleString("from time import time,ctime\n"
"print('Today is', ctime(time()))\n");
if (Py_FinalizeEx() < 0) {
exit(120);
}
return 0;
exception:
PyConfig_Clear(&config);
Py_ExitStatusException(status);
}
Nota
#define PY_SSIZE_T_CLEAN was used to indicate that Py_ssize_t should be
used in some APIs instead of int.
It is not necessary since Python 3.13, but we keep it here for backward compatibility.
See Strings e buffers for a description of this macro.
Setting PyConfig.program_name should be called before
Py_InitializeFromConfig() 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:
Convert data values from Python to C,
Perform a function call to a C routine using the converted values, and
Convert the data values from the call from C to Python.
When embedding Python, the interface code does:
Convert data values from C to Python,
Perform a function call to a Python interface routine using the converted values, and
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
pythonX.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 --cflagswill give you the recommended flags when compiling:$ /opt/bin/python3.11-config --cflags -I/opt/include/python3.11 -I/opt/include/python3.11 -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall
pythonX.Y-config --ldflags --embedwill give you the recommended flags when linking:$ /opt/bin/python3.11-config --ldflags --embed -L/opt/lib/python3.11/config-3.11-x86_64-linux-gnu -L/opt/lib -lpython3.11 -lpthread -ldl -lutil -lm
Nota
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 pythonX.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'