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\title{Extending and Embedding the Python Interpreter}

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\begin{document}

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\begin{abstract}

\noindent

Python is an interpreted, object-oriented programming language. This

document describes how to write modules in \C{} or \Cpp{} 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 \emph{Python

Reference Manual} gives a more formal definition of the language. The

\emph{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

\emph{Python/\C{} API Reference Manual}. \strong{Note:} While that

manual is still in a state of flux, it is safe to say that it is much

more up to date than the manual you're reading currently (which has

been in need for an upgrade for some time now).

\end{abstract}

\tableofcontents

\chapter{Extending Python with \C{} or \Cpp{} code}

%\section{Introduction}

\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 a later section.

\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 straightfoward 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 \samp{spammodule.c}. (In general, 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).

All user-visible symbols defined by \code{"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(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);

}

\end{verbatim}

There is a straightforward translation from the argument list in

Python (e.g.\ 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

builtin method. This will be discussed later. 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 by 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 \emph{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 (\UNIX{}) 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

(e.g. \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 (e.g. by trying something else or pretending

nothing happened).

Note that a 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

(\cfunction{PyInt_FromLong()} etc.) already do this, so only if you

call \cfunction{malloc()} directly this note is of importance.

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,

e.g. \cdata{PyExc_ZeroDevisionError} 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

which 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, e.g.

\begin{verbatim}

static PyObject *SpamError;

\end{verbatim}

and initialize it in your module's initialization function

(\cfunction{initspam()}) with an exception object, e.g. (leaving out

the error checking for now):

\begin{verbatim}

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);

}

\end{verbatim}

Note that the Python name for the exception object is

\exception{spam.error}. The \cfunction{PyErr_NewException()} function

may create either a string or class, depending on whether the

\samp{-X} flag was passed to the interpreter. If \samp{-X} was used,

\cdata{SpamError} will be a string object, otherwise it will be a

class object with the base class being \exception{Exception},

described in the \emph{Python Library Reference} under ``Built-in

Exceptions.''

\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:

\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 (not 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},

...

{NULL, 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 \samp{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 arguemts 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-\code{static}

item defined in the module file):

\begin{verbatim}

void

initspam()

{

(void) Py_InitModule("spam", SpamMethods);

}

\end{verbatim}

When the Python program imports module \module{spam} for the first

time, \cfunction{initspam()} is called. 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 aborts with a fatal error

if the module could not be initialized satisfactorily, so the caller

doesn't need to check for errors.

\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 depend on the style of dynamic loading your

system uses; see the chapter on Dynamic Loading for more info 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 (\file{spammodule.c} for example) in

the \file{Modules} directory, add a line to the file

\file{Modules/Setup} 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 rebuilt the \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 \file{Setup} 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 \samp{-c} command line option in \file{Python/pythonmain.c}.)

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 whereever 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(dummy, arg)

PyObject *dummy, *arg;

{

Py_XDECREF(my_callback); /* Dispose of previous callback */

Py_XINCREF(arg); /* Add a reference to new callback */

my_callback = arg; /* Remember new callback */

/* Boilerplate to return "None" */

Py_INCREF(Py_None);

return Py_None;

}

\end{verbatim}

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. More info on them in the section on

Reference Counts below.

Later, when it is time to call the function, you call the \C{} function

\cfunction{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{Format Strings for \sectcode{PyArg_ParseTuple()}}

\label{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 below. The

remaining arguments must be addresses of variables whose type is

determined by the format string. For the conversion to succeed, the

\var{arg} object must match the format and the format must be

exhausted.

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!

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 \cfunction{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 \samp{\&}

operator to pass a variable's address.)

\begin{description}

\item[\samp{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 \exception{TypeError}

exception is raised.

\item[\samp{s\#} (string) {[char *, int]}]

This variant on \samp{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.

\item[\samp{z} (string or \code{None}) {[char *]}]

Like \samp{s}, but the Python object may also be \code{None}, in which

case the \C{} pointer is set to \NULL{}.

\item[\samp{z\#} (string or \code{None}) {[char *, int]}]

This is to \samp{s\#} as \samp{z} is to \samp{s}.

\item[\samp{b} (integer) {[char]}]

Convert a Python integer to a tiny int, stored in a \C{} \ctype{char}.

\item[\samp{h} (integer) {[short int]}]

Convert a Python integer to a \C{} \ctype{short int}.

\item[\samp{i} (integer) {[int]}]

Convert a Python integer to a plain \C{} \ctype{int}.

\item[\samp{l} (integer) {[long int]}]

Convert a Python integer to a \C{} \ctype{long int}.

\item[\samp{c} (string of length 1) {[char]}]

Convert a Python character, represented as a string of length 1, to a

\C{} \ctype{char}.

\item[\samp{f} (float) {[float]}]

Convert a Python floating point number to a \C{} \ctype{float}.

\item[\samp{d} (float) {[double]}]

Convert a Python floating point number to a \C{} \ctype{double}.

\item[\samp{D} (complex) {[Py_complex]}]

Convert a Python complex number to a \C{} \ctype{Py_complex} structure.

\item[\samp{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{}.

\item[\samp{O!} (object) {[\var{typeobject}, PyObject *{]}}]

Store a Python object in a \C{} object pointer. This is similar to

\samp{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 \ctype{PyObject *}) into which the object pointer is stored.

If the Python object does not have the required type, a

\exception{TypeError} exception is raised.

\item[\samp{O\&} (object) {[\var{converter}, \var{anything}{]}}]

Convert a Python object to a \C{} variable through a \var{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 \ctype{void *}. The \var{converter} function in turn is called as

follows:

\code{\var{status} = \var{converter}(\var{object}, \var{address});}

where \var{object} is the Python object to be converted and

\var{address} is the \ctype{void *} argument that was passed to

\cfunction{PyArg_ConvertTuple()}. The returned \var{status} should be

\code{1} for a successful conversion and \code{0} if the conversion

has failed. When the conversion fails, the \var{converter} function

should raise an exception.

\item[\samp{S} (string) {[PyStringObject *]}]

Like \samp{O} but requires that the Python object is a string object.

Raises a \exception{TypeError} exception if the object is not a string

object. The \C{} variable may also be declared as \ctype{PyObject *}.

\item[\samp{(\var{items})} (tuple) {[\var{matching-items}{]}}]

The object must be a Python tuple whose length is the number of format

units in \var{items}. The \C{} arguments must correspond to the

individual format units in \var{items}. Format units for tuples may

be nested.

\end{description}

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 milage may vary).

A few other characters have a meaning in a format string. These may

not occur inside nested parentheses. They are:

\begin{description}

\item[\samp{|}]

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, \cfunction{PyArg_ParseTuple()} does not touch the contents

of the corresponding \C{} variable(s).

\item[\samp{:}]

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 exceptions that \cfunction{PyArg_ParseTuple()} raises).

\item[\samp{;}]

The list of format units ends here; the string after the colon is used

as the error message \emph{instead} of the default error message.

Clearly, \samp{:} and \samp{;} mutually exclude each other.

\end{description}

Some example calls:

\begin{verbatim}

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) */

}

\end{verbatim}

\section{Keyword Parsing with \sectcode{PyArg_ParseTupleAndKeywords()}}

\label{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.

\strong{Note:} Nested tuples cannot be parsed when using keyword

arguments! Keyword parameters passed in which are not present in the

\var{kwlist} will cause a \exception{TypeError} to be raised.

Here is an example module which uses keywords, based on an example by

Geoff Philbrick (\email{[email protected]}):

\begin{verbatim}

#include <stdio.h>

#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[] = {

{"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);

}

\end{verbatim}

\section{The \sectcode{Py_BuildValue()} Function}

\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.

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 \samp{s\#}). This can be

used to make long format strings a tad more readable.

\begin{description}

\item[\samp{s} (string) {[char *]}]

Convert a null-terminated \C{} string to a Python object. If the \C{}

string pointer is \NULL{}, \code{None} is returned.

\item[\samp{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 \code{None} is

returned.

\item[\samp{z} (string or \code{None}) {[char *]}]

Same as \samp{s}.

\item[\samp{z\#} (string or \code{None}) {[char *, int]}]

Same as \samp{s\#}.

\item[\samp{i} (integer) {[int]}]

Convert a plain \C{} \ctype{int} to a Python integer object.

\item[\samp{b} (integer) {[char]}]

Same as \samp{i}.

\item[\samp{h} (integer) {[short int]}]

Same as \samp{i}.

\item[\samp{l} (integer) {[long int]}]

Convert a \C{} \ctype{long int} to a Python integer object.

\item[\samp{c} (string of length 1) {[char]}]

Convert a \C{} \ctype{int} representing a character to a Python string of

length 1.

\item[\samp{d} (float) {[double]}]

Convert a \C{} \ctype{double} to a Python floating point number.

\item[\samp{f} (float) {[float]}]

Same as \samp{d}.

\item[\samp{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,

\cfunction{Py_BuildValue()} will return \NULL{} but won't raise an

exception. If no exception has been raised yet,

\cdata{PyExc_SystemError} is set.

\item[\samp{S} (object) {[PyObject *]}]

Same as \samp{O}.

\item[\samp{O\&} (object) {[\var{converter}, \var{anything}]}]

Convert \var{anything} to a Python object through a \var{converter}

function. The function is called with \var{anything} (which should be

compatible with \ctype{void *}) as its argument and should return a

``new'' Python object, or \NULL{} if an error occurred.

\item[\samp{(\var{items})} (tuple) {[\var{matching-items}]}]

Convert a sequence of \C{} values to a Python tuple with the same number

of items.

\item[\samp{[\var{items}]} (list) {[\var{matching-items}]}]

Convert a sequence of \C{} values to a Python list with the same number

of items.

\item[\samp{\{\var{items}\}} (dictionary) {[\var{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.

\end{description}

If there is an error in the format string, the

\cdata{PyExc_SystemError} exception is raised and \NULL{} returned.

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}

%\subsection{Introduction}

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; they are

actually implemented using \cfunction{malloc()} and

\cfunction{free()}, so we'll restrict the following discussion to the

latter.

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,