\documentstyle[twoside,11pt,myformat]{report}

\title{Python/C API Reference}

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\begin{document}

\pagenumbering{roman}

\maketitle

\input{copyright}

\begin{abstract}

\noindent
This manual documents the API used by C (or C++) programmers who want
to write extension modules or embed Python.  It is a companion to
``Extending and Embedding the Python Interpreter'', which describes
the general principles of extension writing but does not document the
API functions in detail.

\end{abstract}

\pagebreak

{
\parskip = 0mm
\tableofcontents
}

\pagebreak

\pagenumbering{arabic}

% XXX Consider moving all this back to ext.tex and giving api.tex
% XXX a *really* short intro only.

\chapter{Introduction}

The Application Programmer's Interface to Python gives C and C++
programmers access to the Python interpreter at a variety of levels.
There are two fundamentally different reasons for using the Python/C 
API.  (The API is equally usable from C++, but for brevity it is 
generally referred to as the Python/C API.)  The first reason is to 
write ``extension modules'' for specific purposes; these are C modules 
that extend the Python interpreter.  This is probably the most common 
use.  The second reason is to use Python as a component in a larger 
application; this technique is generally referred to as ``embedding'' 
Python in an application.

Writing an extension module is a relatively well-understood process, 
where a ``cookbook'' approach works well.  There are several tools 
that automate the process to some extent.  While people have embedded 
Python in other applications since its early existence, the process of 
embedding Python is less straightforward that writing an extension.  
Python 1.5 introduces a number of new API functions as well as some 
changes to the build process that make embedding much simpler.  
This manual describes the 1.5 state of affair (as of Python 1.5a3).
% XXX Eventually, take the historical notes out

Many API functions are useful independent of whether you're embedding 
or extending Python; moreover, most applications that embed Python 
will need to provide a custom extension as well, so it's probably a 
good idea to become familiar with writing an extension before 
attempting to embed Python in a real application.

\section{Objects, Types and Reference Counts}

Most Python/C API functions have one or more arguments as well as a 
return value of type \code{PyObject *}.  This type is a pointer 
(obviously!)  to an opaque data type representing an arbitrary Python 
object.  Since all Python object types are treated the same way by the 
Python language in most situations (e.g., assignments, scope rules, 
and argument passing), it is only fitting that they should be 
represented by a single C type.  All Python objects live on the heap:
you never declare an automatic or static variable of type 
\code{PyObject}, only pointer variables of type \code{PyObject *} can 
be declared.

All Python objects (even Python integers) have a ``type'' and a 
``reference count''.  An object's type determines what kind of object 
it is (e.g., an integer, a list, or a user-defined function; there are 
many more as explained in the Python Language Reference Manual).  For 
each of the well-known types there is a macro to check whether an 
object is of that type; for instance, \code{PyList_Check(a)} is true 
iff the object pointed to by \code{a} is a Python list.

\subsection{Reference Counts}

The reference count is important only because today's computers have a 
finite (and often severly limited) memory size; it counts how many 
different places there are that have a reference to an object.  Such a 
place could be another object, or a global (or static) C variable, or 
a local variable in some C function.  When an object's reference count 
becomes zero, the object is deallocated.  If it contains references to 
other objects, their reference count is decremented.  Those other 
objects may be deallocated in turn, if this decrement makes their 
reference count become zero, and so on.  (There's an obvious problem 
with objects that reference each other here; for now, the solution is 
``don't do that''.)

Reference counts are always manipulated explicitly.  The normal way is 
to use the macro \code{Py_INCREF(a)} to increment an object's 
reference count by one, and \code{Py_DECREF(a)} to decrement it by 
one.  The decref macro is considerably more complex than the incref one, 
since it must check whether the reference count becomes zero and then 
cause the object's deallocator, which is a function pointer contained 
in the object's type structure.  The type-specific deallocator takes 
care of decrementing the reference counts for other objects contained 
in the object, and so on, if this is a compound object type such as a 
list.  There's no chance that the reference count can overflow; at 
least as many bits are used to hold the reference count as there are 
distinct memory locations in virtual memory (assuming 
\code{sizeof(long) >= sizeof(char *)}).  Thus, the reference count 
increment is a simple operation.

It is not necessary to increment an object's reference count for every 
local variable that contains a pointer to an object.  In theory, the 
oject's reference count goes up by one when the variable is made to 
point to it and it goes down by one when the variable goes out of 
scope.  However, these two cancel each other out, so at the end the 
reference count hasn't changed.  The only real reason to use the 
reference count is to prevent the object from being deallocated as 
long as our variable is pointing to it.  If we know that there is at 
least one other reference to the object that lives at least as long as 
our variable, there is no need to increment the reference count 
temporarily.  An important situation where this arises is in objects 
that are passed as arguments to C functions in an extension module 
that are called from Python; the call mechanism guarantees to hold a 
reference to every argument for the duration of the call.

However, a common pitfall is to extract an object from a list and 
holding on to it for a while without incrementing its reference count.  
Some other operation might conceivably remove the object from the 
list, decrementing its reference count and possible deallocating it.  
The real danger is that innocent-looking operations may invoke 
arbitrary Python code which could do this; there is a code path which 
allows control to flow back to the user from a \code{Py_DECREF()}, so 
almost any operation is potentially dangerous.

A safe approach is to always use the generic operations (functions 
whose name begins with \code{PyObject_}, \code{PyNumber_}, 
\code{PySequence_} or \code{PyMapping_}).  These operations always 
increment the reference count of the object they return.  This leaves 
the caller with the responsibility to call \code{Py_DECREF()} when 
they are done with the result; this soon becomes second nature.

\subsubsection{Reference Count Details}

The reference count behavior of functions in the Python/C API is best 
expelained in terms of \emph{ownership of references}.  Note that we 
talk of owning reference, never of owning objects; objects are always 
shared!  When a function owns a reference, it has to dispose of it 
properly -- either by passing ownership on (usually to its caller) or 
by calling \code{Py_DECREF()} or \code{Py_XDECREF()}.  When a function 
passes ownership of a reference on to its caller, the caller is said 
to receive a \emph{new} reference.  When to ownership is transferred, 
the caller is said to \emph{borrow} the reference.  Nothing needs to 
be done for a borrowed reference.

Conversely, when calling a function while passing it a reference to an 
object, there are two possibilities: the function \emph{steals} a 
reference to the object, or it does not.  Few functions steal 
references; the two notable exceptions are \code{PyList_SetItem()} and 
\code{PyTuple_SetItem()}, which steal a reference to the item (but not to 
the tuple or list into which the item it put!).  These functions were 
designed to steal a reference because of a common idiom for 
populating a tuple or list with newly created objects; e.g., the code 
to create the tuple \code{(1, 2, "three")} could look like this 
(forgetting about error handling for the moment):

\begin{verbatim}
PyObject *t;
t = PyTuple_New(3);
PyTuple_SetItem(t, 0, PyInt_FromLong(1L));
PyTuple_SetItem(t, 1, PyInt_FromLong(2L));
PyTuple_SetItem(t, 2, PyString_FromString("three"));
\end{verbatim}

Incidentally, \code{PyTuple_SetItem()} is the \emph{only} way to set 
tuple items; \code{PyObject_SetItem()} refuses to do this since tuples 
are an immutable data type.  You should only use 
\code{PyTuple_SetItem()} for tuples that you are creating yourself.

Equivalent code for populating a list can be written using 
\code{PyList_New()} and \code{PyList_SetItem()}.  Such code can also 
use \code{PySequence_SetItem()}; this illustrates the difference 
between the two:

\begin{verbatim}
PyObject *l, *x;
l = PyList_New(3);
x = PyInt_FromLong(1L);
PyObject_SetItem(l, 0, x); Py_DECREF(x);
x = PyInt_FromLong(2L);
PyObject_SetItem(l, 1, x); Py_DECREF(x);
x = PyString_FromString("three");
PyObject_SetItem(l, 2, x); Py_DECREF(x);
\end{verbatim}

You might find it strange that the ``recommended'' approach takes 
more code.  in practice, you will rarely use these ways of creating 
and populating a tuple or list, however; there's a generic function,
\code{Py_BuildValue()} that can create most common objects from C 
values, directed by a ``format string''.  For example, the above two 
blocks of code could be replaced by the following (which also takes 
care of the error checking!):

\begin{verbatim}
PyObject *t, *l;
t = Py_BuildValue("(iis)", 1, 2, "three");
l = Py_BuildValue("[iis]", 1, 2, "three");
\end{verbatim}

It is much more common to use \code{PyObject_SetItem()} and friends 
with items whose references you are only borrowing, like arguments 
that were passed in to the function you are writing.  In that case, 
their behaviour regarding reference counts is much saner, since you 
don't have to increment a reference count so you can give a reference 
away (``have it be stolen'').  For example, this function sets all 
items of a list (actually, any mutable sequence) to a given item:

\begin{verbatim}
int set_all(PyObject *target, PyObject *item)
{
    int i, n;
    n = PyObject_Length(target);
    if (n < 0)
        return -1;
    for (i = 0; i < n; i++) {
        if (PyObject_SetItem(target, i, item) < 0)
            return -1;
    }
    return 0;
}
\end{verbatim}

The situation is slightly different for function return values.  
While passing a reference to most functions does not change your 
ownership responsibilities for that reference, many functions that 
return a referece to an object give you ownership of the reference.
The reason is simple: in many cases, the returned object is created 
on the fly, and the reference you get is the only reference to the 
object!  Therefore, the generic functions that return object 
references, like \code{PyObject_GetItem()} and 
\code{PySequence_GetItem()}, always return a new reference (i.e., the 
caller becomes the owner of the reference).

It is important to realize that whether you own a reference returned 
by a function depends on which function you call only -- \emph{the 
plumage} (i.e., the type of the type of the object passed as an 
argument to the function) \emph{don't enter into it!}  Thus, if you 
extract an item from a list using \code{PyList_GetItem()}, yo don't 
own the reference -- but if you obtain the same item from the same 
list using \code{PySequence_GetItem()} (which happens to take exactly 
the same arguments), you do own a reference to the returned object.

Here is an example of how you could write a function that computes the 
sum of the items in a list of integers; once using 
\code{PyList_GetItem()}, once using \code{PySequence_GetItem()}.

\begin{verbatim}
long sum_list(PyObject *list)
{
    int i, n;
    long total = 0;
    PyObject *item;
    n = PyList_Size(list);
    if (n < 0)
        return -1; /* Not a list */
    for (i = 0; i < n; i++) {
        item = PyList_GetItem(list, i); /* Can't fail */
        if (!PyInt_Check(item)) continue; /* Skip non-integers */
        total += PyInt_AsLong(item);
    }
    return total;
}
\end{verbatim}

\begin{verbatim}
long sum_sequence(PyObject *sequence)
{
    int i, n;
    long total = 0;
    PyObject *item;
    n = PyObject_Size(list);
    if (n < 0)
        return -1; /* Has no length */
    for (i = 0; i < n; i++) {
        item = PySequence_GetItem(list, i);
        if (item == NULL)
            return -1; /* Not a sequence, or other failure */
        if (PyInt_Check(item))
            total += PyInt_AsLong(item);
        Py_DECREF(item); /* Discared reference ownership */
    }
    return total;
}
\end{verbatim}

\subsection{Types}

There are few other data types that play a significant role in 
the Python/C API; most are all simple C types such as \code{int}, 
\code{long}, \code{double} and \code{char *}.  A few structure types 
are used to describe static tables used to list the functions exported 
by a module or the data attributes of a new object type.  These will 
be discussed together with the functions that use them.

\section{Exceptions}

The Python programmer only needs to deal with exceptions if specific 
error handling is required; unhandled exceptions are automatically 
propagated to the caller, then to the caller's caller, and so on, till 
they reach the top-level interpreter, where they are reported to the 
user accompanied by a stack traceback.

For C programmers, however, error checking always has to be explicit.  
All functions in the Python/C API can raise exceptions, unless an 
explicit claim is made otherwise in a function's documentation.  In 
general, when a function encounters an error, it sets an exception, 
discards any object references that it owns, and returns an 
error indicator -- usually \code{NULL} or \code{-1}.  A few functions 
return a Boolean true/false result, with false indicating an error.
Very few functions return no explicit error indicator or have an 
ambiguous return value, and require explicit testing for errors with 
\code{PyErr_Occurred()}.

Exception state is maintained in per-thread storage (this is 
equivalent to using global storage in an unthreaded application).  A 
thread can be on one of two states: an exception has occurred, or not.  
The function \code{PyErr_Occurred()} can be used to check for this: it 
returns a borrowed reference to the exception type object when an 
exception has occurred, and \code{NULL} otherwise.  There are a number 
of functions to set the exception state: \code{PyErr_SetString()} is 
the most common (though not the most general) function to set the 
exception state, and \code{PyErr_Clear()} clears the exception state.

The full exception state consists of three objects (all of which can 
be \code{NULL} ): the exception type, the corresponding exception 
value, and the traceback.  These have the same meanings as the Python 
object \code{sys.exc_type}, \code{sys.exc_value}, 
\code{sys.exc_traceback}; however, they are not the same: the Python 
objects represent the last exception being handled by a Python 
\code{try...except} statement, while the C level exception state only 
exists while an exception is being passed on between C functions until 
it reaches the Python interpreter, which takes care of transferring it 
to \code{sys.exc_type} and friends.

(Note that starting with Python 1.5, the preferred, thread-safe way to 
access the exception state from Python code is to call the function 
\code{sys.exc_info()}, which returns the per-thread exception state 
for Python code.  Also, the semantics of both ways to access the 
exception state have changed so that a function which catches an 
exception will save and restore its thread's exception state so as to 
preserve the exception state of its caller.  This prevents common bugs 
in exception handling code caused by an innocent-looking function 
overwriting the exception being handled; it also reduces the often 
unwanted lifetime extension for objects that are referenced by the 
stack frames in the traceback.)

As a general principle, a function that calls another function to 
perform some task should check whether the called function raised an 
exception, and if so, pass the exception state on to its caller.  It 
should discards any object references that it owns, and returns an 
error indicator, but it should \emph{not} set another exception -- 
that would overwrite the exception that was just raised, and lose 
important reason about the exact cause of the error.

A simple example of detecting exceptions and passing them on is shown 
in the \code{sum_sequence()} example above.  It so happens that that 
example doesn't need to clean up any owned references when it detects 
an error.  The following example function shows some error cleanup.  
First we show the equivalent Python code (to remind you why you like 
Python):

\begin{verbatim}
def incr_item(seq, i):
    try:
        item = seq[i]
    except IndexError:
        item = 0
    seq[i] = item + 1
\end{verbatim}

Here is the corresponding C code, in all its glory:

% XXX Is it better to have fewer comments in the code?

\begin{verbatim}
int incr_item(PyObject *seq, int i)
{
    /* Objects all initialized to NULL for Py_XDECREF */
    PyObject *item = NULL, *const_one = NULL, *incremented_item = NULL;
    int rv = -1; /* Return value initialized to -1 (faulure) */

    item = PySequence_GetItem(seq, i);
    if (item == NULL) {
        /* Handle IndexError only: */
        if (PyErr_Occurred() != PyExc_IndexError) goto error;

        /* Clear the error and use zero: */
        PyErr_Clear();
        item = PyInt_FromLong(1L);
        if (item == NULL) goto error;
    }

    const_one = PyInt_FromLong(1L);
    if (const_one == NULL) goto error;

    incremented_item = PyNumber_Add(item, const_one);
    if (incremented_item == NULL) goto error;

    if (PyObject_SetItem(seq, i, incremented_item) < 0) goto error;
    rv = 0; /* Success */
    /* Continue with cleanup code */

 error:
    /* Cleanup code, shared by success and failure path */

    /* Use Py_XDECREF() to ignore NULL references */
    Py_XDECREF(item);
    Py_XDECREF(const_one);
    Py_XDECREF(incremented_item);

    return rv; /* -1 for error, 0 for success */
}
\end{verbatim}

This example represents an endorsed use of the \code{goto} statement 
in C!  It illustrates the use of \code{PyErr_Occurred()} and 
\code{PyErr_Clear()} to handle specific exceptions, and the use of 
\code{Py_XDECREF()} to dispose of owned references that may be 
\code{NULL} (note the `X' in the name; \code{Py_DECREF()} would crash 
when confronted with a \code{NULL} reference).  It is important that 
the variables used to hold owned references are initialized to 
\code{NULL} for this to work; likewise, the proposed return value is 
initialized to \code{-1} (failure) and only set to success  after 
the final call made is succesful.


\section{Embedding Python}

The one important task that only embedders of the Python interpreter 
have to worry about is the initialization (and possibly the 
finalization) of the Python interpreter.  Most functionality of the 
interpreter can only be used after the interpreter has been 
initialized.

The basic initialization function is \code{Py_Initialize()}.  This 
initializes the table of loaded modules, and creates the fundamental 
modules \code{__builtin__}, \code{__main__} and \code{sys}.  It also 
initializes the module search path (\code{sys.path}).

\code{Py_Initialize()} does not set the ``script argument list'' 
(\code{sys.argv}).  If this variable is needed by Python code that 
will be executed later, it must be set explicitly with a call to 
\code{PySys_SetArgv(\var{argc}, \var{argv})} subsequent to the call 
to \code{Py_Initialize()}.

On Unix, \code{Py_Initialize()} calculates the module search path 
based upon its best guess for the location of the standard Python 
interpreter executable, assuming that the Python library is found in a 
fixed location relative to the Python interpreter executable.  In 
particular, it looks for a directory named \code{lib/python1.5} 
(replacing \code{1.5} with the current interpreter version) relative 
to the parent directory where the executable named \code{python} is 
found on the shell command search path (the environment variable 
\code{\$PATH}).  For instance, if the Python executable is found in 
\code{/usr/local/bin/python}, it will assume that the libraries are in 
\code{/usr/local/lib/python1.5}.  In fact, this also the ``fallback'' 
location, used when no executable file named \code{python} is found 
along \code{\$PATH}.  The user can change this behavior by setting the 
environment variable \code{\$PYTHONHOME}, and can insert additional 
directories in front of the standard path by setting 
\code{\$PYTHONPATH}.

The embedding application can steer the search by calling 
\code{Py_SetProgramName(\var{file})} \emph{before} calling 
\code{Py_Initialize()}.  Note that \code{\$PYTHONHOME} still overrides 
this and \code{\$PYTHONPATH} is still inserted in front of the 
standard path.

Sometimes, it is desirable to ``uninitialize'' Python.  For instance, 
the application may want to start over (make another call to 
\code{Py_Initialize()}) or the application is simply done with its 
use of Python and wants to free all memory allocated by Python.  This 
can be accomplished by calling \code{Py_Finalize()}.
% XXX More...

\section{Embedding Python in Threaded Applications}










\chapter{Old Introduction}

(XXX This is the old introduction, mostly by Jim Fulton -- should be
rewritten.)

From the viewpoint of of C access to Python services, we have:

\begin{enumerate}

\item "Very high level layer": two or three functions that let you
exec or eval arbitrary Python code given as a string in a module whose
name is given, passing C values in and getting C values out using
mkvalue/getargs style format strings.  This does not require the user
to declare any variables of type \code{PyObject *}.  This should be
enough to write a simple application that gets Python code from the
user, execs it, and returns the output or errors.

\item "Abstract objects layer": which is the subject of this chapter.
It has many functions operating on objects, and lets you do many
things from C that you can also write in Python, without going through
the Python parser.

\item "Concrete objects layer": This is the public type-dependent
interface provided by the standard built-in types, such as floats,
strings, and lists.  This interface exists and is currently documented
by the collection of include files provides with the Python
distributions.

\end{enumerate}

From the point of view of Python accessing services provided by C
modules:

\begin{enumerate}

\item[4.] "Python module interface": this interface consist of the basic
routines used to define modules and their members.  Most of the
current extensions-writing guide deals with this interface.

\item[5.] "Built-in object interface": this is the interface that a new
built-in type must provide and the mechanisms and rules that a
developer of a new built-in type must use and follow.

\end{enumerate}

The Python C API provides four groups of operations on objects,
corresponding to the same operations in the Python language: object,
numeric, sequence, and mapping.  Each protocol consists of a
collection of related operations.  If an operation that is not
provided by a particular type is invoked, then the standard exception
\code{TypeError} is raised with a operation name as an argument.

In addition, for convenience this interface defines a set of
constructors for building objects of built-in types.  This is needed
so new objects can be returned from C functions that otherwise treat
objects generically.

\section{Reference Counting}

For most of the functions in the Python/C API, if a function retains a
reference to a Python object passed as an argument, then the function
will increase the reference count of the object.  It is unnecessary
for the caller to increase the reference count of an argument in
anticipation of the object's retention.

Usually, Python objects returned from functions should be treated as
new objects.  Functions that return objects assume that the caller
will retain a reference and the reference count of the object has
already been incremented to account for this fact.  A caller that does
not retain a reference to an object that is returned from a function
must decrement the reference count of the object (using
\code{Py_DECREF()}) to prevent memory leaks.

Exceptions to these rules will be noted with the individual functions.

\section{Include Files}

All function, type and macro definitions needed to use the Python/C
API are included in your code by the following line:

\code{\#include "Python.h"}

This implies inclusion of the following standard header files:
stdio.h, string.h, errno.h, and stdlib.h (if available).

All user visible names defined by Python.h (except those defined by
the included standard headers) have one of the prefixes \code{Py} or
\code{_Py}.  Names beginning with \code{_Py} are for internal use
only.


\chapter{Initialization and Shutdown of an Embedded Python Interpreter}

When embedding the Python interpreter in a C or C++ program, the
interpreter must be initialized.

\begin{cfuncdesc}{void}{PyInitialize}{}
This function initializes the interpreter.  It must be called before
any interaction with the interpreter takes place.  If it is called
more than once, the second and further calls have no effect.

The function performs the following tasks: create an environment in
which modules can be imported and Python code can be executed;
initialize the \code{__builtin__} module; initialize the \code{sys}
module; initialize \code{sys.path}; initialize signal handling; and
create the empty \code{__main__} module.

In the current system, there is no way to undo all these
initializations or to create additional interpreter environments.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{Py_AtExit}{void (*func) ()}
Register a cleanup function to be called when Python exits.  The
cleanup function will be called with no arguments and should return no
value.  At most 32 cleanup functions can be registered.  When the
registration is successful, \code{Py_AtExit} returns 0; on failure, it
returns -1.  Each cleanup function will be called t most once.  The
cleanup function registered last is called first.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_Exit}{int status}
Exit the current process.  This calls \code{Py_Cleanup()} (see next
item) and performs additional cleanup (under some circumstances it
will attempt to delete all modules), and then calls the standard C
library function \code{exit(status)}.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_Cleanup}{}
Perform some of the cleanup that \code{Py_Exit} performs, but don't
exit the process.  In particular, this invokes the user's
\code{sys.exitfunc} function (if defined at all), and it invokes the
cleanup functions registered with \code{Py_AtExit()}, in reverse order
of their registration.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_FatalError}{char *message}
Print a fatal error message and die.  No cleanup is performed.  This
function should only be invoked when a condition is detected that
would make it dangerous to continue using the Python interpreter;
e.g., when the object administration appears to be corrupted.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyImport_Init}{}
Initialize the module table.  For internal use only.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyImport_Cleanup}{}
Empty the module table.  For internal use only.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyBuiltin_Init}{}
Initialize the \code{__builtin__} module.  For internal use only.
\end{cfuncdesc}

XXX Other init functions: PyEval_InitThreads, PyOS_InitInterrupts,
PyMarshal_Init, PySys_Init.

\chapter{Reference Counting}

The functions in this chapter are used for managing reference counts
of Python objects.

\begin{cfuncdesc}{void}{Py_INCREF}{PyObject *o}
Increment the reference count for object \code{o}.  The object must
not be \NULL{}; if you aren't sure that it isn't \NULL{}, use
\code{Py_XINCREF()}.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_XINCREF}{PyObject *o}
Increment the reference count for object \code{o}.  The object may be
\NULL{}, in which case the function has no effect.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_DECREF}{PyObject *o}
Decrement the reference count for object \code{o}.  The object must
not be \NULL{}; if you aren't sure that it isn't \NULL{}, use
\code{Py_XDECREF()}.  If the reference count reaches zero, the object's
type's deallocation function (which must not be \NULL{}) is invoked.

\strong{Warning:} The deallocation function can cause arbitrary Python
code to be invoked (e.g. when a class instance with a \code{__del__()}
method is deallocated).  While exceptions in such code are not
propagated, the executed code has free access to all Python global
variables.  This means that any object that is reachable from a global
variable should be in a consistent state before \code{Py_DECREF()} is
invoked.  For example, code to delete an object from a list should
copy a reference to the deleted object in a temporary variable, update
the list data structure, and then call \code{Py_DECREF()} for the
temporary variable.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_XDECREF}{PyObject *o}
Decrement the reference count for object \code{o}.The object may be
\NULL{}, in which case the function has no effect; otherwise the
effect is the same as for \code{Py_DECREF()}, and the same warning
applies.
\end{cfuncdesc}

The following functions are only for internal use:
\code{_Py_Dealloc}, \code{_Py_ForgetReference}, \code{_Py_NewReference},
as well as the global variable \code{_Py_RefTotal}.


\chapter{Exception Handling}

The functions in this chapter will let you handle and raise Python
exceptions.  It is important to understand some of the basics of
Python exception handling.  It works somewhat like the Unix
\code{errno} variable: there is a global indicator (per thread) of the
last error that occurred.  Most functions don't clear this on success,
but will set it to indicate the cause of the error on failure.  Most
functions also return an error indicator, usually \NULL{} if they are
supposed to return a pointer, or -1 if they return an integer
(exception: the \code{PyArg_Parse*()} functions return 1 for success and
0 for failure).  When a function must fail because of some function it
called failed, it generally doesn't set the error indicator; the
function it called already set it.

The error indicator consists of three Python objects corresponding to
the Python variables \code{sys.exc_type}, \code{sys.exc_value} and
\code{sys.exc_traceback}.  API functions exist to interact with the
error indicator in various ways.  There is a separate error indicator
for each thread.

% XXX Order of these should be more thoughtful.
% Either alphabetical or some kind of structure.

\begin{cfuncdesc}{void}{PyErr_Print}{}
Print a standard traceback to \code{sys.stderr} and clear the error
indicator.  Call this function only when the error indicator is set.
(Otherwise it will cause a fatal error!)
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyErr_Occurred}{}
Test whether the error indicator is set.  If set, return the exception
\code{type} (the first argument to the last call to one of the
\code{PyErr_Set*()} functions or to \code{PyErr_Restore()}).  If not
set, return \NULL{}.  You do not own a reference to the return value,
so you do not need to \code{Py_DECREF()} it.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_Clear}{}
Clear the error indicator.  If the error indicator is not set, there
is no effect.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_Fetch}{PyObject **ptype, PyObject **pvalue, PyObject **ptraceback}
Retrieve the error indicator into three variables whose addresses are
passed.  If the error indicator is not set, set all three variables to
\NULL{}.  If it is set, it will be cleared and you own a reference to
each object retrieved.  The value and traceback object may be \NULL{}
even when the type object is not.  \strong{Note:} this function is
normally only used by code that needs to handle exceptions or by code
that needs to save and restore the error indicator temporarily.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_Restore}{PyObject *type, PyObject *value, PyObject *traceback}
Set  the error indicator from the three objects.  If the error
indicator is already set, it is cleared first.  If the objects are
\NULL{}, the error indicator is cleared.  Do not pass a \NULL{} type
and non-\NULL{} value or traceback.  The exception type should be a
string or class; if it is a class, the value should be an instance of
that class.  Do not pass an invalid exception type or value.
(Violating these rules will cause subtle problems later.)  This call
takes away a reference to each object, i.e. you must own a reference
to each object before the call and after the call you no longer own
these references.  (If you don't understand this, don't use this
function.  I warned you.)  \strong{Note:} this function is normally
only used by code that needs to save and restore the error indicator
temporarily.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_SetString}{PyObject *type, char *message}
This is the most common way to set the error indicator.  The first
argument specifies the exception type; it is normally one of the
standard exceptions, e.g. \code{PyExc_RuntimeError}.  You need not
increment its reference count.  The second argument is an error
message; it is converted to a string object.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_SetObject}{PyObject *type, PyObject *value}
This function is similar to \code{PyErr_SetString()} but lets you
specify an arbitrary Python object for the ``value'' of the exception.
You need not increment its reference count.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_SetNone}{PyObject *type}
This is a shorthand for \code{PyErr_SetString(\var{type}, Py_None}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyErr_BadArgument}{}
This is a shorthand for \code{PyErr_SetString(PyExc_TypeError,
\var{message})}, where \var{message} indicates that a built-in operation
was invoked with an illegal argument.  It is mostly for internal use.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyErr_NoMemory}{}
This is a shorthand for \code{PyErr_SetNone(PyExc_MemoryError)}; it
returns \NULL{} so an object allocation function can write
\code{return PyErr_NoMemory();} when  it runs out of memory.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyErr_SetFromErrno}{PyObject *type}
This is a convenience function to raise an exception when a C library
function has returned an error and set the C variable \code{errno}.
It constructs a tuple object whose first item is the integer
\code{errno} value and whose second item is the corresponding error
message (gotten from \code{strerror()}), and then calls
\code{PyErr_SetObject(\var{type}, \var{object})}.  On \UNIX{}, when
the \code{errno} value is \code{EINTR}, indicating an interrupted
system call, this calls \code{PyErr_CheckSignals()}, and if that set
the error indicator, leaves it set to that.  The function always
returns \NULL{}, so a wrapper function around a system call can write 
\code{return PyErr_NoMemory();} when  the system call returns an error.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_BadInternalCall}{}
This is a shorthand for \code{PyErr_SetString(PyExc_TypeError,
\var{message})}, where \var{message} indicates that an internal
operation (e.g. a Python/C API function) was invoked with an illegal
argument.  It is mostly for internal use.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyErr_CheckSignals}{}
This function interacts with Python's signal handling.  It checks
whether a signal has been sent to the processes and if so, invokes the
corresponding signal handler.  If the \code{signal} module is
supported, this can invoke a signal handler written in Python.  In all
cases, the default effect for \code{SIGINT} is to raise the
\code{KeyboadInterrupt} exception.  If an exception is raised the
error indicator is set and the function returns 1; otherwise the
function returns 0.  The error indicator may or may not be cleared if
it was previously set.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyErr_SetInterrupt}{}
This function is obsolete (XXX or platform dependent?).  It simulates
the effect of a \code{SIGINT} signal arriving -- the next time
\code{PyErr_CheckSignals()} is called, \code{KeyboadInterrupt} will be
raised.
\end{cfuncdesc}

\section{Standard Exceptions}

All standard Python exceptions are available as global variables whose
names are \code{PyExc_} followed by the Python exception name.
These have the type \code{PyObject *}; they are all string objects.
For completion, here are all the variables:
\code{PyExc_AccessError},
\code{PyExc_AssertionError},
\code{PyExc_AttributeError},
\code{PyExc_EOFError},
\code{PyExc_FloatingPointError},
\code{PyExc_IOError},
\code{PyExc_ImportError},
\code{PyExc_IndexError},
\code{PyExc_KeyError},
\code{PyExc_KeyboardInterrupt},
\code{PyExc_MemoryError},
\code{PyExc_NameError},
\code{PyExc_OverflowError},
\code{PyExc_RuntimeError},
\code{PyExc_SyntaxError},
\code{PyExc_SystemError},
\code{PyExc_SystemExit},
\code{PyExc_TypeError},
\code{PyExc_ValueError},
\code{PyExc_ZeroDivisionError}.


\chapter{Utilities}

The functions in this chapter perform various utility tasks, such as
parsing function arguments and constructing Python values from C
values.

\begin{cfuncdesc}{int}{Py_FdIsInteractive}{FILE *fp, char *filename}
Return true (nonzero) if the standard I/O file \code{fp} with name
\code{filename} is deemed interactive.  This is the case for files for
which \code{isatty(fileno(fp))} is true.  If the global flag
\code{Py_InteractiveFlag} is true, this function also returns true if
the \code{name} pointer is \NULL{} or if the name is equal to one of
the strings \code{"<stdin>"} or \code{"???"}.
\end{cfuncdesc}

\begin{cfuncdesc}{long}{PyOS_GetLastModificationTime}{char *filename}
Return the time of last modification of the file \code{filename}.
The result is encoded in the same way as the timestamp returned by
the standard C library function \code{time()}.
\end{cfuncdesc}


\chapter{Debugging}

XXX Explain Py_DEBUG, Py_TRACE_REFS, Py_REF_DEBUG.


\chapter{The Very High Level Layer}

The functions in this chapter will let you execute Python source code
given in a file or a buffer, but they will not let you interact in a
more detailed way with the interpreter.

\begin{cfuncdesc}{int}{PyRun_AnyFile}{FILE *, char *}
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyRun_SimpleString}{char *}
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyRun_SimpleFile}{FILE *, char *}
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyRun_InteractiveOne}{FILE *, char *}
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyRun_InteractiveLoop}{FILE *, char *}
\end{cfuncdesc}

\begin{cfuncdesc}{struct _node *}{PyParser_SimpleParseString}{char *, int}
\end{cfuncdesc}

\begin{cfuncdesc}{struct _node *}{PyParser_SimpleParseFile}{FILE *, char *, int}
\end{cfuncdesc}

\begin{cfuncdesc}{}{PyObject *PyRun_String}{char *, int, PyObject *, PyObject *}
\end{cfuncdesc}

\begin{cfuncdesc}{}{PyObject *PyRun_File}{FILE *, char *, int, PyObject *, PyObject *}
\end{cfuncdesc}

\begin{cfuncdesc}{}{PyObject *Py_CompileString}{char *, char *, int}
\end{cfuncdesc}


\chapter{Abstract Objects Layer}

The functions in this chapter interact with Python objects regardless
of their type, or with wide classes of object types (e.g. all
numerical types, or all sequence types).  When used on object types
for which they do not apply, they will flag a Python exception.

\section{Object Protocol}

\begin{cfuncdesc}{int}{PyObject_Print}{PyObject *o, FILE *fp, int flags}
Print an object \code{o}, on file \code{fp}.  Returns -1 on error
The flags argument is used to enable certain printing
options. The only option currently supported is \code{Py_Print_RAW}. 
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyObject_HasAttrString}{PyObject *o, char *attr_name}
Returns 1 if o has the attribute attr_name, and 0 otherwise.
This is equivalent to the Python expression:
\code{hasattr(o,attr_name)}.
This function always succeeds.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyObject_GetAttrString}{PyObject *o, char *attr_name}
Retrieve an attributed named attr_name from object o.
Returns the attribute value on success, or \NULL{} on failure.
This is the equivalent of the Python expression: \code{o.attr_name}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_HasAttr}{PyObject *o, PyObject *attr_name}
Returns 1 if o has the attribute attr_name, and 0 otherwise.
This is equivalent to the Python expression:
\code{hasattr(o,attr_name)}. 
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyObject_GetAttr}{PyObject *o, PyObject *attr_name}
Retrieve an attributed named attr_name form object o.
Returns the attribute value on success, or \NULL{} on failure.
This is the equivalent of the Python expression: o.attr_name.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_SetAttrString}{PyObject *o, char *attr_name, PyObject *v}
Set the value of the attribute named \code{attr_name}, for object \code{o},
to the value \code{v}. Returns -1 on failure.  This is
the equivalent of the Python statement: \code{o.attr_name=v}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_SetAttr}{PyObject *o, PyObject *attr_name, PyObject *v}
Set the value of the attribute named \code{attr_name}, for
object \code{o},
to the value \code{v}. Returns -1 on failure.  This is
the equivalent of the Python statement: \code{o.attr_name=v}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_DelAttrString}{PyObject *o, char *attr_name}
Delete attribute named \code{attr_name}, for object \code{o}. Returns -1 on
failure.  This is the equivalent of the Python
statement: \code{del o.attr_name}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_DelAttr}{PyObject *o, PyObject *attr_name}
Delete attribute named \code{attr_name}, for object \code{o}. Returns -1 on
failure.  This is the equivalent of the Python
statement: \code{del o.attr_name}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_Cmp}{PyObject *o1, PyObject *o2, int *result}
Compare the values of \code{o1} and \code{o2} using a routine provided by
\code{o1}, if one exists, otherwise with a routine provided by \code{o2}.
The result of the comparison is returned in \code{result}.  Returns
-1 on failure.  This is the equivalent of the Python
statement: \code{result=cmp(o1,o2)}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_Compare}{PyObject *o1, PyObject *o2}
Compare the values of \code{o1} and \code{o2} using a routine provided by
\code{o1}, if one exists, otherwise with a routine provided by \code{o2}.
Returns the result of the comparison on success.  On error,
the value returned is undefined. This is equivalent to the
Python expression: \code{cmp(o1,o2)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyObject_Repr}{PyObject *o}
Compute the string representation of object, \code{o}.  Returns the
string representation on success, \NULL{} on failure.  This is
the equivalent of the Python expression: \code{repr(o)}.
Called by the \code{repr()} built-in function and by reverse quotes.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyObject_Str}{PyObject *o}
Compute the string representation of object, \code{o}.  Returns the
string representation on success, \NULL{} on failure.  This is
the equivalent of the Python expression: \code{str(o)}.
Called by the \code{str()} built-in function and by the \code{print}
statement.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyCallable_Check}{PyObject *o}
Determine if the object \code{o}, is callable.  Return 1 if the
object is callable and 0 otherwise.
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyObject_CallObject}{PyObject *callable_object, PyObject *args}
Call a callable Python object \code{callable_object}, with
arguments given by the tuple \code{args}.  If no arguments are
needed, then args may be \NULL{}.  Returns the result of the
call on success, or \NULL{} on failure.  This is the equivalent
of the Python expression: \code{apply(o, args)}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyObject_CallFunction}{PyObject *callable_object, char *format, ...}
Call a callable Python object \code{callable_object}, with a
variable number of C arguments. The C arguments are described
using a mkvalue-style format string. The format may be \NULL{},
indicating that no arguments are provided.  Returns the
result of the call on success, or \NULL{} on failure.  This is
the equivalent of the Python expression: \code{apply(o,args)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyObject_CallMethod}{PyObject *o, char *m, char *format, ...}
Call the method named \code{m} of object \code{o} with a variable number of
C arguments.  The C arguments are described by a mkvalue
format string.  The format may be \NULL{}, indicating that no
arguments are provided. Returns the result of the call on
success, or \NULL{} on failure.  This is the equivalent of the
Python expression: \code{o.method(args)}.
Note that Special method names, such as "\code{__add__}",
"\code{__getitem__}", and so on are not supported. The specific
abstract-object routines for these must be used.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_Hash}{PyObject *o}
Compute and return the hash value of an object \code{o}.  On
failure, return -1.  This is the equivalent of the Python
expression: \code{hash(o)}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_IsTrue}{PyObject *o}
Returns 1 if the object \code{o} is considered to be true, and
0 otherwise. This is equivalent to the Python expression:
\code{not not o}.
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyObject_Type}{PyObject *o}
On success, returns a type object corresponding to the object
type of object \code{o}. On failure, returns \NULL{}.  This is
equivalent to the Python expression: \code{type(o)}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyObject_Length}{PyObject *o}
Return the length of object \code{o}.  If the object \code{o} provides
both sequence and mapping protocols, the sequence length is
returned. On error, -1 is returned.  This is the equivalent
to the Python expression: \code{len(o)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyObject_GetItem}{PyObject *o, PyObject *key}
Return element of \code{o} corresponding to the object \code{key} or \NULL{}
on failure. This is the equivalent of the Python expression:
\code{o[key]}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_SetItem}{PyObject *o, PyObject *key, PyObject *v}
Map the object \code{key} to the value \code{v}.
Returns -1 on failure.  This is the equivalent
of the Python statement: \code{o[key]=v}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyObject_DelItem}{PyObject *o, PyObject *key, PyObject *v}
Delete the mapping for \code{key} from \code{*o}.  Returns -1
on failure.
This is the equivalent of the Python statement: \code{del o[key]}.
\end{cfuncdesc}


\section{Number Protocol}

\begin{cfuncdesc}{int}{PyNumber_Check}{PyObject *o}
Returns 1 if the object \code{o} provides numeric protocols, and
false otherwise. 
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Add}{PyObject *o1, PyObject *o2}
Returns the result of adding \code{o1} and \code{o2}, or null on failure.
This is the equivalent of the Python expression: \code{o1+o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Subtract}{PyObject *o1, PyObject *o2}
Returns the result of subtracting \code{o2} from \code{o1}, or null on
failure.  This is the equivalent of the Python expression:
\code{o1-o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Multiply}{PyObject *o1, PyObject *o2}
Returns the result of multiplying \code{o1} and \code{o2}, or null on
failure.  This is the equivalent of the Python expression:
\code{o1*o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Divide}{PyObject *o1, PyObject *o2}
Returns the result of dividing \code{o1} by \code{o2}, or null on failure.
This is the equivalent of the Python expression: \code{o1/o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Remainder}{PyObject *o1, PyObject *o2}
Returns the remainder of dividing \code{o1} by \code{o2}, or null on
failure.  This is the equivalent of the Python expression:
\code{o1\%o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Divmod}{PyObject *o1, PyObject *o2}
See the built-in function divmod.  Returns \NULL{} on failure.
This is the equivalent of the Python expression:
\code{divmod(o1,o2)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Power}{PyObject *o1, PyObject *o2, PyObject *o3}
See the built-in function pow.  Returns \NULL{} on failure.
This is the equivalent of the Python expression:
\code{pow(o1,o2,o3)}, where \code{o3} is optional.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Negative}{PyObject *o}
Returns the negation of \code{o} on success, or null on failure.
This is the equivalent of the Python expression: \code{-o}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Positive}{PyObject *o}
Returns \code{o} on success, or \NULL{} on failure.
This is the equivalent of the Python expression: \code{+o}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Absolute}{PyObject *o}
Returns the absolute value of \code{o}, or null on failure.  This is
the equivalent of the Python expression: \code{abs(o)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Invert}{PyObject *o}
Returns the bitwise negation of \code{o} on success, or \NULL{} on
failure.  This is the equivalent of the Python expression:
\code{\~o}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Lshift}{PyObject *o1, PyObject *o2}
Returns the result of left shifting \code{o1} by \code{o2} on success, or
\NULL{} on failure.  This is the equivalent of the Python
expression: \code{o1 << o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Rshift}{PyObject *o1, PyObject *o2}
Returns the result of right shifting \code{o1} by \code{o2} on success, or
\NULL{} on failure.  This is the equivalent of the Python
expression: \code{o1 >> o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_And}{PyObject *o1, PyObject *o2}
Returns the result of "anding" \code{o2} and \code{o2} on success and \NULL{}
on failure. This is the equivalent of the Python
expression: \code{o1 and o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Xor}{PyObject *o1, PyObject *o2}
Returns the bitwise exclusive or of \code{o1} by \code{o2} on success, or
\NULL{} on failure.  This is the equivalent of the Python
expression: \code{o1\^{ }o2}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyNumber_Or}{PyObject *o1, PyObject *o2}
Returns the result of \code{o1} and \code{o2} on success, or \NULL{} on
failure.  This is the equivalent of the Python expression: 
\code{o1 or o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Coerce}{PyObject *o1, PyObject *o2}
This function takes the addresses of two variables of type
\code{PyObject*}.

If the objects pointed to by \code{*p1} and \code{*p2} have the same type,
increment their reference count and return 0 (success).
If the objects can be converted to a common numeric type,
replace \code{*p1} and \code{*p2} by their converted value (with 'new'
reference counts), and return 0.
If no conversion is possible, or if some other error occurs,
return -1 (failure) and don't increment the reference counts.
The call \code{PyNumber_Coerce(\&o1, \&o2)} is equivalent to the Python
statement \code{o1, o2 = coerce(o1, o2)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Int}{PyObject *o}
Returns the \code{o} converted to an integer object on success, or
\NULL{} on failure.  This is the equivalent of the Python
expression: \code{int(o)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Long}{PyObject *o}
Returns the \code{o} converted to a long integer object on success,
or \NULL{} on failure.  This is the equivalent of the Python
expression: \code{long(o)}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyNumber_Float}{PyObject *o}
Returns the \code{o} converted to a float object on success, or \NULL{}
on failure.  This is the equivalent of the Python expression:
\code{float(o)}.
\end{cfuncdesc}


\section{Sequence protocol}

\begin{cfuncdesc}{int}{PySequence_Check}{PyObject *o}
Return 1 if the object provides sequence protocol, and 0
otherwise.  
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PySequence_Concat}{PyObject *o1, PyObject *o2}
Return the concatination of \code{o1} and \code{o2} on success, and \NULL{} on
failure.   This is the equivalent of the Python
expression: \code{o1+o2}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PySequence_Repeat}{PyObject *o, int count}
Return the result of repeating sequence object \code{o} \code{count} times,
or \NULL{} on failure.  This is the equivalent of the Python
expression: \code{o*count}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PySequence_GetItem}{PyObject *o, int i}
Return the ith element of \code{o}, or \NULL{} on failure. This is the
equivalent of the Python expression: \code{o[i]}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PySequence_GetSlice}{PyObject *o, int i1, int i2}
Return the slice of sequence object \code{o} between \code{i1} and \code{i2}, or
\NULL{} on failure. This is the equivalent of the Python
expression, \code{o[i1:i2]}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PySequence_SetItem}{PyObject *o, int i, PyObject *v}
Assign object \code{v} to the \code{i}th element of \code{o}.
Returns -1 on failure.  This is the equivalent of the Python
statement, \code{o[i]=v}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PySequence_DelItem}{PyObject *o, int i}
Delete the \code{i}th element of object \code{v}.  Returns
-1 on failure.  This is the equivalent of the Python
statement: \code{del o[i]}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PySequence_SetSlice}{PyObject *o, int i1, int i2, PyObject *v}
Assign the sequence object \code{v} to the slice in sequence
object \code{o} from \code{i1} to \code{i2}.  This is the equivalent of the Python
statement, \code{o[i1:i2]=v}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PySequence_DelSlice}{PyObject *o, int i1, int i2}
Delete the slice in sequence object, \code{o}, from \code{i1} to \code{i2}.
Returns -1 on failure. This is the equivalent of the Python
statement: \code{del o[i1:i2]}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PySequence_Tuple}{PyObject *o}
Returns the \code{o} as a tuple on success, and \NULL{} on failure.
This is equivalent to the Python expression: \code{tuple(o)}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PySequence_Count}{PyObject *o, PyObject *value}
Return the number of occurrences of \code{value} on \code{o}, that is,
return the number of keys for which \code{o[key]==value}.  On
failure, return -1.  This is equivalent to the Python
expression: \code{o.count(value)}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PySequence_In}{PyObject *o, PyObject *value}
Determine if \code{o} contains \code{value}.  If an item in \code{o} is equal to
\code{value}, return 1, otherwise return 0.  On error, return -1.  This
is equivalent to the Python expression: \code{value in o}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PySequence_Index}{PyObject *o, PyObject *value}
Return the first index for which \code{o[i]==value}.  On error,
return -1.    This is equivalent to the Python
expression: \code{o.index(value)}.
\end{cfuncdesc}

\section{Mapping protocol}

\begin{cfuncdesc}{int}{PyMapping_Check}{PyObject *o}
Return 1 if the object provides mapping protocol, and 0
otherwise.  
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyMapping_Length}{PyObject *o}
Returns the number of keys in object \code{o} on success, and -1 on
failure.  For objects that do not provide sequence protocol,
this is equivalent to the Python expression: \code{len(o)}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyMapping_DelItemString}{PyObject *o, char *key}
Remove the mapping for object \code{key} from the object \code{o}.
Return -1 on failure.  This is equivalent to
the Python statement: \code{del o[key]}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyMapping_DelItem}{PyObject *o, PyObject *key}
Remove the mapping for object \code{key} from the object \code{o}.
Return -1 on failure.  This is equivalent to
the Python statement: \code{del o[key]}.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyMapping_HasKeyString}{PyObject *o, char *key}
On success, return 1 if the mapping object has the key \code{key}
and 0 otherwise.  This is equivalent to the Python expression:
\code{o.has_key(key)}. 
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{int}{PyMapping_HasKey}{PyObject *o, PyObject *key}
Return 1 if the mapping object has the key \code{key}
and 0 otherwise.  This is equivalent to the Python expression:
\code{o.has_key(key)}. 
This function always succeeds.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyMapping_Keys}{PyObject *o}
On success, return a list of the keys in object \code{o}.  On
failure, return \NULL{}. This is equivalent to the Python
expression: \code{o.keys()}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyMapping_Values}{PyObject *o}
On success, return a list of the values in object \code{o}.  On
failure, return \NULL{}. This is equivalent to the Python
expression: \code{o.values()}.
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyMapping_Items}{PyObject *o}
On success, return a list of the items in object \code{o}, where
each item is a tuple containing a key-value pair.  On
failure, return \NULL{}. This is equivalent to the Python
expression: \code{o.items()}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyMapping_Clear}{PyObject *o}
Make object \code{o} empty.  Returns 1 on success and 0 on failure.
This is equivalent to the Python statement:
\code{for key in o.keys(): del o[key]}
\end{cfuncdesc}


\begin{cfuncdesc}{PyObject*}{PyMapping_GetItemString}{PyObject *o, char *key}
Return element of \code{o} corresponding to the object \code{key} or \NULL{}
on failure. This is the equivalent of the Python expression:
\code{o[key]}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyMapping_SetItemString}{PyObject *o, char *key, PyObject *v}
Map the object \code{key} to the value \code{v} in object \code{o}.  Returns 
-1 on failure.  This is the equivalent of the Python
statement: \code{o[key]=v}.
\end{cfuncdesc}


\section{Constructors}

\begin{cfuncdesc}{PyObject*}{PyFile_FromString}{char *file_name, char *mode}
On success, returns a new file object that is opened on the
file given by \code{file_name}, with a file mode given by \code{mode},
where \code{mode} has the same semantics as the standard C routine,
fopen.  On failure, return -1.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyFile_FromFile}{FILE *fp, char *file_name, char *mode, int close_on_del}
Return a new file object for an already opened standard C
file pointer, \code{fp}.  A file name, \code{file_name}, and open mode,
\code{mode}, must be provided as well as a flag, \code{close_on_del}, that
indicates whether the file is to be closed when the file
object is destroyed.  On failure, return -1.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyFloat_FromDouble}{double v}
Returns a new float object with the value \code{v} on success, and
\NULL{} on failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyInt_FromLong}{long v}
Returns a new int object with the value \code{v} on success, and
\NULL{} on failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyList_New}{int l}
Returns a new list of length \code{l} on success, and \NULL{} on
failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyLong_FromLong}{long v}
Returns a new long object with the value \code{v} on success, and
\NULL{} on failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyLong_FromDouble}{double v}
Returns a new long object with the value \code{v} on success, and
\NULL{} on failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyDict_New}{}
Returns a new empty dictionary on success, and \NULL{} on
failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyString_FromString}{char *v}
Returns a new string object with the value \code{v} on success, and
\NULL{} on failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyString_FromStringAndSize}{char *v, int l}
Returns a new string object with the value \code{v} and length \code{l}
on success, and \NULL{} on failure.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject*}{PyTuple_New}{int l}
Returns a new tuple of length \code{l} on success, and \NULL{} on
failure.
\end{cfuncdesc}


\chapter{Concrete Objects Layer}

The functions in this chapter are specific to certain Python object
types.  Passing them an object of the wrong type is not a good idea;
if you receive an object from a Python program and you are not sure
that it has the right type, you must perform a type check first;
e.g. to check that an object is a dictionary, use
\code{PyDict_Check()}.


\chapter{Defining New Object Types}

\begin{cfuncdesc}{PyObject *}{_PyObject_New}{PyTypeObject *type}
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{_PyObject_NewVar}{PyTypeObject *type, int size}
\end{cfuncdesc}

\begin{cfuncdesc}{TYPE}{_PyObject_NEW}{TYPE, PyTypeObject *}
\end{cfuncdesc}

\begin{cfuncdesc}{TYPE}{_PyObject_NEW_VAR}{TYPE, PyTypeObject *, int size}
\end{cfuncdesc}

\chapter{Initialization, Finalization, and Threads}

% XXX Check argument/return type of all these

\begin{cfuncdesc}{void}{Py_Initialize}{}
Initialize the Python interpreter.  In an application embedding 
Python, this should be called before using any other Python/C API 
functions; with the exception of \code{Py_SetProgramName()}, 
\code{PyEval_InitThreads()}, \code{PyEval_ReleaseLock()}, and 
\code{PyEval_AcquireLock()}.  This initializes the table of loaded 
modules (\code{sys.modules}), and creates the fundamental modules 
\code{__builtin__}, \code{__main__} and \code{sys}.  It also 
initializes the module search path (\code{sys.path}).  It does not set 
\code{sys.argv}; use \code{PySys_SetArgv()} for that.  It is a fatal 
error to call it for a second time without calling 
\code{Py_Finalize()} first.  There is no return value; it is a fatal 
error if the initialization fails.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_Finalize}{}
Undo all initializations made by \code{Py_Initialize()} and subsequent 
use of Python/C API functions, and destroy all sub-interpreters (see 
\code{Py_NewInterpreter()} below) that were created and not yet 
destroyed since the last call to \code{Py_Initialize()}.  Ideally, 
this frees all memory allocated by the Python interpreter.  It is a 
fatal error to call it for a second time without calling 
\code{Py_Initialize()} again first.  There is no return value; errors 
during finalization are ignored.

This function is provided for a number of reasons.  An embedding 
application might want to restart Python without having to restart the 
application itself.  An application that has loaded the Python 
interpreter from a dynamically loadable library (or DLL) might want to 
free all memory allocated by Python before unloading the DLL. During a 
hunt for memory leaks in an application a developer might want to free 
all memory allocated by Python before exiting from the application.

\emph{Bugs and caveats:} The destruction of modules and objects in 
modules is done in random order; this may cause destructors 
(\code{__del__} methods) to fail when they depend on other objects 
(even functions) or modules.  Dynamically loaded extension modules 
loaded by Python are not unloaded.  Small amounts of memory allocated 
by the Python interpreter may not be freed (if you find a leak, please 
report it).  Memory tied up in circular references between objects is 
not freed.  Some memory allocated by extension modules may not be 
freed.  Some extension may not work properly if their initialization 
routine is called more than once; this can happen if an applcation 
calls \code{Py_Initialize()} and \code{Py_Finalize()} more than once.
\end{cfuncdesc}

\begin{cfuncdesc}{PyThreadState *}{Py_NewInterpreter}{}
Create a new sub-interpreter.  This is an (almost) totally separate 
environment for the execution of Python code.  In particular, the new 
interpreter has separate, independent versions of all imported 
modules, including the fundamental modules \code{__builtin__}, 
\code{__main__} and \code{sys}.  The table of loaded modules 
(\code{sys.modules}) and the module search path (\code{sys.path}) are 
also separate.  The new environment has no \code{sys.argv} variable.  
It has new standard I/O stream file objects \code{sys.stdin}, 
\code{sys.stdout} and \code{sys.stderr} (however these refer to the 
same underlying \code{FILE} structures in the C library).

The return value points to the first thread state created in the new 
sub-interpreter.  This thread state is made the current thread state.  
Note that no actual thread is created; see the discussion of thread 
states below.  If creation of the new interpreter is unsuccessful, 
\code{NULL} is returned; no exception is set since the exception state 
is stored in the current thread state and there may not be a current 
thread state.  (Like all other Python/C API functions, the global 
interpreter lock must be held before calling this function and is 
still held when it returns; however, unlike most other Python/C API 
functions, there needn't be a current thread state on entry.)

Extension modules are shared between (sub-)interpreters as follows: 
the first time a particular extension is imported, it is initialized 
normally, and a (shallow) copy of its module's dictionary is 
squirreled away.  When the same extension is imported by another 
(sub-)interpreter, a new module is initialized and filled with the 
contents of this copy; the extension's \code{init} function is not 
called.  Note that this is different from what happens when as 
extension is imported after the interpreter has been completely 
re-initialized by calling \code{Py_Finalize()} and 
\code{Py_Initialize()}; in that case, the extension's \code{init} 
function \emph{is} called again.

\emph{Bugs and caveats:} Because sub-interpreters (and the main 
interpreter) are part of the same process, the insulation between them 
isn't perfect -- for example, using low-level file operations like 
\code{os.close()} they can (accidentally or maliciously) affect each 
other's open files.  Because of the way extensions are shared between 
(sub-)interpreters, some extensions may not work properly; this is 
especially likely when the extension makes use of (static) global 
variables, or when the extension manipulates its module's dictionary 
after its initialization.  It is possible to insert objects created in 
one sub-interpreter into a namespace of another sub-interpreter; this 
should be done with great care to avoid sharing user-defined 
functions, methods, instances or classes between sub-interpreters, 
since import operations executed by such objects may affect the 
wrong (sub-)interpreter's dictionary of loaded modules.  (XXX This is 
a hard-to-fix bug that will be addressed in a future release.)
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_EndInterpreter}{PyThreadState *tstate}
Destroy the (sub-)interpreter represented by the given thread state.  
The given thread state must be the current thread state.  See the 
discussion of thread states below.  When the call returns, the current 
thread state is \code{NULL}.  All thread states associated with this 
interpreted are destroyed.  (The global interpreter lock must be held 
before calling this function and is still held when it returns.)  
\code{Py_Finalize()} will destroy all sub-interpreters that haven't 
been explicitly destroyed at that point.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{Py_SetProgramName}{char *name}
This function should be called before \code{Py_Initialize()} is called 
for the first time, if it is called at all.  It tells the interpreter 
the value of the \code{argv[0]} argument to the \code{main()} function 
of the program.  This is used by \code{Py_GetPath()} and some other 
functions below to find the Python run-time libraries relative to the 
interpreter executable.  The default value is \code{"python"}.  The 
argument should point to a zero-terminated character string in static 
storage whose contents will not change for the duration of the 
program's execution.  No code in the Python interpreter will change 
the contents of this storage.
\end{cfuncdesc}

\begin{cfuncdesc}{char *}{Py_GetProgramName}{}
Return the program name set with \code{Py_SetProgramName()}, or the 
default.  The returned string points into static storage; the caller 
should not modify its value.
\end{cfuncdesc}

\begin{cfuncdesc}{char *}{Py_GetPrefix}{}
Return the ``prefix'' for installed platform-independent files.  This 
is derived through a number of complicated rules from the program name 
set with \code{Py_SetProgramName()} and some environment variables; 
for example, if the program name is \code{"/usr/local/bin/python"}, 
the prefix is \code{"/usr/local"}.  The returned string points into 
static storage; the caller should not modify its value.  This 
corresponds to the \code{prefix} variable in the top-level 
\code{Makefile} and the \code{--prefix} argument to the 
\code{configure} script at build time.  The value is available to 
Python code as \code{sys.prefix}.  It is only useful on Unix.  See 
also the next function.
\end{cfuncdesc}

\begin{cfuncdesc}{char *}{Py_GetExecPrefix}{}
Return the ``exec-prefix'' for installed platform-\emph{de}pendent 
files.  This is derived through a number of complicated rules from the 
program name set with \code{Py_SetProgramName()} and some environment 
variables; for example, if the program name is 
\code{"/usr/local/bin/python"}, the exec-prefix is 
\code{"/usr/local"}.  The returned string points into static storage; 
the caller should not modify its value.  This corresponds to the 
\code{exec_prefix} variable in the top-level \code{Makefile} and the 
\code{--exec_prefix} argument to the \code{configure} script at build 
time.  The value is available to Python code as 
\code{sys.exec_prefix}.  It is only useful on Unix.

Background: The exec-prefix differs from the prefix when platform 
dependent files (such as executables and shared libraries) are 
installed in a different directory tree.  In a typical installation, 
platform dependent files may be installed in the 
\code{"/usr/local/plat"} subtree while platform independent may be 
installed in \code{"/usr/local"}.

Generally speaking, a platform is a combination of hardware and 
software families, e.g.  Sparc machines running the Solaris 2.x 
operating system are considered the same platform, but Intel machines 
running Solaris 2.x are another platform, and Intel machines running 
Linux are yet another platform.  Different major revisions of the same 
operating system generally also form different platforms.  Non-Unix 
operating systems are a different story; the installation strategies 
on those systems are so different that the prefix and exec-prefix are 
meaningless, and set to the empty string.  Note that compiled Python 
bytecode files are platform independent (but not independent from the 
Python version by which they were compiled!).

System administrators will know how to configure the \code{mount} or 
\code{automount} programs to share \code{"/usr/local"} between platforms 
while having \code{"/usr/local/plat"} be a different filesystem for each 
platform.
\end{cfuncdesc}

\begin{cfuncdesc}{char *}{Py_GetProgramFullPath}{}
Return the full program name of the Python executable; this is 
computed as a side-effect of deriving the default module search path 
from the program name (set by \code{Py_SetProgramName()} above).  The 
returned string points into static storage; the caller should not 
modify its value.  The value is available to Python code as 
\code{sys.executable}.  % XXX is that the right sys.name?
\end{cfuncdesc}

\begin{cfuncdesc}{char *}{Py_GetPath}{}
Return the default module search path; this is computed from the 
program name (set by \code{Py_SetProgramName()} above) and some 
environment variables.  The returned string consists of a series of 
directory names separated by a platform dependent delimiter character.  
The delimiter character is \code{':'} on Unix, \code{';'} on 
DOS/Windows, and \code{'\\n'} (the ASCII newline character) on 
Macintosh.  The returned string points into static storage; the caller 
should not modify its value.  The value is available to Python code 
as the list \code{sys.path}, which may be modified to change the 
future search path for loaded modules.

% XXX should give the exact rules
\end{cfuncdesc}

\begin{cfuncdesc}{const char *}{Py_GetVersion}{}
Return the version of this Python interpreter.  This is a string that 
looks something like

\begin{verbatim}
"1.5a3 (#67, Aug 1 1997, 22:34:28) [GCC 2.7.2.2]"
\end{verbatim}

The first word (up to the first space character) is the current Python 
version; the first three characters are the major and minor version 
separated by a period.  The returned string points into static storage; 
the caller should not modify its value.  The value is available to 
Python code as the list \code{sys.version}.
\end{cfuncdesc}

\begin{cfuncdesc}{const char *}{Py_GetPlatform}{}
Return the platform identifier for the current platform.  On Unix, 
this is formed from the ``official'' name of the operating system, 
converted to lower case, followed by the major revision number; e.g., 
for Solaris 2.x, which is also known as SunOS 5.x, the value is 
\code{"sunos5"}.  On Macintosh, it is \code{"mac"}.  On Windows, it 
is \code{"win"}.  The returned string points into static storage; 
the caller should not modify its value.  The value is available to 
Python code as \code{sys.platform}.
\end{cfuncdesc}

\begin{cfuncdesc}{const char *}{Py_GetCopyright}{}
Return the official copyright string for the current Python version, 
for example

\code{"Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam"}

The returned string points into static storage; the caller should not 
modify its value.  The value is available to Python code as the list 
\code{sys.copyright}.
\end{cfuncdesc}

\begin{cfuncdesc}{const char *}{Py_GetCompiler}{}
Return an indication of the compiler used to build the current Python 
version, in square brackets, for example

\code{"[GCC 2.7.2.2]"}

The returned string points into static storage; the caller should not 
modify its value.  The value is available to Python code as part of 
the variable \code{sys.version}.
\end{cfuncdesc}

\begin{cfuncdesc}{const char *}{Py_GetBuildInfo}{}
Return information about the sequence number and build date and time 
of the current Python interpreter instance, for example

\begin{verbatim}
"#67, Aug  1 1997, 22:34:28"
\end{verbatim}

The returned string points into static storage; the caller should not 
modify its value.  The value is available to Python code as part of 
the variable \code{sys.version}.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PySys_SetArgv}{int argc, char **argv}
% XXX
\end{cfuncdesc}

% XXX Other PySys thingies (doesn't really belong in this chapter)

\section{Thread State and the Global Interpreter Lock}

\begin{cfuncdesc}{void}{PyEval_AcquireLock}{}
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyEval_ReleaseLock}{}
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyEval_AcquireThread}{PyThreadState *tstate}
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyEval_ReleaseThread}{PyThreadState *tstate}
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyEval_RestoreThread}{PyThreadState *tstate}
\end{cfuncdesc}

\begin{cfuncdesc}{PyThreadState *}{PyEval_SaveThread}{}
\end{cfuncdesc}

% XXX These aren't really C functions!
\begin{cfuncdesc}{}{Py_BEGIN_ALLOW_THREADS}{}
\end{cfuncdesc}

\begin{cfuncdesc}{}{Py_BEGIN_END_THREADS}{}
\end{cfuncdesc}

\begin{cfuncdesc}{}{Py_BEGIN_XXX_THREADS}{}
\end{cfuncdesc}


XXX To be done:

PyObject, PyVarObject

PyObject_HEAD, PyObject_HEAD_INIT, PyObject_VAR_HEAD

Typedefs:
unaryfunc, binaryfunc, ternaryfunc, inquiry, coercion, intargfunc,
intintargfunc, intobjargproc, intintobjargproc, objobjargproc,
getreadbufferproc, getwritebufferproc, getsegcountproc,
destructor, printfunc, getattrfunc, getattrofunc, setattrfunc,
setattrofunc, cmpfunc, reprfunc, hashfunc

PyNumberMethods

PySequenceMethods

PyMappingMethods

PyBufferProcs

PyTypeObject

DL_IMPORT

PyType_Type

Py*_Check

Py_None, _Py_NoneStruct

_PyObject_New, _PyObject_NewVar

PyObject_NEW, PyObject_NEW_VAR


\chapter{Specific Data Types}

This chapter describes the functions that deal with specific types of 
Python objects.  It is structured like the ``family tree'' of Python 
object types.


\section{Fundamental Objects}

This section describes Python type objects and the singleton object 
\code{None}.


\subsection{Type Objects}

\begin{ctypedesc}{PyTypeObject}

\end{ctypedesc}

\begin{cvardesc}{PyObject *}{PyType_Type}

\end{cvardesc}


\subsection{The None Object}

\begin{cvardesc}{PyObject *}{Py_None}
macro
\end{cvardesc}


\section{Sequence Objects}

Generic operations on sequence objects were discussed in the previous 
chapter; this section deals with the specific kinds of sequence 
objects that are intrinsuc to the Python language.


\subsection{String Objects}

\begin{ctypedesc}{PyStringObject}
This subtype of \code{PyObject} represents a Python string object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyString_Type}
This instance of \code{PyTypeObject} represents the Python string type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyString_Check}{PyObject *o}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyString_FromStringAndSize}{const char *, int}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyString_FromString}{const char *}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyString_Size}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{char *}{PyString_AsString}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyString_Concat}{PyObject **, PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyString_ConcatAndDel}{PyObject **, PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{_PyString_Resize}{PyObject **, int}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyString_Format}{PyObject *, PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyString_InternInPlace}{PyObject **}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyString_InternFromString}{const char *}

\end{cfuncdesc}

\begin{cfuncdesc}{char *}{PyString_AS_STRING}{PyStringObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyString_GET_SIZE}{PyStringObject *}

\end{cfuncdesc}


\subsection{Tuple Objects}

\begin{ctypedesc}{PyTupleObject}
This subtype of \code{PyObject} represents a Python tuple object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyTuple_Type}
This instance of \code{PyTypeObject} represents the Python tuple type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyTuple_Check}{PyObject *p}
Return true if the argument is a tuple object.
\end{cfuncdesc}

\begin{cfuncdesc}{PyTupleObject *}{PyTuple_New}{int s}
Return a new tuple object of size \code{s}
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyTuple_Size}{PyTupleObject *p}
akes a pointer to a tuple object, and returns the size
of that tuple.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyTuple_GetItem}{PyTupleObject *p, int pos}
returns the object at position \code{pos} in the tuple pointed
to by \code{p}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyTuple_GET_ITEM}{PyTupleObject *p, int pos}
does the same, but does no checking of it's
arguments.
\end{cfuncdesc}

\begin{cfuncdesc}{PyTupleObject *}{PyTuple_GetSlice}{PyTupleObject *p,
            int low,
            int high}
takes a slice of the tuple pointed to by \code{p} from
\code{low} to \code{high} and returns it as a new tuple.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyTuple_SetItem}{PyTupleObject *p,
            int pos,
            PyObject *o}
inserts a reference to object \code{o} at position \code{pos} of
the tuple pointed to by \code{p}. It returns 0 on success.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyTuple_SET_ITEM}{PyTupleObject *p,
            int pos,
            PyObject *o}

does the same, but does no error checking, and
should \emph{only} be used to fill in brand new tuples.
\end{cfuncdesc}

\begin{cfuncdesc}{PyTupleObject *}{_PyTuple_Resize}{PyTupleObject *p,
            int new,
            int last_is_sticky}
can be used to resize a tuple. Because tuples are
\emph{supposed} to be immutable, this should only be used if there is only
one module referencing the object. Do \emph{not} use this if the tuple may
already be known to some other part of the code. \code{last_is_sticky} is
a flag - if set, the tuple will grow or shrink at the front, otherwise
it will grow or shrink at the end. Think of this as destroying the old
tuple and creating a new one, only more efficiently.
\end{cfuncdesc}


\subsection{List Objects}

\begin{ctypedesc}{PyListObject}
This subtype of \code{PyObject} represents a Python list object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyList_Type}
This instance of \code{PyTypeObject} represents the Python list type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyList_Check}{PyObject *p}
returns true if it's argument is a \code{PyListObject}
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyList_New}{int size}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_Size}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyList_GetItem}{PyObject *, int}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_SetItem}{PyObject *, int, PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_Insert}{PyObject *, int, PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_Append}{PyObject *, PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyList_GetSlice}{PyObject *, int, int}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_SetSlice}{PyObject *, int, int, PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_Sort}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_Reverse}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyList_AsTuple}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyList_GET_ITEM}{PyObject *list, int i}

\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyList_GET_SIZE}{PyObject *list}

\end{cfuncdesc}


\section{Mapping Objects}

\subsection{Dictionary Objects}

\begin{ctypedesc}{PyDictObject}
This subtype of \code{PyObject} represents a Python dictionary object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyDict_Type}
This instance of \code{PyTypeObject} represents the Python dictionary type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyDict_Check}{PyObject *p}
returns true if it's argument is a PyDictObject
\end{cfuncdesc}

\begin{cfuncdesc}{PyDictObject *}{PyDict_New}{}
returns a new empty dictionary.
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyDict_Clear}{PyDictObject *p}
empties an existing dictionary and deletes it.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyDict_SetItem}{PyDictObject *p,
            PyObject *key,
            PyObject *val}
inserts \code{value} into the dictionary with a key of
\code{key}. Both \code{key} and \code{value} should be PyObjects, and \code{key} should
be hashable.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyDict_SetItemString}{PyDictObject *p,
            char *key,
            PyObject *val}
inserts \code{value} into the dictionary using \code{key}
as a key. \code{key} should be a char *
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyDict_DelItem}{PyDictObject *p, PyObject *key}
removes the entry in dictionary \code{p} with key \code{key}.
\code{key} is a PyObject.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyDict_DelItemString}{PyDictObject *p, char *key}
removes the entry in dictionary \code{p} which has a key
specified by the \code{char *}\code{key}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyDict_GetItem}{PyDictObject *p, PyObject *key}
returns the object from dictionary \code{p} which has a key
\code{key}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyDict_GetItemString}{PyDictObject *p, char *key}
does the same, but \code{key} is specified as a
\code{char *}, rather than a \code{PyObject *}.
\end{cfuncdesc}

\begin{cfuncdesc}{PyListObject *}{PyDict_Items}{PyDictObject *p}
returns a PyListObject containing all the items 
from the dictionary, as in the mapping method \code{items()} (see the Reference
Guide)
\end{cfuncdesc}

\begin{cfuncdesc}{PyListObject *}{PyDict_Keys}{PyDictObject *p}
returns a PyListObject containing all the keys 
from the dictionary, as in the mapping method \code{keys()} (see the Reference Guide)
\end{cfuncdesc}

\begin{cfuncdesc}{PyListObject *}{PyDict_Values}{PyDictObject *p}
returns a PyListObject containing all the values 
from the dictionary, as in the mapping method \code{values()} (see the Reference Guide)
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyDict_Size}{PyDictObject *p}
returns the number of items in the dictionary.
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyDict_Next}{PyDictObject *p,
            int ppos,
            PyObject **pkey,
            PyObject **pvalue}

\end{cfuncdesc}


\section{Numeric Objects}

\subsection{Plain Integer Objects}

\begin{ctypedesc}{PyIntObject}
This subtype of \code{PyObject} represents a Python integer object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyInt_Type}
This instance of \code{PyTypeObject} represents the Python plain 
integer type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyInt_Check}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{PyIntObject *}{PyInt_FromLong}{long ival}
creates a new integer object with a value of \code{ival}.

The current implementation keeps an array of integer objects for all
integers between -1 and 100, when you create an int in that range you
actually just get back a reference to the existing object. So it should
be possible to change the value of 1. I suspect the behaviour of python
in this case is undefined. :-)
\end{cfuncdesc}

\begin{cfuncdesc}{long}{PyInt_AS_LONG}{PyIntObject *io}
returns the value of the object \code{io}.
\end{cfuncdesc}

\begin{cfuncdesc}{long}{PyInt_AsLong}{PyObject *io}
will first attempt to cast the object to a PyIntObject, if
it is not already one, and the return it's value.
\end{cfuncdesc}

\begin{cfuncdesc}{long}{PyInt_GetMax}{}
returns the systems idea of the largest int it can handle
(LONG_MAX, as defined in the system header files)
\end{cfuncdesc}


\subsection{Long Integer Objects}

\begin{ctypedesc}{PyLongObject}
This subtype of \code{PyObject} represents a Python long integer object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyLong_Type}
This instance of \code{PyTypeObject} represents the Python long integer type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyLong_Check}{PyObject *p}
returns true if it's argument is a \code{PyLongObject}
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyLong_FromLong}{long}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyLong_FromUnsignedLong}{unsigned long}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyLong_FromDouble}{double}

\end{cfuncdesc}

\begin{cfuncdesc}{long}{PyLong_AsLong}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{unsigned long}{PyLong_AsUnsignedLong}{PyObject }

\end{cfuncdesc}

\begin{cfuncdesc}{double}{PyLong_AsDouble}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{*PyLong_FromString}{char *, char **, int}

\end{cfuncdesc}


\subsection{Floating Point Objects}

\begin{ctypedesc}{PyFloatObject}
This subtype of \code{PyObject} represents a Python floating point object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyFloat_Type}
This instance of \code{PyTypeObject} represents the Python floating 
point type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyFloat_Check}{PyObject *p}
returns true if it's argument is a \code{PyFloatObject}
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyFloat_FromDouble}{double}

\end{cfuncdesc}

\begin{cfuncdesc}{double}{PyFloat_AsDouble}{PyObject *}

\end{cfuncdesc}

\begin{cfuncdesc}{double}{PyFloat_AS_DOUBLE}{PyFloatObject *}

\end{cfuncdesc}


\subsection{Complex Number Objects}

\begin{ctypedesc}{Py_complex}
typedef struct {
   double real;
   double imag;
} 
\end{ctypedesc}

\begin{ctypedesc}{PyComplexObject}
This subtype of \code{PyObject} represents a Python complex number object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyComplex_Type}
This instance of \code{PyTypeObject} represents the Python complex 
number type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyComplex_Check}{PyObject *p}
returns true if it's argument is a \code{PyComplexObject}
\end{cfuncdesc}

\begin{cfuncdesc}{Py_complex}{_Py_c_sum}{Py_complex, Py_complex}

\end{cfuncdesc}

\begin{cfuncdesc}{Py_complex}{_Py_c_diff}{Py_complex, Py_complex}

\end{cfuncdesc}

\begin{cfuncdesc}{Py_complex}{_Py_c_neg}{Py_complex}

\end{cfuncdesc}

\begin{cfuncdesc}{Py_complex}{_Py_c_prod}{Py_complex, Py_complex}

\end{cfuncdesc}

\begin{cfuncdesc}{Py_complex}{_Py_c_quot}{Py_complex, Py_complex}

\end{cfuncdesc}

\begin{cfuncdesc}{Py_complex}{_Py_c_pow}{Py_complex, Py_complex}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyComplex_FromCComplex}{Py_complex}

\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyComplex_FromDoubles}{double real, double imag}

\end{cfuncdesc}

\begin{cfuncdesc}{double}{PyComplex_RealAsDouble}{PyObject *op}

\end{cfuncdesc}

\begin{cfuncdesc}{double}{PyComplex_ImagAsDouble}{PyObject *op}

\end{cfuncdesc}

\begin{cfuncdesc}{Py_complex}{PyComplex_AsCComplex}{PyObject *op}

\end{cfuncdesc}



\section{Other Objects}

\subsection{File Objects}

\begin{ctypedesc}{PyFileObject}
This subtype of \code{PyObject} represents a Python file object.
\end{ctypedesc}

\begin{cvardesc}{PyTypeObject}{PyFile_Type}
This instance of \code{PyTypeObject} represents the Python file type.
\end{cvardesc}

\begin{cfuncdesc}{int}{PyFile_Check}{PyObject *p}
returns true if it's argument is a \code{PyFileObject}
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyFile_FromString}{char *name, char *mode}
creates a new PyFileObject pointing to the file
specified in \code{name} with the mode specified in \code{mode}
\end{cfuncdesc}

\begin{cfuncdesc}{PyObject *}{PyFile_FromFile}{FILE *fp,
              char *name, char *mode, int (*close})
creates a new PyFileObject from the already-open \code{fp}.
The function \code{close} will be called when the file should be closed.
\end{cfuncdesc}

\begin{cfuncdesc}{FILE *}{PyFile_AsFile}{PyFileObject *p}
returns the file object associated with \code{p} as a \code{FILE *}
\end{cfuncdesc}

\begin{cfuncdesc}{PyStringObject *}{PyFile_GetLine}{PyObject *p, int n}
undocumented as yet
\end{cfuncdesc}

\begin{cfuncdesc}{PyStringObject *}{PyFile_Name}{PyObject *p}
returns the name of the file specified by \code{p} as a 
PyStringObject
\end{cfuncdesc}

\begin{cfuncdesc}{void}{PyFile_SetBufSize}{PyFileObject *p, int n}
on systems with \code{setvbuf} only
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyFile_SoftSpace}{PyFileObject *p, int newflag}
same as the file object method \code{softspace}
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyFile_WriteObject}{PyObject *obj, PyFileObject *p}
writes object \code{obj} to file object \code{p}
\end{cfuncdesc}

\begin{cfuncdesc}{int}{PyFile_WriteString}{char *s, PyFileObject *p}
writes string \code{s} to file object \code{p}
\end{cfuncdesc}


\input{api.ind}			% Index -- must be last

\end{document}
