This is Info file /home/pdm/tmp/Python-1.5.2p1/Doc/ext/python-ext.info, produced by Makeinfo version 1.68 from the input file ext.texi. July 6, 1999 1.5.2  File: python-ext.info, Node: Top, Next: Front Matter, Prev: (dir), Up: (dir) Extending and Embedding the Python Interpreter ********************************************** * Menu: * Front Matter:: * Extending Python with C or C++:: * Building C and C++ Extensions on UNIX:: * Building C and C++ Extensions on Windows:: * Embedding Python in Another Application:: * Miscellaneous Index::  File: python-ext.info, Node: Front Matter, Next: Extending Python with C or C++, Prev: Top, Up: Top Front Matter ************ Copyright (C) 1991-1995 by Stichting Mathematisch Centrum, Amsterdam, The Netherlands. All Rights Reserved Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation, and that the names of Stichting Mathematisch Centrum or CWI or Corporation for National Research Initiatives or CNRI not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. While CWI is the initial source for this software, a modified version is made available by the Corporation for National Research Initiatives (CNRI) at the Internet address `ftp://ftp.python.org'. STICHTING MATHEMATISCH CENTRUM AND CNRI DISCLAIM ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO EVENT SHALL STICHTING MATHEMATISCH CENTRUM OR CNRI BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. *Acknowledgements* The following people have contributed sections to this document: Jim Fulton, Konrad Hinsen, Chris Phoenix, and Neil Schemenauer. Python is an interpreted, object-oriented programming language. This document describes how to write modules in C or C++ to extend the Python interpreter with new modules. Those modules can define new functions but also new object types and their methods. The document also describes how to embed the Python interpreter in another application, for use as an extension language. Finally, it shows how to compile and link extension modules so that they can be loaded dynamically (at run time) into the interpreter, if the underlying operating system supports this feature. This document assumes basic knowledge about Python. For an informal introduction to the language, see the Python Tutorial. The *Python Reference Manual* gives a more formal definition of the language. The *Python Library Reference* documents the existing object types, functions and modules (both built-in and written in Python) that give the language its wide application range. For a detailed description of the whole Python/C API, see the separate *Python/C API Reference Manual*.  File: python-ext.info, Node: Extending Python with C or C++, Next: Building C and C++ Extensions on UNIX, Prev: Front Matter, Up: Top Extending Python with C or C++ ****************************** It is quite easy to add new built-in modules to Python, if you know how to program in C. Such "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 `"Python.h"'. The compilation of an extension module depends on its intended use as well as on your system setup; details are given in a later section. * Menu: * A Simple Example:: * Intermezzo Errors and Exceptions:: * Back to the Example:: * Module's Method Table and Initialization Function:: * Compilation and Linkage:: * Calling Python Functions from C:: * Format Strings for PyArg_ParseTuple:: * Keyword Parsing with PyArg_ParseTupleAndKeywords:: * Py_BuildValue Function:: * Reference Counts:: * Writing Extensions in C++:: * Providing a C API for an Extension Module::  File: python-ext.info, Node: A Simple Example, Next: Intermezzo Errors and Exceptions, Prev: Extending Python with C or C++, Up: Extending Python with C or C++ A Simple Example ================ Let's create an extension module called `spam' (the favorite food of Monty Python fans...) and let's say we want to create a Python interface to the C library function `system()'.(1) 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: >>> import spam >>> status = spam.system("ls -l") Begin by creating a file `spammodule.c'. (In general, if a module is called `spam', the C file containing its implementation is called `spammodule.c'; if the module name is very long, like `spammify', the module name can be just `spammify.c'.) The first line of our file can be: #include "Python.h" which pulls in the Python API (you can add a comment describing the purpose of the module and a copyright notice if you like). All user-visible symbols defined by `"Python.h"' have a prefix of `Py' or `PY', except those defined in standard header files. For convenience, and since they are used extensively by the Python interpreter, `"Python.h"' includes a few standard header files: `', `', `', and `'. If the latter header file does not exist on your system, it declares the functions `malloc()', `free()' and `realloc()' directly. The next thing we add to our module file is the C function that will be called when the Python expression `spam.system(STRING)' is evaluated (we'll see shortly how it ends up being called): static PyObject * spam_system(self, args) PyObject *self; PyObject *args; { char *command; int sts; if (!PyArg_ParseTuple(args, "s", &command)) return NULL; sts = system(command); return Py_BuildValue("i", sts); } There is a straightforward translation from the argument list in Python (e.g. the single expression `"ls -l"') to the arguments passed to the C function. The C function always has two arguments, conventionally named SELF and ARGS. The SELF argument is only used when the C function implements a built-in method, not a function. In the example, 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 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 `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. `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 by so the calling function can return `NULL' immediately (as we saw in the example). ---------- Footnotes ---------- (1) An interface for this function already exists in the standard module `os' -- it was chosen as a simple and straightfoward example.  File: python-ext.info, Node: Intermezzo Errors and Exceptions, Next: Back to the Example, Prev: A Simple Example, Up: Extending Python with C or C++ Intermezzo: Errors and Exceptions ================================= 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 `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 `sys.exc_type', `sys.exc_value' and `sys.exc_traceback' (see the section on module `sys' in the *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 `PyErr_SetString()'. Its arguments are an exception object and a C string. The exception object is usually a predefined object like `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 `PyErr_SetFromErrno()', which only takes an exception argument and constructs the associated value by inspection of the (UNIX) global variable `errno'. The most general function is `PyErr_SetObject()', which takes two object arguments, the exception and its associated value. You don't need to `Py_INCREF()' the objects passed to any of these functions. You can test non-destructively whether an exception has been set with `PyErr_Occurred()'. This returns the current exception object, or `NULL' if no exception has occurred. You normally don't need to call `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 F that calls another function G detects that the latter fails, F should itself return an error value (e.g. `NULL' or `-1'). It should *not* call one of the `PyErr_*()' functions -- one has already been called by G. F's caller is then supposed to also return an error indication to *its* caller, again *without* calling `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 `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 `PyErr_Clear()'. The only time C code should call `PyErr_Clear()' is if it doesn't want to pass the error on to the interpreter but wants to handle it completely by itself (e.g. by trying something else or pretending nothing happened). Note that a failing `malloc()' call must be turned into an exception -- the direct caller of `malloc()' (or `realloc()') must call `PyErr_NoMemory()' and return a failure indicator itself. All the object-creating functions (`PyInt_FromLong()' etc.) already do this, so only if you call `malloc()' directly this note is of importance. Also note that, with the important exception of `PyArg_ParseTuple()' and friends, functions that return an integer status usually return a positive value or zero for success and `-1' for failure, like UNIX system calls. Finally, be careful to clean up garbage (by making `Py_XDECREF()' or `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, e.g. `PyExc_ZeroDivisionError', which you can use directly. Of course, you should choose exceptions wisely -- don't use `PyExc_TypeError' to mean that a file couldn't be opened (that should probably be `PyExc_IOError'). If something's wrong with the argument list, the `PyArg_ParseTuple()' function usually raises `PyExc_TypeError'. If you have an argument whose value must be in a particular range or must satisfy other conditions, `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, e.g. static PyObject *SpamError; and initialize it in your module's initialization function (`initspam()') with an exception object, e.g. (leaving out the error checking for now): void initspam() { PyObject *m, *d; m = Py_InitModule("spam", SpamMethods); d = PyModule_GetDict(m); SpamError = PyErr_NewException("spam.error", NULL, NULL); PyDict_SetItemString(d, "error", SpamError); } Note that the Python name for the exception object is `spam.error'. The `PyErr_NewException()' function may create either a string or class, depending on whether the `-X' flag was passed to the interpreter. If `-X' was used, `SpamError' will be a string object, otherwise it will be a class object with the base class being `Exception', described in the *Python Library Reference* under "Built-in Exceptions."  File: python-ext.info, Node: Back to the Example, Next: Module's Method Table and Initialization Function, Prev: Intermezzo Errors and Exceptions, Up: Extending Python with C or C++ Back to the Example =================== Going back to our example function, you should now be able to understand this statement: if (!PyArg_ParseTuple(args, "s", &command)) return NULL; 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 `PyArg_ParseTuple()'. Otherwise the string value of the argument has been copied to the local variable `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 `command' should properly be declared as `const char *command'). The next statement is a call to the UNIX function `system()', passing it the string we just got from `PyArg_ParseTuple()': sts = system(command); Our `spam.system()' function must return the value of `sts' as a Python object. This is done using the function `Py_BuildValue()', which is something like the inverse of `PyArg_ParseTuple()': it takes a format string and an arbitrary number of C values, and returns a new Python object. More info on `Py_BuildValue()' is given later. return Py_BuildValue("i", sts); 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 `void'), the corresponding Python function must return `None'. You need this idiom to do so: Py_INCREF(Py_None); return Py_None; `Py_None' is the C name for the special Python object `None'. It is a genuine Python object rather than a `NULL' pointer, which means "error" in most contexts, as we have seen.  File: python-ext.info, Node: Module's Method Table and Initialization Function, Next: Compilation and Linkage, Prev: Back to the Example, Up: Extending Python with C or C++ The Module's Method Table and Initialization Function ===================================================== I promised to show how `spam_system()' is called from Python programs. First, we need to list its name and address in a "method table": static PyMethodDef SpamMethods[] = { ... {"system", spam_system, METH_VARARGS}, ... {NULL, NULL} /* Sentinel */ }; Note the third entry (`METH_VARARGS'). This is a flag telling the interpreter the calling convention to be used for the C function. It should normally always be `METH_VARARGS' or `METH_VARARGS | METH_KEYWORDS'; a value of `0' means that an obsolete variant of `PyArg_ParseTuple()' is used. When using only `METH_VARARGS', the function should expect the Python-level parameters to be passed in as a tuple acceptable for parsing via `PyArg_ParseTuple()'; more information on this function is provided below. The `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 `PyObject *' parameter which will be a dictionary of keywords. Use `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 (which should be the only non-`static' item defined in the module file): void initspam() { (void) Py_InitModule("spam", SpamMethods); } When the Python program imports module `spam' for the first time, `initspam()' is called. It calls `Py_InitModule()', which creates a "module object" (which is inserted in the dictionary `sys.modules' under the key `"spam"'), and inserts built-in function objects into the newly created module based upon the table (an array of `PyMethodDef' structures) that was passed as its second argument. `Py_InitModule()' returns a pointer to the module object that it creates (which is unused here). It aborts with a fatal error if the module could not be initialized satisfactorily, so the caller doesn't need to check for errors. *Note:* Removing entries from `sys.modules' or importing compiled modules into multiple interpreters within a process (or following a `fork()' without an intervening `exec()') can create problems for some extension modules. Extension module authors should exercise caution when initializing internal data structures.  File: python-ext.info, Node: Compilation and Linkage, Next: Calling Python Functions from C, Prev: Module's Method Table and Initialization Function, Up: Extending Python with C or C++ Compilation and Linkage ======================= 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 depend on the style of dynamic loading your system uses; see the chapter "Dynamic Loading" 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: just place your file (`spammodule.c' for example) in the `Modules/' directory of an unpacked source distribution, add a line to the file `Modules/Setup.local' describing your file: spam spammodule.o and rebuild the interpreter by running `make' in the toplevel directory. You can also run `make' in the `Modules/' subdirectory, but then you must first rebuild `Makefile' there by running ``make' Makefile'. (This is necessary each time you change the `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: spam spammodule.o -lX11  File: python-ext.info, Node: Calling Python Functions from C, Next: Format Strings for PyArg_ParseTuple, Prev: Compilation and Linkage, Up: Extending Python with C or C++ Calling Python Functions from C =============================== 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 `-c' command line option in `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 `Py_INCREF()' it!) in a global variable -- or wherever you see fit. For example, the following function might be part of a module definition: static PyObject *my_callback = NULL; static PyObject * my_set_callback(dummy, arg) PyObject *dummy, *arg; { 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; } This function must be registered with the interpreter using the `METH_VARARGS' flag; this is described in section *Note Module's Method Table and Initialization Function::, "The Module's Method Table and Initialization Function." The `PyArg_ParseTuple()' function and its arguments are documented in section *Note Format Strings for PyArg_ParseTuple::, "Format Strings for `PyArg_ParseTuple()'." The macros `Py_XINCREF()' and `Py_XDECREF()' increment/decrement the reference count of an object and are safe in the presence of `NULL' pointers (but note that TEMP will not be `NULL' in this context). More info on them in section *Note Reference Counts::, "Reference Counts." Later, when it is time to call the function, you call the C function `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. `Py_BuildValue()' returns a tuple when its format string consists of zero or more format codes between parentheses. For example: 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); `PyEval_CallObject()' returns a Python object pointer: this is the return value of the Python function. `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 `Py_DECREF()'-ed immediately after the call. The return value of `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 `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 `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 `PyErr_Clear()'. For example: if (result == NULL) return NULL; /* Pass error back */ ...use result... Py_DECREF(result); Depending on the desired interface to the Python callback function, you may also have to provide an argument list to `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 `Py_BuildValue()'. For example, if you want to pass an integral event code, you might use the following code: 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); Note the placement of `Py_DECREF(arglist)' immediately after the call, before the error check! Also note that strictly spoken this code is not complete: `Py_BuildValue()' may run out of memory, and this should be checked.  File: python-ext.info, Node: Format Strings for PyArg_ParseTuple, Next: Keyword Parsing with PyArg_ParseTupleAndKeywords, Prev: Calling Python Functions from C, Up: Extending Python with C or C++ Format Strings for `PyArg_ParseTuple()' ======================================= The `PyArg_ParseTuple()' function is declared as follows: int PyArg_ParseTuple(PyObject *arg, char *format, ...); The ARG argument must be a tuple object containing an argument list passed from Python to a C function. The FORMAT argument must be a format string, whose syntax is explained below. The remaining arguments must be addresses of variables whose type is determined by the format string. For the conversion to succeed, the ARG object must match the format and the format must be exhausted. Note that while `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! A format string consists of zero or more "format units". A format unit describes one Python object; it is usually a single character or a parenthesized sequence of format units. With a few exceptions, a format unit that is not a parenthesized sequence normally corresponds to a single address argument to `PyArg_ParseTuple()'. In the following description, the quoted form is the format unit; the entry in (round) parentheses is the Python object type that matches the format unit; and the entry in [square] brackets is the type of the C variable(s) whose address should be passed. (Use the `&' operator to pass a variable's address.) ``s' (string) {[char * }]' Convert a Python string to a C pointer to a character string. You must not provide storage for the string itself; a pointer to an existing string is stored into the character pointer variable whose address you pass. The C string is null-terminated. The Python string must not contain embedded null bytes; if it does, a `TypeError' exception is raised. ``s#' (string) {[char *, int }]' This variant on `s' stores into two C variables, the first one a pointer to a character string, the second one its length. In this case the Python string may contain embedded null bytes. ``z' (string or `None') {[char * }]' Like `s', but the Python object may also be `None', in which case the C pointer is set to `NULL'. ``z#' (string or `None') {[char *, int }]' This is to `s#' as `z' is to `s'. ``b' (integer) {[char }]' Convert a Python integer to a tiny int, stored in a C `char'. ``h' (integer) {[short int }]' Convert a Python integer to a C `short int'. ``i' (integer) {[int }]' Convert a Python integer to a plain C `int'. ``l' (integer) {[long int }]' Convert a Python integer to a C `long int'. ``c' (string of length 1) {[char }]' Convert a Python character, represented as a string of length 1, to a C `char'. ``f' (float) {[float }]' Convert a Python floating point number to a C `float'. ``d' (float) {[double }]' Convert a Python floating point number to a C `double'. ``D' (complex) {[Py_complex }]' Convert a Python complex number to a C `Py_complex' structure. ``O' (object) {[PyObject * }]' Store a Python object (without any conversion) in a C object pointer. The C program thus receives the actual object that was passed. The object's reference count is not increased. The pointer stored is not `NULL'. ``O!' (object) {[TYPEOBJECT, PyObject * }]' Store a Python object in a C object pointer. This is similar to `O', but takes two C arguments: the first is the address of a Python type object, the second is the address of the C variable (of type `PyObject *') into which the object pointer is stored. If the Python object does not have the required type, a `TypeError' exception is raised. ``O&' (object) {[CONVERTER, ANYTHING }]' Convert a Python object to a C variable through a CONVERTER function. This takes two arguments: the first is a function, the second is the address of a C variable (of arbitrary type), converted to `void *'. The CONVERTER function in turn is called as follows: STATUS` = 'CONVERTER`('OBJECT, ADDRESS`);' where OBJECT is the Python object to be converted and ADDRESS is the `void *' argument that was passed to `PyArg_ConvertTuple()'. The returned STATUS should be `1' for a successful conversion and `0' if the conversion has failed. When the conversion fails, the CONVERTER function should raise an exception. ``S' (string) {[PyStringObject * }]' Like `O' but requires that the Python object is a string object. Raises a `TypeError' exception if the object is not a string object. The C variable may also be declared as `PyObject *'. ``(ITEMS)' (tuple) {[MATCHING-ITEMS }]' The object must be a Python sequence whose length is the number of format units in ITEMS. The C arguments must correspond to the individual format units in ITEMS. Format units for sequences may be nested. *Note:* Prior to Python version 1.5.2, this format specifier only accepted a tuple containing the individual parameters, not an arbitrary sequence. Code which previously caused a `TypeError' to be raised here may now proceed without an exception. This is not expected to be a problem for existing code. It is possible to pass Python long integers where integers are requested; however no proper range checking is done -- the most significant bits are silently truncated when the receiving field is too small to receive the value (actually, the semantics are inherited from downcasts in C -- your mileage may vary). A few other characters have a meaning in a format string. These may not occur inside nested parentheses. They are: ``|'' Indicates that the remaining arguments in the Python argument list are optional. The C variables corresponding to optional arguments should be initialized to their default value -- when an optional argument is not specified, `PyArg_ParseTuple()' does not touch the contents of the corresponding C variable(s). ``:'' The list of format units ends here; the string after the colon is used as the function name in error messages (the "associated value" of the exception that `PyArg_ParseTuple()' raises). ``;'' The list of format units ends here; the string after the colon is used as the error message *instead* of the default error message. Clearly, `:' and `;' mutually exclude each other. Some example calls: int ok; int i, j; long k, l; char *s; int size; ok = PyArg_ParseTuple(args, ""); /* No arguments */ /* Python call: f() */ ok = PyArg_ParseTuple(args, "s", &s); /* A string */ /* Possible Python call: f('whoops!') */ ok = PyArg_ParseTuple(args, "lls", &k, &l, &s); /* Two longs and a string */ /* Possible Python call: f(1, 2, 'three') */ 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') */ { char *file; 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) */ } { 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)) */ } { 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) */ }  File: python-ext.info, Node: Keyword Parsing with PyArg_ParseTupleAndKeywords, Next: Py_BuildValue Function, Prev: Format Strings for PyArg_ParseTuple, Up: Extending Python with C or C++ Keyword Parsing with `PyArg_ParseTupleAndKeywords()' ==================================================== The `PyArg_ParseTupleAndKeywords()' function is declared as follows: int PyArg_ParseTupleAndKeywords(PyObject *arg, PyObject *kwdict, char *format, char **kwlist, ...); The ARG and FORMAT parameters are identical to those of the `PyArg_ParseTuple()' function. The KWDICT parameter is the dictionary of keywords received as the third parameter from the Python runtime. The KWLIST parameter is a `NULL'-terminated list of strings which identify the parameters; the names are matched with the type information from FORMAT from left to right. *Note:* Nested tuples cannot be parsed when using keyword arguments! Keyword parameters passed in which are not present in the KWLIST will cause `TypeError' to be raised. Here is an example module which uses keywords, based on an example by Geoff Philbrick (): #include #include "Python.h" static PyObject * keywdarg_parrot(self, args, keywds) 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}, {NULL, NULL} /* sentinel */ }; void initkeywdarg() { /* Create the module and add the functions */ Py_InitModule("keywdarg", keywdarg_methods); }  File: python-ext.info, Node: Py_BuildValue Function, Next: Reference Counts, Prev: Keyword Parsing with PyArg_ParseTupleAndKeywords, Up: Extending Python with C or C++ The `Py_BuildValue()' Function ============================== This function is the counterpart to `PyArg_ParseTuple()'. It is declared as follows: PyObject *Py_BuildValue(char *format, ...); It recognizes a set of format units similar to the ones recognized by `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 `PyArg_ParseTuple()': while the latter requires its first argument to be a tuple (since Python argument lists are always represented as tuples internally), `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 `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. In the following description, the quoted form is the format unit; the entry in (round) parentheses is the Python object type that the format unit will return; and the entry in [square] brackets is the type of the C value(s) to be passed. The characters space, tab, colon and comma are ignored in format strings (but not within format units such as `s#'). This can be used to make long format strings a tad more readable. ``s' (string) {[char * }]' Convert a null-terminated C string to a Python object. If the C string pointer is `NULL', `None' is returned. ``s#' (string) {[char *, int }]' Convert a C string and its length to a Python object. If the C string pointer is `NULL', the length is ignored and `None' is returned. ``z' (string or `None') {[char * }]' Same as `s'. ``z#' (string or `None') {[char *, int }]' Same as `s#'. ``i' (integer) {[int }]' Convert a plain C `int' to a Python integer object. ``b' (integer) {[char }]' Same as `i'. ``h' (integer) {[short int }]' Same as `i'. ``l' (integer) {[long int }]' Convert a C `long int' to a Python integer object. ``c' (string of length 1) {[char }]' Convert a C `int' representing a character to a Python string of length 1. ``d' (float) {[double }]' Convert a C `double' to a Python floating point number. ``f' (float) {[float }]' Same as `d'. ``O' (object) {[PyObject * }]' Pass a Python object untouched (except for its reference count, which is incremented by one). If the object passed in is a `NULL' pointer, it is assumed that this was caused because the call producing the argument found an error and set an exception. Therefore, `Py_BuildValue()' will return `NULL' but won't raise an exception. If no exception has been raised yet, `PyExc_SystemError' is set. ``S' (object) {[PyObject * }]' Same as `O'. ``N' (object) {[PyObject * }]' Same as `O', except it doesn't increment the reference count on the object. Useful when the object is created by a call to an object constructor in the argument list. ``O&' (object) {[CONVERTER, ANYTHING }]' Convert ANYTHING to a Python object through a CONVERTER function. The function is called with ANYTHING (which should be compatible with `void *') as its argument and should return a "new" Python object, or `NULL' if an error occurred. ``(ITEMS)' (tuple) {[MATCHING-ITEMS }]' Convert a sequence of C values to a Python tuple with the same number of items. ``[ITEMS ' (list) {[MATCHING-ITEMS]}]' Convert a sequence of C values to a Python list with the same number of items. ``{ITEMS}' (dictionary) {[MATCHING-ITEMS }]' Convert a sequence of C values to a Python dictionary. Each pair of consecutive C values adds one item to the dictionary, serving as key and value, respectively. If there is an error in the format string, the `PyExc_SystemError' exception is raised and `NULL' returned. Examples (to the left the call, to the right the resulting Python value): 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))  File: python-ext.info, Node: Reference Counts, Next: Writing Extensions in C++, Prev: Py_BuildValue Function, Up: Extending Python with C or C++ Reference Counts ================ In languages like C or C++, the programmer is responsible for dynamic allocation and deallocation of memory on the heap. In C, this is done using the functions `malloc()' and `free()'. In C++, the operators `new' and `delete' are used with essentially the same meaning; they are actually implemented using `malloc()' and `free()', so we'll restrict the following discussion to the latter. Every block of memory allocated with `malloc()' should eventually be returned to the pool of available memory by exactly one call to `free()'. It is important to call `free()' at the right time. If a block's address is forgotten but `free()' is not called for it, the memory it occupies cannot be reused until the program terminates. This is called a "memory leak". On the other hand, if a program calls `free()' for a block and then continues to use the block, it creates a conflict with re-use of the block through another `malloc()' call. This is called "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 `malloc()' and `free()', it needs a strategy to avoid memory leaks as well as the use of freed memory. The chosen method is called "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 "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 `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 `malloc()' and `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. * Menu: * Reference Counting in Python:: * Ownership Rules:: * Thin Ice:: * NULL Pointers::  File: python-ext.info, Node: Reference Counting in Python, Next: Ownership Rules, Prev: Reference Counts, Up: Reference Counts Reference Counting in Python ---------------------------- There are two macros, `Py_INCREF(x)' and `Py_DECREF(x)', which handle the incrementing and decrementing of the reference count. `Py_DECREF()' also frees the object when the count reaches zero. For flexibility, it doesn't call `free()' directly -- rather, it makes a call through a function pointer in the object's "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 `Py_INCREF(x)' and `Py_DECREF(x)'? Let's first introduce some terms. Nobody "owns" an object; however, you can "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 `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 `Py_DECREF()'. Forgetting to dispose of an owned reference creates a memory leak. It is also possible to "borrow"(1) a reference to an object. The borrower of a reference should not call `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.(2) 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 `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 (i.e., the new owner must dispose of the reference properly, as well as the previous owner). ---------- Footnotes ---------- (1) The metaphor of "borrowing" a reference is not completely correct: the owner still has a copy of the reference. (2) Checking that the reference count is at least 1 *does not work* -- the reference count itself could be in freed memory and may thus be reused for another object!