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diff --git a/Doc/ext/extending.tex b/Doc/ext/extending.tex deleted file mode 100644 index 53d90db..0000000 --- a/Doc/ext/extending.tex +++ /dev/null @@ -1,1390 +0,0 @@ -\chapter{Extending Python with \C{} or \Cpp{} \label{intro}} - - -It is quite easy to add new built-in modules to Python, if you know -how to program in C. Such \dfn{extension modules} can do two things -that can't be done directly in Python: they can implement new built-in -object types, and they can call C library functions and system calls. - -To support extensions, the Python API (Application Programmers -Interface) defines a set of functions, macros and variables that -provide access to most aspects of the Python run-time system. The -Python API is incorporated in a C source file by including the header -\code{"Python.h"}. - -The compilation of an extension module depends on its intended use as -well as on your system setup; details are given in later chapters. - - -\section{A Simple Example - \label{simpleExample}} - -Let's create an extension module called \samp{spam} (the favorite food -of Monty Python fans...) and let's say we want to create a Python -interface to the C library function \cfunction{system()}.\footnote{An -interface for this function already exists in the standard module -\module{os} --- it was chosen as a simple and straightforward example.} -This function takes a null-terminated character string as argument and -returns an integer. We want this function to be callable from Python -as follows: - -\begin{verbatim} ->>> import spam ->>> status = spam.system("ls -l") -\end{verbatim} - -Begin by creating a file \file{spammodule.c}. (Historically, if a -module is called \samp{spam}, the C file containing its implementation -is called \file{spammodule.c}; if the module name is very long, like -\samp{spammify}, the module name can be just \file{spammify.c}.) - -The first line of our file can be: - -\begin{verbatim} -#include <Python.h> -\end{verbatim} - -which pulls in the Python API (you can add a comment describing the -purpose of the module and a copyright notice if you like). - -\begin{notice}[warning] - Since Python may define some pre-processor definitions which affect - the standard headers on some systems, you \emph{must} include - \file{Python.h} before any standard headers are included. -\end{notice} - -All user-visible symbols defined by \file{Python.h} have a prefix of -\samp{Py} or \samp{PY}, except those defined in standard header files. -For convenience, and since they are used extensively by the Python -interpreter, \code{"Python.h"} includes a few standard header files: -\code{<stdio.h>}, \code{<string.h>}, \code{<errno.h>}, and -\code{<stdlib.h>}. If the latter header file does not exist on your -system, it declares the functions \cfunction{malloc()}, -\cfunction{free()} and \cfunction{realloc()} directly. - -The next thing we add to our module file is the C function that will -be called when the Python expression \samp{spam.system(\var{string})} -is evaluated (we'll see shortly how it ends up being called): - -\begin{verbatim} -static PyObject * -spam_system(PyObject *self, PyObject *args) -{ - const char *command; - int sts; - - if (!PyArg_ParseTuple(args, "s", &command)) - return NULL; - sts = system(command); - return Py_BuildValue("i", sts); -} -\end{verbatim} - -There is a straightforward translation from the argument list in -Python (for example, the single expression \code{"ls -l"}) to the -arguments passed to the C function. The C function always has two -arguments, conventionally named \var{self} and \var{args}. - -The \var{self} argument is only used when the C function implements a -built-in method, not a function. In the example, \var{self} will -always be a \NULL{} pointer, since we are defining a function, not a -method. (This is done so that the interpreter doesn't have to -understand two different types of C functions.) - -The \var{args} argument will be a pointer to a Python tuple object -containing the arguments. Each item of the tuple corresponds to an -argument in the call's argument list. The arguments are Python -objects --- in order to do anything with them in our C function we have -to convert them to C values. The function \cfunction{PyArg_ParseTuple()} -in the Python API checks the argument types and converts them to C -values. It uses a template string to determine the required types of -the arguments as well as the types of the C variables into which to -store the converted values. More about this later. - -\cfunction{PyArg_ParseTuple()} returns true (nonzero) if all arguments have -the right type and its components have been stored in the variables -whose addresses are passed. It returns false (zero) if an invalid -argument list was passed. In the latter case it also raises an -appropriate exception so the calling function can return -\NULL{} immediately (as we saw in the example). - - -\section{Intermezzo: Errors and Exceptions - \label{errors}} - -An important convention throughout the Python interpreter is the -following: when a function fails, it should set an exception condition -and return an error value (usually a \NULL{} pointer). Exceptions -are stored in a static global variable inside the interpreter; if this -variable is \NULL{} no exception has occurred. A second global -variable stores the ``associated value'' of the exception (the second -argument to \keyword{raise}). A third variable contains the stack -traceback in case the error originated in Python code. These three -variables are the C equivalents of the Python variables -\code{sys.exc_type}, \code{sys.exc_value} and \code{sys.exc_traceback} (see -the section on module \module{sys} in the -\citetitle[../lib/lib.html]{Python Library Reference}). It is -important to know about them to understand how errors are passed -around. - -The Python API defines a number of functions to set various types of -exceptions. - -The most common one is \cfunction{PyErr_SetString()}. Its arguments -are an exception object and a C string. The exception object is -usually a predefined object like \cdata{PyExc_ZeroDivisionError}. The -C string indicates the cause of the error and is converted to a -Python string object and stored as the ``associated value'' of the -exception. - -Another useful function is \cfunction{PyErr_SetFromErrno()}, which only -takes an exception argument and constructs the associated value by -inspection of the global variable \cdata{errno}. The most -general function is \cfunction{PyErr_SetObject()}, which takes two object -arguments, the exception and its associated value. You don't need to -\cfunction{Py_INCREF()} the objects passed to any of these functions. - -You can test non-destructively whether an exception has been set with -\cfunction{PyErr_Occurred()}. This returns the current exception object, -or \NULL{} if no exception has occurred. You normally don't need -to call \cfunction{PyErr_Occurred()} to see whether an error occurred in a -function call, since you should be able to tell from the return value. - -When a function \var{f} that calls another function \var{g} detects -that the latter fails, \var{f} should itself return an error value -(usually \NULL{} or \code{-1}). It should \emph{not} call one of the -\cfunction{PyErr_*()} functions --- one has already been called by \var{g}. -\var{f}'s caller is then supposed to also return an error indication -to \emph{its} caller, again \emph{without} calling \cfunction{PyErr_*()}, -and so on --- the most detailed cause of the error was already -reported by the function that first detected it. Once the error -reaches the Python interpreter's main loop, this aborts the currently -executing Python code and tries to find an exception handler specified -by the Python programmer. - -(There are situations where a module can actually give a more detailed -error message by calling another \cfunction{PyErr_*()} function, and in -such cases it is fine to do so. As a general rule, however, this is -not necessary, and can cause information about the cause of the error -to be lost: most operations can fail for a variety of reasons.) - -To ignore an exception set by a function call that failed, the exception -condition must be cleared explicitly by calling \cfunction{PyErr_Clear()}. -The only time C code should call \cfunction{PyErr_Clear()} is if it doesn't -want to pass the error on to the interpreter but wants to handle it -completely by itself (possibly by trying something else, or pretending -nothing went wrong). - -Every failing \cfunction{malloc()} call must be turned into an -exception --- the direct caller of \cfunction{malloc()} (or -\cfunction{realloc()}) must call \cfunction{PyErr_NoMemory()} and -return a failure indicator itself. All the object-creating functions -(for example, \cfunction{PyInt_FromLong()}) already do this, so this -note is only relevant to those who call \cfunction{malloc()} directly. - -Also note that, with the important exception of -\cfunction{PyArg_ParseTuple()} and friends, functions that return an -integer status usually return a positive value or zero for success and -\code{-1} for failure, like \UNIX{} system calls. - -Finally, be careful to clean up garbage (by making -\cfunction{Py_XDECREF()} or \cfunction{Py_DECREF()} calls for objects -you have already created) when you return an error indicator! - -The choice of which exception to raise is entirely yours. There are -predeclared C objects corresponding to all built-in Python exceptions, -such as \cdata{PyExc_ZeroDivisionError}, which you can use directly. -Of course, you should choose exceptions wisely --- don't use -\cdata{PyExc_TypeError} to mean that a file couldn't be opened (that -should probably be \cdata{PyExc_IOError}). If something's wrong with -the argument list, the \cfunction{PyArg_ParseTuple()} function usually -raises \cdata{PyExc_TypeError}. If you have an argument whose value -must be in a particular range or must satisfy other conditions, -\cdata{PyExc_ValueError} is appropriate. - -You can also define a new exception that is unique to your module. -For this, you usually declare a static object variable at the -beginning of your file: - -\begin{verbatim} -static PyObject *SpamError; -\end{verbatim} - -and initialize it in your module's initialization function -(\cfunction{initspam()}) with an exception object (leaving out -the error checking for now): - -\begin{verbatim} -PyMODINIT_FUNC -initspam(void) -{ - PyObject *m; - - m = Py_InitModule("spam", SpamMethods); - if (m == NULL) - return; - - SpamError = PyErr_NewException("spam.error", NULL, NULL); - Py_INCREF(SpamError); - PyModule_AddObject(m, "error", SpamError); -} -\end{verbatim} - -Note that the Python name for the exception object is -\exception{spam.error}. The \cfunction{PyErr_NewException()} function -may create a class with the base class being \exception{Exception} -(unless another class is passed in instead of \NULL), described in the -\citetitle[../lib/lib.html]{Python Library Reference} under ``Built-in -Exceptions.'' - -Note also that the \cdata{SpamError} variable retains a reference to -the newly created exception class; this is intentional! Since the -exception could be removed from the module by external code, an owned -reference to the class is needed to ensure that it will not be -discarded, causing \cdata{SpamError} to become a dangling pointer. -Should it become a dangling pointer, C code which raises the exception -could cause a core dump or other unintended side effects. - -We discuss the use of PyMODINIT_FUNC as a function return type later in this -sample. - -\section{Back to the Example - \label{backToExample}} - -Going back to our example function, you should now be able to -understand this statement: - -\begin{verbatim} - if (!PyArg_ParseTuple(args, "s", &command)) - return NULL; -\end{verbatim} - -It returns \NULL{} (the error indicator for functions returning -object pointers) if an error is detected in the argument list, relying -on the exception set by \cfunction{PyArg_ParseTuple()}. Otherwise the -string value of the argument has been copied to the local variable -\cdata{command}. This is a pointer assignment and you are not supposed -to modify the string to which it points (so in Standard C, the variable -\cdata{command} should properly be declared as \samp{const char -*command}). - -The next statement is a call to the \UNIX{} function -\cfunction{system()}, passing it the string we just got from -\cfunction{PyArg_ParseTuple()}: - -\begin{verbatim} - sts = system(command); -\end{verbatim} - -Our \function{spam.system()} function must return the value of -\cdata{sts} as a Python object. This is done using the function -\cfunction{Py_BuildValue()}, which is something like the inverse of -\cfunction{PyArg_ParseTuple()}: it takes a format string and an -arbitrary number of C values, and returns a new Python object. -More info on \cfunction{Py_BuildValue()} is given later. - -\begin{verbatim} - return Py_BuildValue("i", sts); -\end{verbatim} - -In this case, it will return an integer object. (Yes, even integers -are objects on the heap in Python!) - -If you have a C function that returns no useful argument (a function -returning \ctype{void}), the corresponding Python function must return -\code{None}. You need this idiom to do so (which is implemented by the -\csimplemacro{Py_RETURN_NONE} macro): - -\begin{verbatim} - Py_INCREF(Py_None); - return Py_None; -\end{verbatim} - -\cdata{Py_None} is the C name for the special Python object -\code{None}. It is a genuine Python object rather than a \NULL{} -pointer, which means ``error'' in most contexts, as we have seen. - - -\section{The Module's Method Table and Initialization Function - \label{methodTable}} - -I promised to show how \cfunction{spam_system()} is called from Python -programs. First, we need to list its name and address in a ``method -table'': - -\begin{verbatim} -static PyMethodDef SpamMethods[] = { - ... - {"system", spam_system, METH_VARARGS, - "Execute a shell command."}, - ... - {NULL, NULL, 0, NULL} /* Sentinel */ -}; -\end{verbatim} - -Note the third entry (\samp{METH_VARARGS}). This is a flag telling -the interpreter the calling convention to be used for the C -function. It should normally always be \samp{METH_VARARGS} or -\samp{METH_VARARGS | METH_KEYWORDS}; a value of \code{0} means that an -obsolete variant of \cfunction{PyArg_ParseTuple()} is used. - -When using only \samp{METH_VARARGS}, the function should expect -the Python-level parameters to be passed in as a tuple acceptable for -parsing via \cfunction{PyArg_ParseTuple()}; more information on this -function is provided below. - -The \constant{METH_KEYWORDS} bit may be set in the third field if -keyword arguments should be passed to the function. In this case, the -C function should accept a third \samp{PyObject *} parameter which -will be a dictionary of keywords. Use -\cfunction{PyArg_ParseTupleAndKeywords()} to parse the arguments to -such a function. - -The method table must be passed to the interpreter in the module's -initialization function. The initialization function must be named -\cfunction{init\var{name}()}, where \var{name} is the name of the -module, and should be the only non-\keyword{static} item defined in -the module file: - -\begin{verbatim} -PyMODINIT_FUNC -initspam(void) -{ - (void) Py_InitModule("spam", SpamMethods); -} -\end{verbatim} - -Note that PyMODINIT_FUNC declares the function as \code{void} return type, -declares any special linkage declarations required by the platform, and for -\Cpp{} declares the function as \code{extern "C"}. - -When the Python program imports module \module{spam} for the first -time, \cfunction{initspam()} is called. (See below for comments about -embedding Python.) It calls -\cfunction{Py_InitModule()}, which creates a ``module object'' (which -is inserted in the dictionary \code{sys.modules} under the key -\code{"spam"}), and inserts built-in function objects into the newly -created module based upon the table (an array of \ctype{PyMethodDef} -structures) that was passed as its second argument. -\cfunction{Py_InitModule()} returns a pointer to the module object -that it creates (which is unused here). It may abort with a fatal error -for certain errors, or return \NULL{} if the module could not be -initialized satisfactorily. - -When embedding Python, the \cfunction{initspam()} function is not -called automatically unless there's an entry in the -\cdata{_PyImport_Inittab} table. The easiest way to handle this is to -statically initialize your statically-linked modules by directly -calling \cfunction{initspam()} after the call to -\cfunction{Py_Initialize()}: - -\begin{verbatim} -int -main(int argc, char *argv[]) -{ - /* Pass argv[0] to the Python interpreter */ - Py_SetProgramName(argv[0]); - - /* Initialize the Python interpreter. Required. */ - Py_Initialize(); - - /* Add a static module */ - initspam(); -\end{verbatim} - -An example may be found in the file \file{Demo/embed/demo.c} in the -Python source distribution. - -\note{Removing entries from \code{sys.modules} or importing -compiled modules into multiple interpreters within a process (or -following a \cfunction{fork()} without an intervening -\cfunction{exec()}) can create problems for some extension modules. -Extension module authors should exercise caution when initializing -internal data structures. -Note also that the \function{reload()} function can be used with -extension modules, and will call the module initialization function -(\cfunction{initspam()} in the example), but will not load the module -again if it was loaded from a dynamically loadable object file -(\file{.so} on \UNIX, \file{.dll} on Windows).} - -A more substantial example module is included in the Python source -distribution as \file{Modules/xxmodule.c}. This file may be used as a -template or simply read as an example. The \program{modulator.py} -script included in the source distribution or Windows install provides -a simple graphical user interface for declaring the functions and -objects which a module should implement, and can generate a template -which can be filled in. The script lives in the -\file{Tools/modulator/} directory; see the \file{README} file there -for more information. - - -\section{Compilation and Linkage - \label{compilation}} - -There are two more things to do before you can use your new extension: -compiling and linking it with the Python system. If you use dynamic -loading, the details may depend on the style of dynamic loading your -system uses; see the chapters about building extension modules -(chapter \ref{building}) and additional information that pertains only -to building on Windows (chapter \ref{building-on-windows}) for more -information about this. - -If you can't use dynamic loading, or if you want to make your module a -permanent part of the Python interpreter, you will have to change the -configuration setup and rebuild the interpreter. Luckily, this is -very simple on \UNIX: just place your file (\file{spammodule.c} for -example) in the \file{Modules/} directory of an unpacked source -distribution, add a line to the file \file{Modules/Setup.local} -describing your file: - -\begin{verbatim} -spam spammodule.o -\end{verbatim} - -and rebuild the interpreter by running \program{make} in the toplevel -directory. You can also run \program{make} in the \file{Modules/} -subdirectory, but then you must first rebuild \file{Makefile} -there by running `\program{make} Makefile'. (This is necessary each -time you change the \file{Setup} file.) - -If your module requires additional libraries to link with, these can -be listed on the line in the configuration file as well, for instance: - -\begin{verbatim} -spam spammodule.o -lX11 -\end{verbatim} - -\section{Calling Python Functions from C - \label{callingPython}} - -So far we have concentrated on making C functions callable from -Python. The reverse is also useful: calling Python functions from C. -This is especially the case for libraries that support so-called -``callback'' functions. If a C interface makes use of callbacks, the -equivalent Python often needs to provide a callback mechanism to the -Python programmer; the implementation will require calling the Python -callback functions from a C callback. Other uses are also imaginable. - -Fortunately, the Python interpreter is easily called recursively, and -there is a standard interface to call a Python function. (I won't -dwell on how to call the Python parser with a particular string as -input --- if you're interested, have a look at the implementation of -the \programopt{-c} command line option in \file{Python/pythonmain.c} -from the Python source code.) - -Calling a Python function is easy. First, the Python program must -somehow pass you the Python function object. You should provide a -function (or some other interface) to do this. When this function is -called, save a pointer to the Python function object (be careful to -\cfunction{Py_INCREF()} it!) in a global variable --- or wherever you -see fit. For example, the following function might be part of a module -definition: - -\begin{verbatim} -static PyObject *my_callback = NULL; - -static PyObject * -my_set_callback(PyObject *dummy, PyObject *args) -{ - PyObject *result = NULL; - PyObject *temp; - - if (PyArg_ParseTuple(args, "O:set_callback", &temp)) { - if (!PyCallable_Check(temp)) { - PyErr_SetString(PyExc_TypeError, "parameter must be callable"); - return NULL; - } - Py_XINCREF(temp); /* Add a reference to new callback */ - Py_XDECREF(my_callback); /* Dispose of previous callback */ - my_callback = temp; /* Remember new callback */ - /* Boilerplate to return "None" */ - Py_INCREF(Py_None); - result = Py_None; - } - return result; -} -\end{verbatim} - -This function must be registered with the interpreter using the -\constant{METH_VARARGS} flag; this is described in section -\ref{methodTable}, ``The Module's Method Table and Initialization -Function.'' The \cfunction{PyArg_ParseTuple()} function and its -arguments are documented in section~\ref{parseTuple}, ``Extracting -Parameters in Extension Functions.'' - -The macros \cfunction{Py_XINCREF()} and \cfunction{Py_XDECREF()} -increment/decrement the reference count of an object and are safe in -the presence of \NULL{} pointers (but note that \var{temp} will not be -\NULL{} in this context). More info on them in -section~\ref{refcounts}, ``Reference Counts.'' - -Later, when it is time to call the function, you call the C function -\cfunction{PyEval_CallObject()}.\ttindex{PyEval_CallObject()} This -function has two arguments, both pointers to arbitrary Python objects: -the Python function, and the argument list. The argument list must -always be a tuple object, whose length is the number of arguments. To -call the Python function with no arguments, pass an empty tuple; to -call it with one argument, pass a singleton tuple. -\cfunction{Py_BuildValue()} returns a tuple when its format string -consists of zero or more format codes between parentheses. For -example: - -\begin{verbatim} - int arg; - PyObject *arglist; - PyObject *result; - ... - arg = 123; - ... - /* Time to call the callback */ - arglist = Py_BuildValue("(i)", arg); - result = PyEval_CallObject(my_callback, arglist); - Py_DECREF(arglist); -\end{verbatim} - -\cfunction{PyEval_CallObject()} returns a Python object pointer: this is -the return value of the Python function. \cfunction{PyEval_CallObject()} is -``reference-count-neutral'' with respect to its arguments. In the -example a new tuple was created to serve as the argument list, which -is \cfunction{Py_DECREF()}-ed immediately after the call. - -The return value of \cfunction{PyEval_CallObject()} is ``new'': either it -is a brand new object, or it is an existing object whose reference -count has been incremented. So, unless you want to save it in a -global variable, you should somehow \cfunction{Py_DECREF()} the result, -even (especially!) if you are not interested in its value. - -Before you do this, however, it is important to check that the return -value isn't \NULL. If it is, the Python function terminated by -raising an exception. If the C code that called -\cfunction{PyEval_CallObject()} is called from Python, it should now -return an error indication to its Python caller, so the interpreter -can print a stack trace, or the calling Python code can handle the -exception. If this is not possible or desirable, the exception should -be cleared by calling \cfunction{PyErr_Clear()}. For example: - -\begin{verbatim} - if (result == NULL) - return NULL; /* Pass error back */ - ...use result... - Py_DECREF(result); -\end{verbatim} - -Depending on the desired interface to the Python callback function, -you may also have to provide an argument list to -\cfunction{PyEval_CallObject()}. In some cases the argument list is -also provided by the Python program, through the same interface that -specified the callback function. It can then be saved and used in the -same manner as the function object. In other cases, you may have to -construct a new tuple to pass as the argument list. The simplest way -to do this is to call \cfunction{Py_BuildValue()}. For example, if -you want to pass an integral event code, you might use the following -code: - -\begin{verbatim} - PyObject *arglist; - ... - arglist = Py_BuildValue("(l)", eventcode); - result = PyEval_CallObject(my_callback, arglist); - Py_DECREF(arglist); - if (result == NULL) - return NULL; /* Pass error back */ - /* Here maybe use the result */ - Py_DECREF(result); -\end{verbatim} - -Note the placement of \samp{Py_DECREF(arglist)} immediately after the -call, before the error check! Also note that strictly spoken this -code is not complete: \cfunction{Py_BuildValue()} may run out of -memory, and this should be checked. - - -\section{Extracting Parameters in Extension Functions - \label{parseTuple}} - -\ttindex{PyArg_ParseTuple()} - -The \cfunction{PyArg_ParseTuple()} function is declared as follows: - -\begin{verbatim} -int PyArg_ParseTuple(PyObject *arg, char *format, ...); -\end{verbatim} - -The \var{arg} argument must be a tuple object containing an argument -list passed from Python to a C function. The \var{format} argument -must be a format string, whose syntax is explained in -``\ulink{Parsing arguments and building -values}{../api/arg-parsing.html}'' in the -\citetitle[../api/api.html]{Python/C API Reference Manual}. The -remaining arguments must be addresses of variables whose type is -determined by the format string. - -Note that while \cfunction{PyArg_ParseTuple()} checks that the Python -arguments have the required types, it cannot check the validity of the -addresses of C variables passed to the call: if you make mistakes -there, your code will probably crash or at least overwrite random bits -in memory. So be careful! - -Note that any Python object references which are provided to the -caller are \emph{borrowed} references; do not decrement their -reference count! - -Some example calls: - -\begin{verbatim} - int ok; - int i, j; - long k, l; - const char *s; - int size; - - ok = PyArg_ParseTuple(args, ""); /* No arguments */ - /* Python call: f() */ -\end{verbatim} - -\begin{verbatim} - ok = PyArg_ParseTuple(args, "s", &s); /* A string */ - /* Possible Python call: f('whoops!') */ -\end{verbatim} - -\begin{verbatim} - ok = PyArg_ParseTuple(args, "lls", &k, &l, &s); /* Two longs and a string */ - /* Possible Python call: f(1, 2, 'three') */ -\end{verbatim} - -\begin{verbatim} - ok = PyArg_ParseTuple(args, "(ii)s#", &i, &j, &s, &size); - /* A pair of ints and a string, whose size is also returned */ - /* Possible Python call: f((1, 2), 'three') */ -\end{verbatim} - -\begin{verbatim} - { - const char *file; - const char *mode = "r"; - int bufsize = 0; - ok = PyArg_ParseTuple(args, "s|si", &file, &mode, &bufsize); - /* A string, and optionally another string and an integer */ - /* Possible Python calls: - f('spam') - f('spam', 'w') - f('spam', 'wb', 100000) */ - } -\end{verbatim} - -\begin{verbatim} - { - int left, top, right, bottom, h, v; - ok = PyArg_ParseTuple(args, "((ii)(ii))(ii)", - &left, &top, &right, &bottom, &h, &v); - /* A rectangle and a point */ - /* Possible Python call: - f(((0, 0), (400, 300)), (10, 10)) */ - } -\end{verbatim} - -\begin{verbatim} - { - Py_complex c; - ok = PyArg_ParseTuple(args, "D:myfunction", &c); - /* a complex, also providing a function name for errors */ - /* Possible Python call: myfunction(1+2j) */ - } -\end{verbatim} - - -\section{Keyword Parameters for Extension Functions - \label{parseTupleAndKeywords}} - -\ttindex{PyArg_ParseTupleAndKeywords()} - -The \cfunction{PyArg_ParseTupleAndKeywords()} function is declared as -follows: - -\begin{verbatim} -int PyArg_ParseTupleAndKeywords(PyObject *arg, PyObject *kwdict, - char *format, char *kwlist[], ...); -\end{verbatim} - -The \var{arg} and \var{format} parameters are identical to those of the -\cfunction{PyArg_ParseTuple()} function. The \var{kwdict} parameter -is the dictionary of keywords received as the third parameter from the -Python runtime. The \var{kwlist} parameter is a \NULL-terminated -list of strings which identify the parameters; the names are matched -with the type information from \var{format} from left to right. On -success, \cfunction{PyArg_ParseTupleAndKeywords()} returns true, -otherwise it returns false and raises an appropriate exception. - -\note{Nested tuples cannot be parsed when using keyword -arguments! Keyword parameters passed in which are not present in the -\var{kwlist} will cause \exception{TypeError} to be raised.} - -Here is an example module which uses keywords, based on an example by -Geoff Philbrick (\email{philbrick@hks.com}):% -\index{Philbrick, Geoff} - -\begin{verbatim} -#include "Python.h" - -static PyObject * -keywdarg_parrot(PyObject *self, PyObject *args, PyObject *keywds) -{ - int voltage; - char *state = "a stiff"; - char *action = "voom"; - char *type = "Norwegian Blue"; - - static char *kwlist[] = {"voltage", "state", "action", "type", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, keywds, "i|sss", kwlist, - &voltage, &state, &action, &type)) - return NULL; - - printf("-- This parrot wouldn't %s if you put %i Volts through it.\n", - action, voltage); - printf("-- Lovely plumage, the %s -- It's %s!\n", type, state); - - Py_INCREF(Py_None); - - return Py_None; -} - -static PyMethodDef keywdarg_methods[] = { - /* The cast of the function is necessary since PyCFunction values - * only take two PyObject* parameters, and keywdarg_parrot() takes - * three. - */ - {"parrot", (PyCFunction)keywdarg_parrot, METH_VARARGS | METH_KEYWORDS, - "Print a lovely skit to standard output."}, - {NULL, NULL, 0, NULL} /* sentinel */ -}; -\end{verbatim} - -\begin{verbatim} -void -initkeywdarg(void) -{ - /* Create the module and add the functions */ - Py_InitModule("keywdarg", keywdarg_methods); -} -\end{verbatim} - - -\section{Building Arbitrary Values - \label{buildValue}} - -This function is the counterpart to \cfunction{PyArg_ParseTuple()}. It is -declared as follows: - -\begin{verbatim} -PyObject *Py_BuildValue(char *format, ...); -\end{verbatim} - -It recognizes a set of format units similar to the ones recognized by -\cfunction{PyArg_ParseTuple()}, but the arguments (which are input to the -function, not output) must not be pointers, just values. It returns a -new Python object, suitable for returning from a C function called -from Python. - -One difference with \cfunction{PyArg_ParseTuple()}: while the latter -requires its first argument to be a tuple (since Python argument lists -are always represented as tuples internally), -\cfunction{Py_BuildValue()} does not always build a tuple. It builds -a tuple only if its format string contains two or more format units. -If the format string is empty, it returns \code{None}; if it contains -exactly one format unit, it returns whatever object is described by -that format unit. To force it to return a tuple of size 0 or one, -parenthesize the format string. - -Examples (to the left the call, to the right the resulting Python value): - -\begin{verbatim} - Py_BuildValue("") None - Py_BuildValue("i", 123) 123 - Py_BuildValue("iii", 123, 456, 789) (123, 456, 789) - Py_BuildValue("s", "hello") 'hello' - Py_BuildValue("ss", "hello", "world") ('hello', 'world') - Py_BuildValue("s#", "hello", 4) 'hell' - Py_BuildValue("()") () - Py_BuildValue("(i)", 123) (123,) - Py_BuildValue("(ii)", 123, 456) (123, 456) - Py_BuildValue("(i,i)", 123, 456) (123, 456) - Py_BuildValue("[i,i]", 123, 456) [123, 456] - Py_BuildValue("{s:i,s:i}", - "abc", 123, "def", 456) {'abc': 123, 'def': 456} - Py_BuildValue("((ii)(ii)) (ii)", - 1, 2, 3, 4, 5, 6) (((1, 2), (3, 4)), (5, 6)) -\end{verbatim} - - -\section{Reference Counts - \label{refcounts}} - -In languages like C or \Cpp, the programmer is responsible for -dynamic allocation and deallocation of memory on the heap. In C, -this is done using the functions \cfunction{malloc()} and -\cfunction{free()}. In \Cpp, the operators \keyword{new} and -\keyword{delete} are used with essentially the same meaning and -we'll restrict the following discussion to the C case. - -Every block of memory allocated with \cfunction{malloc()} should -eventually be returned to the pool of available memory by exactly one -call to \cfunction{free()}. It is important to call -\cfunction{free()} at the right time. If a block's address is -forgotten but \cfunction{free()} is not called for it, the memory it -occupies cannot be reused until the program terminates. This is -called a \dfn{memory leak}. On the other hand, if a program calls -\cfunction{free()} for a block and then continues to use the block, it -creates a conflict with re-use of the block through another -\cfunction{malloc()} call. This is called \dfn{using freed memory}. -It has the same bad consequences as referencing uninitialized data --- -core dumps, wrong results, mysterious crashes. - -Common causes of memory leaks are unusual paths through the code. For -instance, a function may allocate a block of memory, do some -calculation, and then free the block again. Now a change in the -requirements for the function may add a test to the calculation that -detects an error condition and can return prematurely from the -function. It's easy to forget to free the allocated memory block when -taking this premature exit, especially when it is added later to the -code. Such leaks, once introduced, often go undetected for a long -time: the error exit is taken only in a small fraction of all calls, -and most modern machines have plenty of virtual memory, so the leak -only becomes apparent in a long-running process that uses the leaking -function frequently. Therefore, it's important to prevent leaks from -happening by having a coding convention or strategy that minimizes -this kind of errors. - -Since Python makes heavy use of \cfunction{malloc()} and -\cfunction{free()}, it needs a strategy to avoid memory leaks as well -as the use of freed memory. The chosen method is called -\dfn{reference counting}. The principle is simple: every object -contains a counter, which is incremented when a reference to the -object is stored somewhere, and which is decremented when a reference -to it is deleted. When the counter reaches zero, the last reference -to the object has been deleted and the object is freed. - -An alternative strategy is called \dfn{automatic garbage collection}. -(Sometimes, reference counting is also referred to as a garbage -collection strategy, hence my use of ``automatic'' to distinguish the -two.) The big advantage of automatic garbage collection is that the -user doesn't need to call \cfunction{free()} explicitly. (Another claimed -advantage is an improvement in speed or memory usage --- this is no -hard fact however.) The disadvantage is that for C, there is no -truly portable automatic garbage collector, while reference counting -can be implemented portably (as long as the functions \cfunction{malloc()} -and \cfunction{free()} are available --- which the C Standard guarantees). -Maybe some day a sufficiently portable automatic garbage collector -will be available for C. Until then, we'll have to live with -reference counts. - -While Python uses the traditional reference counting implementation, -it also offers a cycle detector that works to detect reference -cycles. This allows applications to not worry about creating direct -or indirect circular references; these are the weakness of garbage -collection implemented using only reference counting. Reference -cycles consist of objects which contain (possibly indirect) references -to themselves, so that each object in the cycle has a reference count -which is non-zero. Typical reference counting implementations are not -able to reclaim the memory belonging to any objects in a reference -cycle, or referenced from the objects in the cycle, even though there -are no further references to the cycle itself. - -The cycle detector is able to detect garbage cycles and can reclaim -them so long as there are no finalizers implemented in Python -(\method{__del__()} methods). When there are such finalizers, the -detector exposes the cycles through the \ulink{\module{gc} -module}{../lib/module-gc.html} (specifically, the \code{garbage} -variable in that module). The \module{gc} module also exposes a way -to run the detector (the \function{collect()} function), as well as -configuration interfaces and the ability to disable the detector at -runtime. The cycle detector is considered an optional component; -though it is included by default, it can be disabled at build time -using the \longprogramopt{without-cycle-gc} option to the -\program{configure} script on \UNIX{} platforms (including Mac OS X) -or by removing the definition of \code{WITH_CYCLE_GC} in the -\file{pyconfig.h} header on other platforms. If the cycle detector is -disabled in this way, the \module{gc} module will not be available. - - -\subsection{Reference Counting in Python - \label{refcountsInPython}} - -There are two macros, \code{Py_INCREF(x)} and \code{Py_DECREF(x)}, -which handle the incrementing and decrementing of the reference count. -\cfunction{Py_DECREF()} also frees the object when the count reaches zero. -For flexibility, it doesn't call \cfunction{free()} directly --- rather, it -makes a call through a function pointer in the object's \dfn{type -object}. For this purpose (and others), every object also contains a -pointer to its type object. - -The big question now remains: when to use \code{Py_INCREF(x)} and -\code{Py_DECREF(x)}? Let's first introduce some terms. Nobody -``owns'' an object; however, you can \dfn{own a reference} to an -object. An object's reference count is now defined as the number of -owned references to it. The owner of a reference is responsible for -calling \cfunction{Py_DECREF()} when the reference is no longer -needed. Ownership of a reference can be transferred. There are three -ways to dispose of an owned reference: pass it on, store it, or call -\cfunction{Py_DECREF()}. Forgetting to dispose of an owned reference -creates a memory leak. - -It is also possible to \dfn{borrow}\footnote{The metaphor of -``borrowing'' a reference is not completely correct: the owner still -has a copy of the reference.} a reference to an object. The borrower -of a reference should not call \cfunction{Py_DECREF()}. The borrower must -not hold on to the object longer than the owner from which it was -borrowed. Using a borrowed reference after the owner has disposed of -it risks using freed memory and should be avoided -completely.\footnote{Checking that the reference count is at least 1 -\strong{does not work} --- the reference count itself could be in -freed memory and may thus be reused for another object!} - -The advantage of borrowing over owning a reference is that you don't -need to take care of disposing of the reference on all possible paths -through the code --- in other words, with a borrowed reference you -don't run the risk of leaking when a premature exit is taken. The -disadvantage of borrowing over leaking is that there are some subtle -situations where in seemingly correct code a borrowed reference can be -used after the owner from which it was borrowed has in fact disposed -of it. - -A borrowed reference can be changed into an owned reference by calling -\cfunction{Py_INCREF()}. This does not affect the status of the owner from -which the reference was borrowed --- it creates a new owned reference, -and gives full owner responsibilities (the new owner must -dispose of the reference properly, as well as the previous owner). - - -\subsection{Ownership Rules - \label{ownershipRules}} - -Whenever an object reference is passed into or out of a function, it -is part of the function's interface specification whether ownership is -transferred with the reference or not. - -Most functions that return a reference to an object pass on ownership -with the reference. In particular, all functions whose function it is -to create a new object, such as \cfunction{PyInt_FromLong()} and -\cfunction{Py_BuildValue()}, pass ownership to the receiver. Even if -the object is not actually new, you still receive ownership of a new -reference to that object. For instance, \cfunction{PyInt_FromLong()} -maintains a cache of popular values and can return a reference to a -cached item. - -Many functions that extract objects from other objects also transfer -ownership with the reference, for instance -\cfunction{PyObject_GetAttrString()}. The picture is less clear, here, -however, since a few common routines are exceptions: -\cfunction{PyTuple_GetItem()}, \cfunction{PyList_GetItem()}, -\cfunction{PyDict_GetItem()}, and \cfunction{PyDict_GetItemString()} -all return references that you borrow from the tuple, list or -dictionary. - -The function \cfunction{PyImport_AddModule()} also returns a borrowed -reference, even though it may actually create the object it returns: -this is possible because an owned reference to the object is stored in -\code{sys.modules}. - -When you pass an object reference into another function, in general, -the function borrows the reference from you --- if it needs to store -it, it will use \cfunction{Py_INCREF()} to become an independent -owner. There are exactly two important exceptions to this rule: -\cfunction{PyTuple_SetItem()} and \cfunction{PyList_SetItem()}. These -functions take over ownership of the item passed to them --- even if -they fail! (Note that \cfunction{PyDict_SetItem()} and friends don't -take over ownership --- they are ``normal.'') - -When a C function is called from Python, it borrows references to its -arguments from the caller. The caller owns a reference to the object, -so the borrowed reference's lifetime is guaranteed until the function -returns. Only when such a borrowed reference must be stored or passed -on, it must be turned into an owned reference by calling -\cfunction{Py_INCREF()}. - -The object reference returned from a C function that is called from -Python must be an owned reference --- ownership is transferred from -the function to its caller. - - -\subsection{Thin Ice - \label{thinIce}} - -There are a few situations where seemingly harmless use of a borrowed -reference can lead to problems. These all have to do with implicit -invocations of the interpreter, which can cause the owner of a -reference to dispose of it. - -The first and most important case to know about is using -\cfunction{Py_DECREF()} on an unrelated object while borrowing a -reference to a list item. For instance: - -\begin{verbatim} -void -bug(PyObject *list) -{ - PyObject *item = PyList_GetItem(list, 0); - - PyList_SetItem(list, 1, PyInt_FromLong(0L)); - PyObject_Print(item, stdout, 0); /* BUG! */ -} -\end{verbatim} - -This function first borrows a reference to \code{list[0]}, then -replaces \code{list[1]} with the value \code{0}, and finally prints -the borrowed reference. Looks harmless, right? But it's not! - -Let's follow the control flow into \cfunction{PyList_SetItem()}. The list -owns references to all its items, so when item 1 is replaced, it has -to dispose of the original item 1. Now let's suppose the original -item 1 was an instance of a user-defined class, and let's further -suppose that the class defined a \method{__del__()} method. If this -class instance has a reference count of 1, disposing of it will call -its \method{__del__()} method. - -Since it is written in Python, the \method{__del__()} method can execute -arbitrary Python code. Could it perhaps do something to invalidate -the reference to \code{item} in \cfunction{bug()}? You bet! Assuming -that the list passed into \cfunction{bug()} is accessible to the -\method{__del__()} method, it could execute a statement to the effect of -\samp{del list[0]}, and assuming this was the last reference to that -object, it would free the memory associated with it, thereby -invalidating \code{item}. - -The solution, once you know the source of the problem, is easy: -temporarily increment the reference count. The correct version of the -function reads: - -\begin{verbatim} -void -no_bug(PyObject *list) -{ - PyObject *item = PyList_GetItem(list, 0); - - Py_INCREF(item); - PyList_SetItem(list, 1, PyInt_FromLong(0L)); - PyObject_Print(item, stdout, 0); - Py_DECREF(item); -} -\end{verbatim} - -This is a true story. An older version of Python contained variants -of this bug and someone spent a considerable amount of time in a C -debugger to figure out why his \method{__del__()} methods would fail... - -The second case of problems with a borrowed reference is a variant -involving threads. Normally, multiple threads in the Python -interpreter can't get in each other's way, because there is a global -lock protecting Python's entire object space. However, it is possible -to temporarily release this lock using the macro -\csimplemacro{Py_BEGIN_ALLOW_THREADS}, and to re-acquire it using -\csimplemacro{Py_END_ALLOW_THREADS}. This is common around blocking -I/O calls, to let other threads use the processor while waiting for -the I/O to complete. Obviously, the following function has the same -problem as the previous one: - -\begin{verbatim} -void -bug(PyObject *list) -{ - PyObject *item = PyList_GetItem(list, 0); - Py_BEGIN_ALLOW_THREADS - ...some blocking I/O call... - Py_END_ALLOW_THREADS - PyObject_Print(item, stdout, 0); /* BUG! */ -} -\end{verbatim} - - -\subsection{NULL Pointers - \label{nullPointers}} - -In general, functions that take object references as arguments do not -expect you to pass them \NULL{} pointers, and will dump core (or -cause later core dumps) if you do so. Functions that return object -references generally return \NULL{} only to indicate that an -exception occurred. The reason for not testing for \NULL{} -arguments is that functions often pass the objects they receive on to -other function --- if each function were to test for \NULL, -there would be a lot of redundant tests and the code would run more -slowly. - -It is better to test for \NULL{} only at the ``source:'' when a -pointer that may be \NULL{} is received, for example, from -\cfunction{malloc()} or from a function that may raise an exception. - -The macros \cfunction{Py_INCREF()} and \cfunction{Py_DECREF()} -do not check for \NULL{} pointers --- however, their variants -\cfunction{Py_XINCREF()} and \cfunction{Py_XDECREF()} do. - -The macros for checking for a particular object type -(\code{Py\var{type}_Check()}) don't check for \NULL{} pointers --- -again, there is much code that calls several of these in a row to test -an object against various different expected types, and this would -generate redundant tests. There are no variants with \NULL{} -checking. - -The C function calling mechanism guarantees that the argument list -passed to C functions (\code{args} in the examples) is never -\NULL{} --- in fact it guarantees that it is always a tuple.\footnote{ -These guarantees don't hold when you use the ``old'' style -calling convention --- this is still found in much existing code.} - -It is a severe error to ever let a \NULL{} pointer ``escape'' to -the Python user. - -% Frank Stajano: -% A pedagogically buggy example, along the lines of the previous listing, -% would be helpful here -- showing in more concrete terms what sort of -% actions could cause the problem. I can't very well imagine it from the -% description. - - -\section{Writing Extensions in \Cpp - \label{cplusplus}} - -It is possible to write extension modules in \Cpp. Some restrictions -apply. If the main program (the Python interpreter) is compiled and -linked by the C compiler, global or static objects with constructors -cannot be used. This is not a problem if the main program is linked -by the \Cpp{} compiler. Functions that will be called by the -Python interpreter (in particular, module initialization functions) -have to be declared using \code{extern "C"}. -It is unnecessary to enclose the Python header files in -\code{extern "C" \{...\}} --- they use this form already if the symbol -\samp{__cplusplus} is defined (all recent \Cpp{} compilers define this -symbol). - - -\section{Providing a C API for an Extension Module - \label{using-cobjects}} -\sectionauthor{Konrad Hinsen}{hinsen@cnrs-orleans.fr} - -Many extension modules just provide new functions and types to be -used from Python, but sometimes the code in an extension module can -be useful for other extension modules. For example, an extension -module could implement a type ``collection'' which works like lists -without order. Just like the standard Python list type has a C API -which permits extension modules to create and manipulate lists, this -new collection type should have a set of C functions for direct -manipulation from other extension modules. - -At first sight this seems easy: just write the functions (without -declaring them \keyword{static}, of course), provide an appropriate -header file, and document the C API. And in fact this would work if -all extension modules were always linked statically with the Python -interpreter. When modules are used as shared libraries, however, the -symbols defined in one module may not be visible to another module. -The details of visibility depend on the operating system; some systems -use one global namespace for the Python interpreter and all extension -modules (Windows, for example), whereas others require an explicit -list of imported symbols at module link time (AIX is one example), or -offer a choice of different strategies (most Unices). And even if -symbols are globally visible, the module whose functions one wishes to -call might not have been loaded yet! - -Portability therefore requires not to make any assumptions about -symbol visibility. This means that all symbols in extension modules -should be declared \keyword{static}, except for the module's -initialization function, in order to avoid name clashes with other -extension modules (as discussed in section~\ref{methodTable}). And it -means that symbols that \emph{should} be accessible from other -extension modules must be exported in a different way. - -Python provides a special mechanism to pass C-level information -(pointers) from one extension module to another one: CObjects. -A CObject is a Python data type which stores a pointer (\ctype{void -*}). CObjects can only be created and accessed via their C API, but -they can be passed around like any other Python object. In particular, -they can be assigned to a name in an extension module's namespace. -Other extension modules can then import this module, retrieve the -value of this name, and then retrieve the pointer from the CObject. - -There are many ways in which CObjects can be used to export the C API -of an extension module. Each name could get its own CObject, or all C -API pointers could be stored in an array whose address is published in -a CObject. And the various tasks of storing and retrieving the pointers -can be distributed in different ways between the module providing the -code and the client modules. - -The following example demonstrates an approach that puts most of the -burden on the writer of the exporting module, which is appropriate -for commonly used library modules. It stores all C API pointers -(just one in the example!) in an array of \ctype{void} pointers which -becomes the value of a CObject. The header file corresponding to -the module provides a macro that takes care of importing the module -and retrieving its C API pointers; client modules only have to call -this macro before accessing the C API. - -The exporting module is a modification of the \module{spam} module from -section~\ref{simpleExample}. The function \function{spam.system()} -does not call the C library function \cfunction{system()} directly, -but a function \cfunction{PySpam_System()}, which would of course do -something more complicated in reality (such as adding ``spam'' to -every command). This function \cfunction{PySpam_System()} is also -exported to other extension modules. - -The function \cfunction{PySpam_System()} is a plain C function, -declared \keyword{static} like everything else: - -\begin{verbatim} -static int -PySpam_System(const char *command) -{ - return system(command); -} -\end{verbatim} - -The function \cfunction{spam_system()} is modified in a trivial way: - -\begin{verbatim} -static PyObject * -spam_system(PyObject *self, PyObject *args) -{ - const char *command; - int sts; - - if (!PyArg_ParseTuple(args, "s", &command)) - return NULL; - sts = PySpam_System(command); - return Py_BuildValue("i", sts); -} -\end{verbatim} - -In the beginning of the module, right after the line - -\begin{verbatim} -#include "Python.h" -\end{verbatim} - -two more lines must be added: - -\begin{verbatim} -#define SPAM_MODULE -#include "spammodule.h" -\end{verbatim} - -The \code{\#define} is used to tell the header file that it is being -included in the exporting module, not a client module. Finally, -the module's initialization function must take care of initializing -the C API pointer array: - -\begin{verbatim} -PyMODINIT_FUNC -initspam(void) -{ - PyObject *m; - static void *PySpam_API[PySpam_API_pointers]; - PyObject *c_api_object; - - m = Py_InitModule("spam", SpamMethods); - if (m == NULL) - return; - - /* Initialize the C API pointer array */ - PySpam_API[PySpam_System_NUM] = (void *)PySpam_System; - - /* Create a CObject containing the API pointer array's address */ - c_api_object = PyCObject_FromVoidPtr((void *)PySpam_API, NULL); - - if (c_api_object != NULL) - PyModule_AddObject(m, "_C_API", c_api_object); -} -\end{verbatim} - -Note that \code{PySpam_API} is declared \keyword{static}; otherwise -the pointer array would disappear when \function{initspam()} terminates! - -The bulk of the work is in the header file \file{spammodule.h}, -which looks like this: - -\begin{verbatim} -#ifndef Py_SPAMMODULE_H -#define Py_SPAMMODULE_H -#ifdef __cplusplus -extern "C" { -#endif - -/* Header file for spammodule */ - -/* C API functions */ -#define PySpam_System_NUM 0 -#define PySpam_System_RETURN int -#define PySpam_System_PROTO (const char *command) - -/* Total number of C API pointers */ -#define PySpam_API_pointers 1 - - -#ifdef SPAM_MODULE -/* This section is used when compiling spammodule.c */ - -static PySpam_System_RETURN PySpam_System PySpam_System_PROTO; - -#else -/* This section is used in modules that use spammodule's API */ - -static void **PySpam_API; - -#define PySpam_System \ - (*(PySpam_System_RETURN (*)PySpam_System_PROTO) PySpam_API[PySpam_System_NUM]) - -/* Return -1 and set exception on error, 0 on success. */ -static int -import_spam(void) -{ - PyObject *module = PyImport_ImportModule("spam"); - - if (module != NULL) { - PyObject *c_api_object = PyObject_GetAttrString(module, "_C_API"); - if (c_api_object == NULL) - return -1; - if (PyCObject_Check(c_api_object)) - PySpam_API = (void **)PyCObject_AsVoidPtr(c_api_object); - Py_DECREF(c_api_object); - } - return 0; -} - -#endif - -#ifdef __cplusplus -} -#endif - -#endif /* !defined(Py_SPAMMODULE_H) */ -\end{verbatim} - -All that a client module must do in order to have access to the -function \cfunction{PySpam_System()} is to call the function (or -rather macro) \cfunction{import_spam()} in its initialization -function: - -\begin{verbatim} -PyMODINIT_FUNC -initclient(void) -{ - PyObject *m; - - m = Py_InitModule("client", ClientMethods); - if (m == NULL) - return; - if (import_spam() < 0) - return; - /* additional initialization can happen here */ -} -\end{verbatim} - -The main disadvantage of this approach is that the file -\file{spammodule.h} is rather complicated. However, the -basic structure is the same for each function that is -exported, so it has to be learned only once. - -Finally it should be mentioned that CObjects offer additional -functionality, which is especially useful for memory allocation and -deallocation of the pointer stored in a CObject. The details -are described in the \citetitle[../api/api.html]{Python/C API -Reference Manual} in the section -``\ulink{CObjects}{../api/cObjects.html}'' and in the implementation -of CObjects (files \file{Include/cobject.h} and -\file{Objects/cobject.c} in the Python source code distribution). |