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Marked reference to the Python Library Reference with \emph{}. 

Changed sample module creation of an exception to use PyErr_NewException().

Logical markup.
This commit is contained in:
Fred Drake 1998-03-03 17:52:07 +00:00
parent fcf275e0be
commit d7bb3032c1
2 changed files with 474 additions and 450 deletions
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@ -74,9 +74,9 @@ well as on your system setup; details are given in a later section.
Let's create an extension module called \samp{spam} (the favorite food
of Monty Python fans...) and let's say we want to create a Python
interface to the \C{} library function \code{system()}.\footnote{An
interface to the \C{} library function \cfunction{system()}.\footnote{An
interface for this function already exists in the standard module
\code{os} --- it was chosen as a simple and straightfoward example.}
\module{os} --- it was chosen as a simple and straightfoward example.}
This function takes a null-terminated character string as argument and
returns an integer. We want this function to be callable from Python
as follows:
@ -106,8 +106,8 @@ For convenience, and since they are used extensively by the Python
interpreter, \code{"Python.h"} includes a few standard header files:
\code{<stdio.h>}, \code{<string.h>}, \code{<errno.h>}, and
\code{<stdlib.h>}. If the latter header file does not exist on your
system, it declares the functions \code{malloc()}, \code{free()} and
\code{realloc()} directly.
system, it declares the functions \cfunction{malloc()},
\cfunction{free()} and \cfunction{realloc()} directly.
The next thing we add to our module file is the \C{} function that will
be called when the Python expression \samp{spam.system(\var{string})}
@ -166,42 +166,43 @@ and return an error value (usually a \NULL{} pointer). Exceptions
are stored in a static global variable inside the interpreter; if this
variable is \NULL{} no exception has occurred. A second global
variable stores the ``associated value'' of the exception (the second
argument to \code{raise}). A third variable contains the stack
argument to \keyword{raise}). A third variable contains the stack
traceback in case the error originated in Python code. These three
variables are the \C{} equivalents of the Python variables
\code{sys.exc_type}, \code{sys.exc_value} and \code{sys.exc_traceback}
(see the section on module \code{sys} in the Library Reference
Manual). It is important to know about them to understand how errors
are passed around.
(see the section on module \module{sys} in the \emph{Python Library
Reference}). It is important to know about them to understand how
errors are passed around.
The Python API defines a number of functions to set various types of
exceptions.
The most common one is \code{PyErr_SetString()}. Its arguments are an
exception object and a \C{} string. The exception object is usually a
predefined object like \code{PyExc_ZeroDivisionError}. The \C{} string
indicates the cause of the error and is converted to a Python string
object and stored as the ``associated value'' of the exception.
The most common one is \cfunction{PyErr_SetString()}. Its arguments
are an exception object and a \C{} string. The exception object is
usually a predefined object like \cdata{PyExc_ZeroDivisionError}. The
\C{} string indicates the cause of the error and is converted to a
Python string object and stored as the ``associated value'' of the
exception.
Another useful function is \code{PyErr_SetFromErrno()}, which only
Another useful function is \cfunction{PyErr_SetFromErrno()}, which only
takes an exception argument and constructs the associated value by
inspection of the (\UNIX{}) global variable \code{errno}. The most
general function is \code{PyErr_SetObject()}, which takes two object
inspection of the (\UNIX{}) global variable \cdata{errno}. The most
general function is \cfunction{PyErr_SetObject()}, which takes two object
arguments, the exception and its associated value. You don't need to
\code{Py_INCREF()} the objects passed to any of these functions.
\cfunction{Py_INCREF()} the objects passed to any of these functions.
You can test non-destructively whether an exception has been set with
\code{PyErr_Occurred()}. This returns the current exception object,
\cfunction{PyErr_Occurred()}. This returns the current exception object,
or \NULL{} if no exception has occurred. You normally don't need
to call \code{PyErr_Occurred()} to see whether an error occurred in a
to call \cfunction{PyErr_Occurred()} to see whether an error occurred in a
function call, since you should be able to tell from the return value.
When a function \var{f} that calls another function \var{g} detects
that the latter fails, \var{f} should itself return an error value
(e.g. \NULL{} or \code{-1}). It should \emph{not} call one of the
\code{PyErr_*()} functions --- one has already been called by \var{g}.
\cfunction{PyErr_*()} functions --- one has already been called by \var{g}.
\var{f}'s caller is then supposed to also return an error indication
to \emph{its} caller, again \emph{without} calling \code{PyErr_*()},
to \emph{its} caller, again \emph{without} calling \cfunction{PyErr_*()},
and so on --- the most detailed cause of the error was already
reported by the function that first detected it. Once the error
reaches the Python interpreter's main loop, this aborts the currently
@ -209,44 +210,44 @@ executing Python code and tries to find an exception handler specified
by the Python programmer.
(There are situations where a module can actually give a more detailed
error message by calling another \code{PyErr_*()} function, and in
error message by calling another \cfunction{PyErr_*()} function, and in
such cases it is fine to do so. As a general rule, however, this is
not necessary, and can cause information about the cause of the error
to be lost: most operations can fail for a variety of reasons.)
To ignore an exception set by a function call that failed, the exception
condition must be cleared explicitly by calling \code{PyErr_Clear()}.
The only time \C{} code should call \code{PyErr_Clear()} is if it doesn't
condition must be cleared explicitly by calling \cfunction{PyErr_Clear()}.
The only time \C{} code should call \cfunction{PyErr_Clear()} is if it doesn't
want to pass the error on to the interpreter but wants to handle it
completely by itself (e.g. by trying something else or pretending
nothing happened).
Note that a failing \code{malloc()} call must be turned into an
exception --- the direct caller of \code{malloc()} (or
\code{realloc()}) must call \code{PyErr_NoMemory()} and return a
failure indicator itself. All the object-creating functions
(\code{PyInt_FromLong()} etc.) already do this, so only if you call
\code{malloc()} directly this note is of importance.
Note that a failing \cfunction{malloc()} call must be turned into an
exception --- the direct caller of \cfunction{malloc()} (or
\cfunction{realloc()}) must call \cfunction{PyErr_NoMemory()} and
return a failure indicator itself. All the object-creating functions
(\cfunction{PyInt_FromLong()} etc.) already do this, so only if you
call \cfunction{malloc()} directly this note is of importance.
Also note that, with the important exception of
\cfunction{PyArg_ParseTuple()} and friends, functions that return an
integer status usually return a positive value or zero for success and
\code{-1} for failure, like \UNIX{} system calls.
Finally, be careful to clean up garbage (by making \code{Py_XDECREF()}
or \code{Py_DECREF()} calls for objects you have already created) when
you return an error indicator!
Finally, be careful to clean up garbage (by making
\cfunction{Py_XDECREF()} or \cfunction{Py_DECREF()} calls for objects
you have already created) when you return an error indicator!
The choice of which exception to raise is entirely yours. There are
predeclared \C{} objects corresponding to all built-in Python exceptions,
e.g. \code{PyExc_ZeroDevisionError} which you can use directly. Of
e.g. \cdata{PyExc_ZeroDevisionError} which you can use directly. Of
course, you should choose exceptions wisely --- don't use
\code{PyExc_TypeError} to mean that a file couldn't be opened (that
should probably be \code{PyExc_IOError}). If something's wrong with
\cdata{PyExc_TypeError} to mean that a file couldn't be opened (that
should probably be \cdata{PyExc_IOError}). If something's wrong with
the argument list, the \cfunction{PyArg_ParseTuple()} function usually
raises \code{PyExc_TypeError}. If you have an argument whose value
raises \cdata{PyExc_TypeError}. If you have an argument whose value
which must be in a particular range or must satisfy other conditions,
\code{PyExc_ValueError} is appropriate.
\cdata{PyExc_ValueError} is appropriate.
You can also define a new exception that is unique to your module.
For this, you usually declare a static object variable at the
@ -257,8 +258,8 @@ static PyObject *SpamError;
\end{verbatim}
and initialize it in your module's initialization function
(\code{initspam()}) with a string object, e.g. (leaving out the error
checking for now):
(\cfunction{initspam()}) with an exception object, e.g. (leaving out
the error checking for now):
\begin{verbatim}
void
@ -267,16 +268,19 @@ initspam()
PyObject *m, *d;
m = Py_InitModule("spam", SpamMethods);
d = PyModule_GetDict(m);
SpamError = PyString_FromString("spam.error");
SpamError = PyErr_NewException("spam.error", NULL, NULL);
PyDict_SetItemString(d, "error", SpamError);
}
\end{verbatim}
Note that the Python name for the exception object is
\code{spam.error}. It is conventional for module and exception names
to be spelled in lower case. It is also conventional that the
\emph{value} of the exception object is the same as its name, e.g.\
the string \code{"spam.error"}.
\exception{spam.error}. The \cfunction{PyErr_NewException()} function
may create either a string or class, depending on whether the
\samp{-X} flag was passed to the interpreter. If \samp{-X} was used,
\cdata{SpamError} will be a string object, otherwise it will be a
class object with the base class being \exception{Exception},
described in the \emph{Python Library Reference} under ``Built-in
Exceptions.''
\section{Back to the Example}
@ -294,24 +298,25 @@ It returns \NULL{} (the error indicator for functions returning
object pointers) if an error is detected in the argument list, relying
on the exception set by \cfunction{PyArg_ParseTuple()}. Otherwise the
string value of the argument has been copied to the local variable
\code{command}. This is a pointer assignment and you are not supposed
\cdata{command}. This is a pointer assignment and you are not supposed
to modify the string to which it points (so in Standard \C{}, the variable
\code{command} should properly be declared as \samp{const char
\cdata{command} should properly be declared as \samp{const char
*command}).
The next statement is a call to the \UNIX{} function \code{system()},
passing it the string we just got from \cfunction{PyArg_ParseTuple()}:
The next statement is a call to the \UNIX{} function
\cfunction{system()}, passing it the string we just got from
\cfunction{PyArg_ParseTuple()}:
\begin{verbatim}
sts = system(command);
\end{verbatim}
Our \code{spam.system()} function must return the value of \code{sts}
as a Python object. This is done using the function
\code{Py_BuildValue()}, which is something like the inverse of
\cfunction{PyArg_ParseTuple()}: it takes a format string and an arbitrary
number of \C{} values, and returns a new Python object. More info on
\code{Py_BuildValue()} is given later.
Our \function{spam.system()} function must return the value of
\cdata{sts} as a Python object. This is done using the function
\cfunction{Py_BuildValue()}, which is something like the inverse of
\cfunction{PyArg_ParseTuple()}: it takes a format string and an
arbitrary number of \C{} values, and returns a new Python object.
More info on \cfunction{Py_BuildValue()} is given later.
\begin{verbatim}
return Py_BuildValue("i", sts);
@ -321,7 +326,7 @@ In this case, it will return an integer object. (Yes, even integers
are objects on the heap in Python!)
If you have a \C{} function that returns no useful argument (a function
returning \code{void}), the corresponding Python function must return
returning \ctype{void}), the corresponding Python function must return
\code{None}. You need this idiom to do so:
\begin{verbatim}
@ -329,7 +334,7 @@ returning \code{void}), the corresponding Python function must return
return Py_None;
\end{verbatim}
\code{Py_None} is the \C{} name for the special Python object
\cdata{Py_None} is the \C{} name for the special Python object
\code{None}. It is a genuine Python object (not a \NULL{}
pointer, which means ``error'' in most contexts, as we have seen).
@ -337,7 +342,7 @@ pointer, which means ``error'' in most contexts, as we have seen).
\section{The Module's Method Table and Initialization Function}
\label{methodTable}
I promised to show how \code{spam_system()} is called from Python
I promised to show how \cfunction{spam_system()} is called from Python
programs. First, we need to list its name and address in a ``method
table'':
@ -361,7 +366,7 @@ the Python-level parameters to be passed in as a tuple acceptable for
parsing via \cfunction{PyArg_ParseTuple()}; more information on this
function is provided below.
The \code{METH_KEYWORDS} bit may be set in the third field if keyword
The \constant{METH_KEYWORDS} bit may be set in the third field if keyword
arguments should be passed to the function. In this case, the \C{}
function should accept a third \samp{PyObject *} parameter which will
be a dictionary of keywords. Use \cfunction{PyArg_ParseTupleAndKeywords()}
@ -379,16 +384,17 @@ initspam()
}
\end{verbatim}
When the Python program imports module \code{spam} for the first time,
\code{initspam()} is called. It calls \code{Py_InitModule()}, which
creates a ``module object'' (which is inserted in the dictionary
\code{sys.modules} under the key \code{"spam"}), and inserts built-in
function objects into the newly created module based upon the table
(an array of \code{PyMethodDef} structures) that was passed as its
second argument. \code{Py_InitModule()} returns a pointer to the
module object that it creates (which is unused here). It aborts with
a fatal error if the module could not be initialized satisfactorily,
so the caller doesn't need to check for errors.
When the Python program imports module \module{spam} for the first
time, \cfunction{initspam()} is called. It calls
\cfunction{Py_InitModule()}, which creates a ``module object'' (which
is inserted in the dictionary \code{sys.modules} under the key
\code{"spam"}), and inserts built-in function objects into the newly
created module based upon the table (an array of \ctype{PyMethodDef}
structures) that was passed as its second argument.
\cfunction{Py_InitModule()} returns a pointer to the module object
that it creates (which is unused here). It aborts with a fatal error
if the module could not be initialized satisfactorily, so the caller
doesn't need to check for errors.
\section{Compilation and Linkage}
@ -411,11 +417,11 @@ the \file{Modules} directory, add a line to the file
spam spammodule.o
\end{verbatim}
and rebuild the interpreter by running \code{make} in the toplevel
directory. You can also run \code{make} in the \file{Modules}
and rebuild the interpreter by running \program{make} in the toplevel
directory. You can also run \program{make} in the \file{Modules}
subdirectory, but then you must first rebuilt the \file{Makefile}
there by running \code{make Makefile}. (This is necessary each time
you change the \file{Setup} file.)
there by running `\program{make} Makefile'. (This is necessary each
time you change the \file{Setup} file.)
If your module requires additional libraries to link with, these can
be listed on the line in the \file{Setup} file as well, for instance:
@ -445,8 +451,8 @@ Calling a Python function is easy. First, the Python program must
somehow pass you the Python function object. You should provide a
function (or some other interface) to do this. When this function is
called, save a pointer to the Python function object (be careful to
\code{Py_INCREF()} it!) in a global variable --- or whereever you see fit.
For example, the following function might be part of a module
\cfunction{Py_INCREF()} it!) in a global variable --- or whereever you
see fit. For example, the following function might be part of a module
definition:
\begin{verbatim}
@ -465,18 +471,18 @@ my_set_callback(dummy, arg)
}
\end{verbatim}
The macros \code{Py_XINCREF()} and \code{Py_XDECREF()} increment/decrement
the reference count of an object and are safe in the presence of
\NULL{} pointers. More info on them in the section on Reference
Counts below.
The macros \cfunction{Py_XINCREF()} and \cfunction{Py_XDECREF()}
increment/decrement the reference count of an object and are safe in
the presence of \NULL{} pointers. More info on them in the section on
Reference Counts below.
Later, when it is time to call the function, you call the \C{} function
\code{PyEval_CallObject()}. This function has two arguments, both
\cfunction{PyEval_CallObject()}. This function has two arguments, both
pointers to arbitrary Python objects: the Python function, and the
argument list. The argument list must always be a tuple object, whose
length is the number of arguments. To call the Python function with
no arguments, pass an empty tuple; to call it with one argument, pass
a singleton tuple. \code{Py_BuildValue()} returns a tuple when its
a singleton tuple. \cfunction{Py_BuildValue()} returns a tuple when its
format string consists of zero or more format codes between
parentheses. For example:
@ -493,26 +499,26 @@ parentheses. For example:
Py_DECREF(arglist);
\end{verbatim}
\code{PyEval_CallObject()} returns a Python object pointer: this is
the return value of the Python function. \code{PyEval_CallObject()} is
\cfunction{PyEval_CallObject()} returns a Python object pointer: this is
the return value of the Python function. \cfunction{PyEval_CallObject()} is
``reference-count-neutral'' with respect to its arguments. In the
example a new tuple was created to serve as the argument list, which
is \code{Py_DECREF()}-ed immediately after the call.
is \cfunction{Py_DECREF()}-ed immediately after the call.
The return value of \code{PyEval_CallObject()} is ``new'': either it
The return value of \cfunction{PyEval_CallObject()} is ``new'': either it
is a brand new object, or it is an existing object whose reference
count has been incremented. So, unless you want to save it in a
global variable, you should somehow \code{Py_DECREF()} the result,
global variable, you should somehow \cfunction{Py_DECREF()} the result,
even (especially!) if you are not interested in its value.
Before you do this, however, it is important to check that the return
value isn't \NULL{}. If it is, the Python function terminated by raising
an exception. If the \C{} code that called \code{PyEval_CallObject()} is
called from Python, it should now return an error indication to its
Python caller, so the interpreter can print a stack trace, or the
calling Python code can handle the exception. If this is not possible
or desirable, the exception should be cleared by calling
\code{PyErr_Clear()}. For example:
value isn't \NULL{}. If it is, the Python function terminated by
raising an exception. If the \C{} code that called
\cfunction{PyEval_CallObject()} is called from Python, it should now
return an error indication to its Python caller, so the interpreter
can print a stack trace, or the calling Python code can handle the
exception. If this is not possible or desirable, the exception should
be cleared by calling \cfunction{PyErr_Clear()}. For example:
\begin{verbatim}
if (result == NULL)
@ -522,14 +528,15 @@ or desirable, the exception should be cleared by calling
\end{verbatim}
Depending on the desired interface to the Python callback function,
you may also have to provide an argument list to \code{PyEval_CallObject()}.
In some cases the argument list is also provided by the Python
program, through the same interface that specified the callback
function. It can then be saved and used in the same manner as the
function object. In other cases, you may have to construct a new
tuple to pass as the argument list. The simplest way to do this is to
call \code{Py_BuildValue()}. For example, if you want to pass an integral
event code, you might use the following code:
you may also have to provide an argument list to
\cfunction{PyEval_CallObject()}. In some cases the argument list is
also provided by the Python program, through the same interface that
specified the callback function. It can then be saved and used in the
same manner as the function object. In other cases, you may have to
construct a new tuple to pass as the argument list. The simplest way
to do this is to call \cfunction{Py_BuildValue()}. For example, if
you want to pass an integral event code, you might use the following
code:
\begin{verbatim}
PyObject *arglist;
@ -543,10 +550,10 @@ event code, you might use the following code:
Py_DECREF(result);
\end{verbatim}
Note the placement of \code{Py_DECREF(argument)} immediately after the call,
before the error check! Also note that strictly spoken this code is
not complete: \code{Py_BuildValue()} may run out of memory, and this should
be checked.
Note the placement of \samp{Py_DECREF(arglist)} immediately after the
call, before the error check! Also note that strictly spoken this
code is not complete: \cfunction{Py_BuildValue()} may run out of
memory, and this should be checked.
\section{Format Strings for \sectcode{PyArg_ParseTuple()}}
@ -594,7 +601,7 @@ must not contain embedded null bytes; if it does, a \exception{TypeError}
exception is raised.
\item[\samp{s\#} (string) {[char *, int]}]
This variant on \code{'s'} stores into two \C{} variables, the first one
This variant on \samp{s} stores into two \C{} variables, the first one
a pointer to a character string, the second one its length. In this
case the Python string may contain embedded null bytes.
@ -603,32 +610,32 @@ Like \samp{s}, but the Python object may also be \code{None}, in which
case the \C{} pointer is set to \NULL{}.
\item[\samp{z\#} (string or \code{None}) {[char *, int]}]
This is to \code{'s\#'} as \code{'z'} is to \code{'s'}.
This is to \samp{s\#} as \samp{z} is to \samp{s}.
\item[\samp{b} (integer) {[char]}]
Convert a Python integer to a tiny int, stored in a \C{} \code{char}.
Convert a Python integer to a tiny int, stored in a \C{} \ctype{char}.
\item[\samp{h} (integer) {[short int]}]
Convert a Python integer to a \C{} \code{short int}.
Convert a Python integer to a \C{} \ctype{short int}.
\item[\samp{i} (integer) {[int]}]
Convert a Python integer to a plain \C{} \code{int}.
Convert a Python integer to a plain \C{} \ctype{int}.
\item[\samp{l} (integer) {[long int]}]
Convert a Python integer to a \C{} \code{long int}.
Convert a Python integer to a \C{} \ctype{long int}.
\item[\samp{c} (string of length 1) {[char]}]
Convert a Python character, represented as a string of length 1, to a
\C{} \code{char}.
\C{} \ctype{char}.
\item[\samp{f} (float) {[float]}]
Convert a Python floating point number to a \C{} \code{float}.
Convert a Python floating point number to a \C{} \ctype{float}.
\item[\samp{d} (float) {[double]}]
Convert a Python floating point number to a \C{} \code{double}.
Convert a Python floating point number to a \C{} \ctype{double}.
\item[\samp{D} (complex) {[Py_complex]}]
Convert a Python complex number to a \C{} \code{Py_complex} structure.
Convert a Python complex number to a \C{} \ctype{Py_complex} structure.
\item[\samp{O} (object) {[PyObject *]}]
Store a Python object (without any conversion) in a \C{} object pointer.
@ -636,36 +643,36 @@ The \C{} program thus receives the actual object that was passed. The
object's reference count is not increased. The pointer stored is not
\NULL{}.
\item[\samp{O!} (object) {[\var{typeobject}, PyObject *]}]
\item[\samp{O!} (object) {[\var{typeobject}, PyObject *{]}}]
Store a Python object in a \C{} object pointer. This is similar to
\samp{O}, but takes two \C{} arguments: the first is the address of a
Python type object, the second is the address of the \C{} variable (of
type \code{PyObject *}) into which the object pointer is stored.
type \ctype{PyObject *}) into which the object pointer is stored.
If the Python object does not have the required type, a
\code{TypeError} exception is raised.
\exception{TypeError} exception is raised.
\item[\samp{O\&} (object) {[\var{converter}, \var{anything}]}]
\item[\samp{O\&} (object) {[\var{converter}, \var{anything}{]}}]
Convert a Python object to a \C{} variable through a \var{converter}
function. This takes two arguments: the first is a function, the
second is the address of a \C{} variable (of arbitrary type), converted
to \code{void *}. The \var{converter} function in turn is called as
to \ctype{void *}. The \var{converter} function in turn is called as
follows:
\code{\var{status} = \var{converter}(\var{object}, \var{address});}
where \var{object} is the Python object to be converted and
\var{address} is the \code{void *} argument that was passed to
\code{PyArg_ConvertTuple()}. The returned \var{status} should be
\var{address} is the \ctype{void *} argument that was passed to
\cfunction{PyArg_ConvertTuple()}. The returned \var{status} should be
\code{1} for a successful conversion and \code{0} if the conversion
has failed. When the conversion fails, the \var{converter} function
should raise an exception.
\item[\samp{S} (string) {[PyStringObject *]}]
Like \samp{O} but requires that the Python object is a string object.
Raises a \code{TypeError} exception if the object is not a string
object. The \C{} variable may also be declared as \code{PyObject *}.
Raises a \exception{TypeError} exception if the object is not a string
object. The \C{} variable may also be declared as \ctype{PyObject *}.
\item[\samp{(\var{items})} (tuple) {[\var{matching-items}]}]
\item[\samp{(\var{items})} (tuple) {[\var{matching-items}{]}}]
The object must be a Python tuple whose length is the number of format
units in \var{items}. The \C{} arguments must correspond to the
individual format units in \var{items}. Format units for tuples may
@ -688,13 +695,13 @@ not occur inside nested parentheses. They are:
Indicates that the remaining arguments in the Python argument list are
optional. The \C{} variables corresponding to optional arguments should
be initialized to their default value --- when an optional argument is
not specified, the \code{PyArg_ParseTuple} does not touch the contents
not specified, \cfuntion{PyArg_ParseTuple()} does not touch the contents
of the corresponding \C{} variable(s).
\item[\samp{:}]
The list of format units ends here; the string after the colon is used
as the function name in error messages (the ``associated value'' of
the exceptions that \code{PyArg_ParseTuple} raises).
the exceptions that \cfunction{PyArg_ParseTuple()} raises).
\item[\samp{;}]
The list of format units ends here; the string after the colon is used
@ -828,7 +835,7 @@ initkeywdarg()
\section{The \sectcode{Py_BuildValue()} Function}
\label{buildValue}
This function is the counterpart to \code{PyArg_ParseTuple()}. It is
This function is the counterpart to \cfunction{PyArg_ParseTuple()}. It is
declared as follows:
\begin{verbatim}
@ -836,19 +843,20 @@ PyObject *Py_BuildValue(char *format, ...);
\end{verbatim}
It recognizes a set of format units similar to the ones recognized by
\code{PyArg_ParseTuple()}, but the arguments (which are input to the
\cfunction{PyArg_ParseTuple()}, but the arguments (which are input to the
function, not output) must not be pointers, just values. It returns a
new Python object, suitable for returning from a \C{} function called
from Python.
One difference with \code{PyArg_ParseTuple()}: while the latter
One difference with \cfunction{PyArg_ParseTuple()}: while the latter
requires its first argument to be a tuple (since Python argument lists
are always represented as tuples internally), \code{BuildValue()} does
not always build a tuple. It builds a tuple only if its format string
contains two or more format units. If the format string is empty, it
returns \code{None}; if it contains exactly one format unit, it
returns whatever object is described by that format unit. To force it
to return a tuple of size 0 or one, parenthesize the format string.
are always represented as tuples internally),
\cfunction{Py_BuildValue()} does not always build a tuple. It builds
a tuple only if its format string contains two or more format units.
If the format string is empty, it returns \code{None}; if it contains
exactly one format unit, it returns whatever object is described by
that format unit. To force it to return a tuple of size 0 or one,
parenthesize the format string.
In the following description, the quoted form is the format unit; the
entry in (round) parentheses is the Python object type that the format
@ -877,7 +885,7 @@ Same as \samp{s}.
Same as \samp{s\#}.
\item[\samp{i} (integer) {[int]}]
Convert a plain \C{} \code{int} to a Python integer object.
Convert a plain \C{} \ctype{int} to a Python integer object.
\item[\samp{b} (integer) {[char]}]
Same as \samp{i}.
@ -886,14 +894,14 @@ Same as \samp{i}.
Same as \samp{i}.
\item[\samp{l} (integer) {[long int]}]
Convert a \C{} \code{long int} to a Python integer object.
Convert a \C{} \ctype{long int} to a Python integer object.
\item[\samp{c} (string of length 1) {[char]}]
Convert a \C{} \code{int} representing a character to a Python string of
Convert a \C{} \ctype{int} representing a character to a Python string of
length 1.
\item[\samp{d} (float) {[double]}]
Convert a \C{} \code{double} to a Python floating point number.
Convert a \C{} \ctype{double} to a Python floating point number.
\item[\samp{f} (float) {[float]}]
Same as \samp{d}.
@ -903,9 +911,9 @@ Pass a Python object untouched (except for its reference count, which
is incremented by one). If the object passed in is a \NULL{}
pointer, it is assumed that this was caused because the call producing
the argument found an error and set an exception. Therefore,
\code{Py_BuildValue()} will return \NULL{} but won't raise an
\cfunction{Py_BuildValue()} will return \NULL{} but won't raise an
exception. If no exception has been raised yet,
\code{PyExc_SystemError} is set.
\cdata{PyExc_SystemError} is set.
\item[\samp{S} (object) {[PyObject *]}]
Same as \samp{O}.
@ -913,7 +921,7 @@ Same as \samp{O}.
\item[\samp{O\&} (object) {[\var{converter}, \var{anything}]}]
Convert \var{anything} to a Python object through a \var{converter}
function. The function is called with \var{anything} (which should be
compatible with \code{void *}) as its argument and should return a
compatible with \ctype{void *}) as its argument and should return a
``new'' Python object, or \NULL{} if an error occurred.
\item[\samp{(\var{items})} (tuple) {[\var{matching-items}]}]
@ -932,7 +940,7 @@ and value, respectively.
\end{description}
If there is an error in the format string, the
\code{PyExc_SystemError} exception is raised and \NULL{} returned.
\cdata{PyExc_SystemError} exception is raised and \NULL{} returned.
Examples (to the left the call, to the right the resulting Python value):
@ -960,24 +968,26 @@ Examples (to the left the call, to the right the resulting Python value):
%\subsection{Introduction}
In languages like \C{} or \Cpp{}, the programmer is responsible for
dynamic allocation and deallocation of memory on the heap. In \C{}, this
is done using the functions \code{malloc()} and \code{free()}. In
\Cpp{}, the operators \code{new} and \code{delete} are used with
essentially the same meaning; they are actually implemented using
\code{malloc()} and \code{free()}, so we'll restrict the following
discussion to the latter.
dynamic allocation and deallocation of memory on the heap. In \C{},
this is done using the functions \cfunction{malloc()} and
\cfunction{free()}. In \Cpp{}, the operators \keyword{new} and
\keyword{delete} are used with essentially the same meaning; they are
actually implemented using \cfunction{malloc()} and
\cfunction{free()}, so we'll restrict the following discussion to the
latter.
Every block of memory allocated with \code{malloc()} should eventually
be returned to the pool of available memory by exactly one call to
\code{free()}. It is important to call \code{free()} at the right
time. If a block's address is forgotten but \code{free()} is not
called for it, the memory it occupies cannot be reused until the
program terminates. This is called a \dfn{memory leak}. On the other
hand, if a program calls \code{free()} for a block and then continues
to use the block, it creates a conflict with re-use of the block
through another \code{malloc()} call. This is called \dfn{using freed
memory}. It has the same bad consequences as referencing uninitialized
data --- core dumps, wrong results, mysterious crashes.
Every block of memory allocated with \cfunction{malloc()} should
eventually be returned to the pool of available memory by exactly one
call to \cfunction{free()}. It is important to call
\cfunction{free()} at the right time. If a block's address is
forgotten but \cfunction{free()} is not called for it, the memory it
occupies cannot be reused until the program terminates. This is
called a \dfn{memory leak}. On the other hand, if a program calls
\cfunction{free()} for a block and then continues to use the block, it
creates a conflict with re-use of the block through another
\cfunction{malloc()} call. This is called \dfn{using freed memory}.
It has the same bad consequences as referencing uninitialized data ---
core dumps, wrong results, mysterious crashes.
Common causes of memory leaks are unusual paths through the code. For
instance, a function may allocate a block of memory, do some
@ -994,25 +1004,25 @@ function frequently. Therefore, it's important to prevent leaks from
happening by having a coding convention or strategy that minimizes
this kind of errors.
Since Python makes heavy use of \code{malloc()} and \code{free()}, it
needs a strategy to avoid memory leaks as well as the use of freed
memory. The chosen method is called \dfn{reference counting}. The
principle is simple: every object contains a counter, which is
incremented when a reference to the object is stored somewhere, and
which is decremented when a reference to it is deleted. When the
counter reaches zero, the last reference to the object has been
deleted and the object is freed.
Since Python makes heavy use of \cfunction{malloc()} and
\cfunction{free()}, it needs a strategy to avoid memory leaks as well
as the use of freed memory. The chosen method is called
\dfn{reference counting}. The principle is simple: every object
contains a counter, which is incremented when a reference to the
object is stored somewhere, and which is decremented when a reference
to it is deleted. When the counter reaches zero, the last reference
to the object has been deleted and the object is freed.
An alternative strategy is called \dfn{automatic garbage collection}.
(Sometimes, reference counting is also referred to as a garbage
collection strategy, hence my use of ``automatic'' to distinguish the
two.) The big advantage of automatic garbage collection is that the
user doesn't need to call \code{free()} explicitly. (Another claimed
user doesn't need to call \cfunction{free()} explicitly. (Another claimed
advantage is an improvement in speed or memory usage --- this is no
hard fact however.) The disadvantage is that for \C{}, there is no
truly portable automatic garbage collector, while reference counting
can be implemented portably (as long as the functions \code{malloc()}
and \code{free()} are available --- which the \C{} Standard guarantees).
can be implemented portably (as long as the functions \cfunction{malloc()}
and \cfunction{free()} are available --- which the \C{} Standard guarantees).
Maybe some day a sufficiently portable automatic garbage collector
will be available for \C{}. Until then, we'll have to live with
reference counts.
@ -1022,8 +1032,8 @@ reference counts.
There are two macros, \code{Py_INCREF(x)} and \code{Py_DECREF(x)},
which handle the incrementing and decrementing of the reference count.
\code{Py_DECREF()} also frees the object when the count reaches zero.
For flexibility, it doesn't call \code{free()} directly --- rather, it
\cfunction{Py_DECREF()} also frees the object when the count reaches zero.
For flexibility, it doesn't call \cfunction{free()} directly --- rather, it
makes a call through a function pointer in the object's \dfn{type
object}. For this purpose (and others), every object also contains a
pointer to its type object.
@ -1033,16 +1043,16 @@ The big question now remains: when to use \code{Py_INCREF(x)} and
``owns'' an object; however, you can \dfn{own a reference} to an
object. An object's reference count is now defined as the number of
owned references to it. The owner of a reference is responsible for
calling \code{Py_DECREF()} when the reference is no longer needed.
Ownership of a reference can be transferred. There are three ways to
dispose of an owned reference: pass it on, store it, or call
\code{Py_DECREF()}. Forgetting to dispose of an owned reference creates
a memory leak.
calling \cfunction{Py_DECREF()} when the reference is no longer
needed. Ownership of a reference can be transferred. There are three
ways to dispose of an owned reference: pass it on, store it, or call
\cfunction{Py_DECREF()}. Forgetting to dispose of an owned reference
creates a memory leak.
It is also possible to \dfn{borrow}\footnote{The metaphor of
``borrowing'' a reference is not completely correct: the owner still
has a copy of the reference.} a reference to an object. The borrower
of a reference should not call \code{Py_DECREF()}. The borrower must
of a reference should not call \cfunction{Py_DECREF()}. The borrower must
not hold on to the object longer than the owner from which it was
borrowed. Using a borrowed reference after the owner has disposed of
it risks using freed memory and should be avoided
@ -1060,7 +1070,7 @@ used after the owner from which it was borrowed has in fact disposed
of it.
A borrowed reference can be changed into an owned reference by calling
\code{Py_INCREF()}. This does not affect the status of the owner from
\cfunction{Py_INCREF()}. This does not affect the status of the owner from
which the reference was borrowed --- it creates a new owned reference,
and gives full owner responsibilities (i.e., the new owner must
dispose of the reference properly, as well as the previous owner).
@ -1074,41 +1084,42 @@ transferred with the reference or not.
Most functions that return a reference to an object pass on ownership
with the reference. In particular, all functions whose function it is
to create a new object, e.g.\ \code{PyInt_FromLong()} and
\code{Py_BuildValue()}, pass ownership to the receiver. Even if in
to create a new object, e.g.\ \cfunction{PyInt_FromLong()} and
\cfunction{Py_BuildValue()}, pass ownership to the receiver. Even if in
fact, in some cases, you don't receive a reference to a brand new
object, you still receive ownership of the reference. For instance,
\code{PyInt_FromLong()} maintains a cache of popular values and can
\cfunction{PyInt_FromLong()} maintains a cache of popular values and can
return a reference to a cached item.
Many functions that extract objects from other objects also transfer
ownership with the reference, for instance
\code{PyObject_GetAttrString()}. The picture is less clear, here,
\cfunction{PyObject_GetAttrString()}. The picture is less clear, here,
however, since a few common routines are exceptions:
\code{PyTuple_GetItem()}, \code{PyList_GetItem()} and
\code{PyDict_GetItem()} (and \code{PyDict_GetItemString()}) all return
references that you borrow from the tuple, list or dictionary.
\cfunction{PyTuple_GetItem()}, \cfunction{PyList_GetItem()},
\cfunction{PyDict_GetItem()}, and \cfunction{PyDict_GetItemString()}
all return references that you borrow from the tuple, list or
dictionary.
The function \code{PyImport_AddModule()} also returns a borrowed
The function \cfunction{PyImport_AddModule()} also returns a borrowed
reference, even though it may actually create the object it returns:
this is possible because an owned reference to the object is stored in
\code{sys.modules}.
When you pass an object reference into another function, in general,
the function borrows the reference from you --- if it needs to store
it, it will use \code{Py_INCREF()} to become an independent owner.
There are exactly two important exceptions to this rule:
\code{PyTuple_SetItem()} and \code{PyList_SetItem()}. These functions
take over ownership of the item passed to them --- even if they fail!
(Note that \code{PyDict_SetItem()} and friends don't take over
ownership --- they are ``normal''.)
it, it will use \cfunction{Py_INCREF()} to become an independent
owner. There are exactly two important exceptions to this rule:
\cfunction{PyTuple_SetItem()} and \cfunction{PyList_SetItem()}. These
functions take over ownership of the item passed to them --- even if
they fail! (Note that \cfunction{PyDict_SetItem()} and friends don't
take over ownership --- they are ``normal''.)
When a \C{} function is called from Python, it borrows references to its
arguments from the caller. The caller owns a reference to the object,
so the borrowed reference's lifetime is guaranteed until the function
returns. Only when such a borrowed reference must be stored or passed
on, it must be turned into an owned reference by calling
\code{Py_INCREF()}.
\cfunction{Py_INCREF()}.
The object reference returned from a \C{} function that is called from
Python must be an owned reference --- ownership is tranferred from the
@ -1123,8 +1134,8 @@ invocations of the interpreter, which can cause the owner of a
reference to dispose of it.
The first and most important case to know about is using
\code{Py_DECREF()} on an unrelated object while borrowing a reference
to a list item. For instance:
\cfunction{Py_DECREF()} on an unrelated object while borrowing a
reference to a list item. For instance:
\begin{verbatim}
bug(PyObject *list) {
@ -1138,20 +1149,20 @@ This function first borrows a reference to \code{list[0]}, then
replaces \code{list[1]} with the value \code{0}, and finally prints
the borrowed reference. Looks harmless, right? But it's not!
Let's follow the control flow into \code{PyList_SetItem()}. The list
Let's follow the control flow into \cfunction{PyList_SetItem()}. The list
owns references to all its items, so when item 1 is replaced, it has
to dispose of the original item 1. Now let's suppose the original
item 1 was an instance of a user-defined class, and let's further
suppose that the class defined a \code{__del__()} method. If this
suppose that the class defined a \method{__del__()} method. If this
class instance has a reference count of 1, disposing of it will call
its \code{__del__()} method.
its \method{__del__()} method.
Since it is written in Python, the \code{__del__()} method can execute
Since it is written in Python, the \method{__del__()} method can execute
arbitrary Python code. Could it perhaps do something to invalidate
the reference to \code{item} in \code{bug()}? You bet! Assuming that
the list passed into \code{bug()} is accessible to the
\code{__del__()} method, it could execute a statement to the effect of
\code{del list[0]}, and assuming this was the last reference to that
the reference to \code{item} in \cfunction{bug()}? You bet! Assuming
that the list passed into \cfunction{bug()} is accessible to the
\method{__del__()} method, it could execute a statement to the effect of
\samp{del list[0]}, and assuming this was the last reference to that
object, it would free the memory associated with it, thereby
invalidating \code{item}.
@ -1171,7 +1182,7 @@ no_bug(PyObject *list) {
This is a true story. An older version of Python contained variants
of this bug and someone spent a considerable amount of time in a \C{}
debugger to figure out why his \code{__del__()} methods would fail...
debugger to figure out why his \method{__del__()} methods would fail...
The second case of problems with a borrowed reference is a variant
involving threads. Normally, multiple threads in the Python
@ -1208,11 +1219,11 @@ there would be a lot of redundant tests and the code would run slower.
It is better to test for \NULL{} only at the ``source'', i.e.\
when a pointer that may be \NULL{} is received, e.g.\ from
\code{malloc()} or from a function that may raise an exception.
\cfunction{malloc()} or from a function that may raise an exception.
The macros \code{Py_INCREF()} and \code{Py_DECREF()}
The macros \cfunction{Py_INCREF()} and \cfunction{Py_DECREF()}
don't check for \NULL{} pointers --- however, their variants
\code{Py_XINCREF()} and \code{Py_XDECREF()} do.
\cfunction{Py_XINCREF()} and \cfunction{Py_XDECREF()} do.
The macros for checking for a particular object type
(\code{Py\var{type}_Check()}) don't check for \NULL{} pointers ---
@ -1259,16 +1270,17 @@ interpreter to run some Python code.
So if you are embedding Python, you are providing your own main
program. One of the things this main program has to do is initialize
the Python interpreter. At the very least, you have to call the
function \code{Py_Initialize()}. There are optional calls to pass command
line arguments to Python. Then later you can call the interpreter
from any part of the application.
function \cfunction{Py_Initialize()}. There are optional calls to
pass command line arguments to Python. Then later you can call the
interpreter from any part of the application.
There are several different ways to call the interpreter: you can pass
a string containing Python statements to \code{PyRun_SimpleString()},
or you can pass a stdio file pointer and a file name (for
identification in error messages only) to \code{PyRun_SimpleFile()}. You
can also call the lower-level operations described in the previous
chapters to construct and use Python objects.
a string containing Python statements to
\cfunction{PyRun_SimpleString()}, or you can pass a stdio file pointer
and a file name (for identification in error messages only) to
\cfunction{PyRun_SimpleFile()}. You can also call the lower-level
operations described in the previous chapters to construct and use
Python objects.
A simple demo of embedding Python can be found in the directory
\file{Demo/embed}.
@ -1336,9 +1348,9 @@ loading. (SGI IRIX 5 might also support it but it is inferior to
using shared libraries so there is no reason to; a small test didn't
work right away so I gave up trying to support it.)
Before you build Python, you first need to fetch and build the \code{dl}
package written by Jack Jansen. This is available by anonymous ftp
from \url{ftp://ftp.cwi.nl/pub/dynload}, file
Before you build Python, you first need to fetch and build the
\code{dl} package written by Jack Jansen. This is available by
anonymous ftp from \url{ftp://ftp.cwi.nl/pub/dynload}, file
\file{dl-1.6.tar.Z}. (The version number may change.) Follow the
instructions in the package's \file{README} file to build it.
@ -1387,7 +1399,7 @@ will support GNU dynamic loading.
Since there are three styles of dynamic loading, there are also three
groups of instructions for building a dynamically loadable module.
Instructions common for all three styles are given first. Assuming
your module is called \code{spam}, the source filename must be
your module is called \module{spam}, the source filename must be
\file{spammodule.c}, so the object name is \file{spammodule.o}. The
module must be written as a normal Python extension module (as
described earlier).
@ -1425,12 +1437,12 @@ On SGI IRIX 5, use
ld -shared spammodule.o -o spammodule.so
\end{verbatim}
On other systems, consult the manual page for \code{ld}(1) to find what
flags, if any, must be used.
On other systems, consult the manual page for \manpage{ld}{1} to find
what flags, if any, must be used.
If your extension module uses system libraries that haven't already
been linked with Python (e.g. a windowing system), these must be
passed to the \code{ld} command as \samp{-l} options after the
passed to the \program{ld} command as \samp{-l} options after the
\samp{.o} file.
The resulting file \file{spammodule.so} must be copied into a directory

462
Doc/ext/ext.tex
View File

@ -74,9 +74,9 @@ well as on your system setup; details are given in a later section.
Let's create an extension module called \samp{spam} (the favorite food
of Monty Python fans...) and let's say we want to create a Python
interface to the \C{} library function \code{system()}.\footnote{An
interface to the \C{} library function \cfunction{system()}.\footnote{An
interface for this function already exists in the standard module
\code{os} --- it was chosen as a simple and straightfoward example.}
\module{os} --- it was chosen as a simple and straightfoward example.}
This function takes a null-terminated character string as argument and
returns an integer. We want this function to be callable from Python
as follows:
@ -106,8 +106,8 @@ For convenience, and since they are used extensively by the Python
interpreter, \code{"Python.h"} includes a few standard header files:
\code{<stdio.h>}, \code{<string.h>}, \code{<errno.h>}, and
\code{<stdlib.h>}. If the latter header file does not exist on your
system, it declares the functions \code{malloc()}, \code{free()} and
\code{realloc()} directly.
system, it declares the functions \cfunction{malloc()},
\cfunction{free()} and \cfunction{realloc()} directly.
The next thing we add to our module file is the \C{} function that will
be called when the Python expression \samp{spam.system(\var{string})}
@ -166,42 +166,43 @@ and return an error value (usually a \NULL{} pointer). Exceptions
are stored in a static global variable inside the interpreter; if this
variable is \NULL{} no exception has occurred. A second global
variable stores the ``associated value'' of the exception (the second
argument to \code{raise}). A third variable contains the stack
argument to \keyword{raise}). A third variable contains the stack
traceback in case the error originated in Python code. These three
variables are the \C{} equivalents of the Python variables
\code{sys.exc_type}, \code{sys.exc_value} and \code{sys.exc_traceback}
(see the section on module \code{sys} in the Library Reference
Manual). It is important to know about them to understand how errors
are passed around.
(see the section on module \module{sys} in the \emph{Python Library
Reference}). It is important to know about them to understand how
errors are passed around.
The Python API defines a number of functions to set various types of
exceptions.
The most common one is \code{PyErr_SetString()}. Its arguments are an
exception object and a \C{} string. The exception object is usually a
predefined object like \code{PyExc_ZeroDivisionError}. The \C{} string
indicates the cause of the error and is converted to a Python string
object and stored as the ``associated value'' of the exception.
The most common one is \cfunction{PyErr_SetString()}. Its arguments
are an exception object and a \C{} string. The exception object is
usually a predefined object like \cdata{PyExc_ZeroDivisionError}. The
\C{} string indicates the cause of the error and is converted to a
Python string object and stored as the ``associated value'' of the
exception.
Another useful function is \code{PyErr_SetFromErrno()}, which only
Another useful function is \cfunction{PyErr_SetFromErrno()}, which only
takes an exception argument and constructs the associated value by
inspection of the (\UNIX{}) global variable \code{errno}. The most
general function is \code{PyErr_SetObject()}, which takes two object
inspection of the (\UNIX{}) global variable \cdata{errno}. The most
general function is \cfunction{PyErr_SetObject()}, which takes two object
arguments, the exception and its associated value. You don't need to
\code{Py_INCREF()} the objects passed to any of these functions.
\cfunction{Py_INCREF()} the objects passed to any of these functions.
You can test non-destructively whether an exception has been set with
\code{PyErr_Occurred()}. This returns the current exception object,
\cfunction{PyErr_Occurred()}. This returns the current exception object,
or \NULL{} if no exception has occurred. You normally don't need
to call \code{PyErr_Occurred()} to see whether an error occurred in a
to call \cfunction{PyErr_Occurred()} to see whether an error occurred in a
function call, since you should be able to tell from the return value.
When a function \var{f} that calls another function \var{g} detects
that the latter fails, \var{f} should itself return an error value
(e.g. \NULL{} or \code{-1}). It should \emph{not} call one of the
\code{PyErr_*()} functions --- one has already been called by \var{g}.
\cfunction{PyErr_*()} functions --- one has already been called by \var{g}.
\var{f}'s caller is then supposed to also return an error indication
to \emph{its} caller, again \emph{without} calling \code{PyErr_*()},
to \emph{its} caller, again \emph{without} calling \cfunction{PyErr_*()},
and so on --- the most detailed cause of the error was already
reported by the function that first detected it. Once the error
reaches the Python interpreter's main loop, this aborts the currently
@ -209,44 +210,44 @@ executing Python code and tries to find an exception handler specified
by the Python programmer.
(There are situations where a module can actually give a more detailed
error message by calling another \code{PyErr_*()} function, and in
error message by calling another \cfunction{PyErr_*()} function, and in
such cases it is fine to do so. As a general rule, however, this is
not necessary, and can cause information about the cause of the error
to be lost: most operations can fail for a variety of reasons.)
To ignore an exception set by a function call that failed, the exception
condition must be cleared explicitly by calling \code{PyErr_Clear()}.
The only time \C{} code should call \code{PyErr_Clear()} is if it doesn't
condition must be cleared explicitly by calling \cfunction{PyErr_Clear()}.
The only time \C{} code should call \cfunction{PyErr_Clear()} is if it doesn't
want to pass the error on to the interpreter but wants to handle it
completely by itself (e.g. by trying something else or pretending
nothing happened).
Note that a failing \code{malloc()} call must be turned into an
exception --- the direct caller of \code{malloc()} (or
\code{realloc()}) must call \code{PyErr_NoMemory()} and return a
failure indicator itself. All the object-creating functions
(\code{PyInt_FromLong()} etc.) already do this, so only if you call
\code{malloc()} directly this note is of importance.
Note that a failing \cfunction{malloc()} call must be turned into an
exception --- the direct caller of \cfunction{malloc()} (or
\cfunction{realloc()}) must call \cfunction{PyErr_NoMemory()} and
return a failure indicator itself. All the object-creating functions
(\cfunction{PyInt_FromLong()} etc.) already do this, so only if you
call \cfunction{malloc()} directly this note is of importance.
Also note that, with the important exception of
\cfunction{PyArg_ParseTuple()} and friends, functions that return an
integer status usually return a positive value or zero for success and
\code{-1} for failure, like \UNIX{} system calls.
Finally, be careful to clean up garbage (by making \code{Py_XDECREF()}
or \code{Py_DECREF()} calls for objects you have already created) when
you return an error indicator!
Finally, be careful to clean up garbage (by making
\cfunction{Py_XDECREF()} or \cfunction{Py_DECREF()} calls for objects
you have already created) when you return an error indicator!
The choice of which exception to raise is entirely yours. There are
predeclared \C{} objects corresponding to all built-in Python exceptions,
e.g. \code{PyExc_ZeroDevisionError} which you can use directly. Of
e.g. \cdata{PyExc_ZeroDevisionError} which you can use directly. Of
course, you should choose exceptions wisely --- don't use
\code{PyExc_TypeError} to mean that a file couldn't be opened (that
should probably be \code{PyExc_IOError}). If something's wrong with
\cdata{PyExc_TypeError} to mean that a file couldn't be opened (that
should probably be \cdata{PyExc_IOError}). If something's wrong with
the argument list, the \cfunction{PyArg_ParseTuple()} function usually
raises \code{PyExc_TypeError}. If you have an argument whose value
raises \cdata{PyExc_TypeError}. If you have an argument whose value
which must be in a particular range or must satisfy other conditions,
\code{PyExc_ValueError} is appropriate.
\cdata{PyExc_ValueError} is appropriate.
You can also define a new exception that is unique to your module.
For this, you usually declare a static object variable at the
@ -257,8 +258,8 @@ static PyObject *SpamError;
\end{verbatim}
and initialize it in your module's initialization function
(\code{initspam()}) with a string object, e.g. (leaving out the error
checking for now):
(\cfunction{initspam()}) with an exception object, e.g. (leaving out
the error checking for now):
\begin{verbatim}
void
@ -267,16 +268,19 @@ initspam()
PyObject *m, *d;
m = Py_InitModule("spam", SpamMethods);
d = PyModule_GetDict(m);
SpamError = PyString_FromString("spam.error");
SpamError = PyErr_NewException("spam.error", NULL, NULL);
PyDict_SetItemString(d, "error", SpamError);
}
\end{verbatim}
Note that the Python name for the exception object is
\code{spam.error}. It is conventional for module and exception names
to be spelled in lower case. It is also conventional that the
\emph{value} of the exception object is the same as its name, e.g.\
the string \code{"spam.error"}.
\exception{spam.error}. The \cfunction{PyErr_NewException()} function
may create either a string or class, depending on whether the
\samp{-X} flag was passed to the interpreter. If \samp{-X} was used,
\cdata{SpamError} will be a string object, otherwise it will be a
class object with the base class being \exception{Exception},
described in the \emph{Python Library Reference} under ``Built-in
Exceptions.''
\section{Back to the Example}
@ -294,24 +298,25 @@ It returns \NULL{} (the error indicator for functions returning
object pointers) if an error is detected in the argument list, relying
on the exception set by \cfunction{PyArg_ParseTuple()}. Otherwise the
string value of the argument has been copied to the local variable
\code{command}. This is a pointer assignment and you are not supposed
\cdata{command}. This is a pointer assignment and you are not supposed
to modify the string to which it points (so in Standard \C{}, the variable
\code{command} should properly be declared as \samp{const char
\cdata{command} should properly be declared as \samp{const char
*command}).
The next statement is a call to the \UNIX{} function \code{system()},
passing it the string we just got from \cfunction{PyArg_ParseTuple()}:
The next statement is a call to the \UNIX{} function
\cfunction{system()}, passing it the string we just got from
\cfunction{PyArg_ParseTuple()}:
\begin{verbatim}
sts = system(command);
\end{verbatim}
Our \code{spam.system()} function must return the value of \code{sts}
as a Python object. This is done using the function
\code{Py_BuildValue()}, which is something like the inverse of
\cfunction{PyArg_ParseTuple()}: it takes a format string and an arbitrary
number of \C{} values, and returns a new Python object. More info on
\code{Py_BuildValue()} is given later.
Our \function{spam.system()} function must return the value of
\cdata{sts} as a Python object. This is done using the function
\cfunction{Py_BuildValue()}, which is something like the inverse of
\cfunction{PyArg_ParseTuple()}: it takes a format string and an
arbitrary number of \C{} values, and returns a new Python object.
More info on \cfunction{Py_BuildValue()} is given later.
\begin{verbatim}
return Py_BuildValue("i", sts);
@ -321,7 +326,7 @@ In this case, it will return an integer object. (Yes, even integers
are objects on the heap in Python!)
If you have a \C{} function that returns no useful argument (a function
returning \code{void}), the corresponding Python function must return
returning \ctype{void}), the corresponding Python function must return
\code{None}. You need this idiom to do so:
\begin{verbatim}
@ -329,7 +334,7 @@ returning \code{void}), the corresponding Python function must return
return Py_None;
\end{verbatim}
\code{Py_None} is the \C{} name for the special Python object
\cdata{Py_None} is the \C{} name for the special Python object
\code{None}. It is a genuine Python object (not a \NULL{}
pointer, which means ``error'' in most contexts, as we have seen).
@ -337,7 +342,7 @@ pointer, which means ``error'' in most contexts, as we have seen).
\section{The Module's Method Table and Initialization Function}
\label{methodTable}
I promised to show how \code{spam_system()} is called from Python
I promised to show how \cfunction{spam_system()} is called from Python
programs. First, we need to list its name and address in a ``method
table'':
@ -361,7 +366,7 @@ the Python-level parameters to be passed in as a tuple acceptable for
parsing via \cfunction{PyArg_ParseTuple()}; more information on this
function is provided below.
The \code{METH_KEYWORDS} bit may be set in the third field if keyword
The \constant{METH_KEYWORDS} bit may be set in the third field if keyword
arguments should be passed to the function. In this case, the \C{}
function should accept a third \samp{PyObject *} parameter which will
be a dictionary of keywords. Use \cfunction{PyArg_ParseTupleAndKeywords()}
@ -379,16 +384,17 @@ initspam()
}
\end{verbatim}
When the Python program imports module \code{spam} for the first time,
\code{initspam()} is called. It calls \code{Py_InitModule()}, which
creates a ``module object'' (which is inserted in the dictionary
\code{sys.modules} under the key \code{"spam"}), and inserts built-in
function objects into the newly created module based upon the table
(an array of \code{PyMethodDef} structures) that was passed as its
second argument. \code{Py_InitModule()} returns a pointer to the
module object that it creates (which is unused here). It aborts with
a fatal error if the module could not be initialized satisfactorily,
so the caller doesn't need to check for errors.
When the Python program imports module \module{spam} for the first
time, \cfunction{initspam()} is called. It calls
\cfunction{Py_InitModule()}, which creates a ``module object'' (which
is inserted in the dictionary \code{sys.modules} under the key
\code{"spam"}), and inserts built-in function objects into the newly
created module based upon the table (an array of \ctype{PyMethodDef}
structures) that was passed as its second argument.
\cfunction{Py_InitModule()} returns a pointer to the module object
that it creates (which is unused here). It aborts with a fatal error
if the module could not be initialized satisfactorily, so the caller
doesn't need to check for errors.
\section{Compilation and Linkage}
@ -411,11 +417,11 @@ the \file{Modules} directory, add a line to the file
spam spammodule.o
\end{verbatim}
and rebuild the interpreter by running \code{make} in the toplevel
directory. You can also run \code{make} in the \file{Modules}
and rebuild the interpreter by running \program{make} in the toplevel
directory. You can also run \program{make} in the \file{Modules}
subdirectory, but then you must first rebuilt the \file{Makefile}
there by running \code{make Makefile}. (This is necessary each time
you change the \file{Setup} file.)
there by running `\program{make} Makefile'. (This is necessary each
time you change the \file{Setup} file.)
If your module requires additional libraries to link with, these can
be listed on the line in the \file{Setup} file as well, for instance:
@ -445,8 +451,8 @@ Calling a Python function is easy. First, the Python program must
somehow pass you the Python function object. You should provide a
function (or some other interface) to do this. When this function is
called, save a pointer to the Python function object (be careful to
\code{Py_INCREF()} it!) in a global variable --- or whereever you see fit.
For example, the following function might be part of a module
\cfunction{Py_INCREF()} it!) in a global variable --- or whereever you
see fit. For example, the following function might be part of a module
definition:
\begin{verbatim}
@ -465,18 +471,18 @@ my_set_callback(dummy, arg)
}
\end{verbatim}
The macros \code{Py_XINCREF()} and \code{Py_XDECREF()} increment/decrement
the reference count of an object and are safe in the presence of
\NULL{} pointers. More info on them in the section on Reference
Counts below.
The macros \cfunction{Py_XINCREF()} and \cfunction{Py_XDECREF()}
increment/decrement the reference count of an object and are safe in
the presence of \NULL{} pointers. More info on them in the section on
Reference Counts below.
Later, when it is time to call the function, you call the \C{} function
\code{PyEval_CallObject()}. This function has two arguments, both
\cfunction{PyEval_CallObject()}. This function has two arguments, both
pointers to arbitrary Python objects: the Python function, and the
argument list. The argument list must always be a tuple object, whose
length is the number of arguments. To call the Python function with
no arguments, pass an empty tuple; to call it with one argument, pass
a singleton tuple. \code{Py_BuildValue()} returns a tuple when its
a singleton tuple. \cfunction{Py_BuildValue()} returns a tuple when its
format string consists of zero or more format codes between
parentheses. For example:
@ -493,26 +499,26 @@ parentheses. For example:
Py_DECREF(arglist);
\end{verbatim}
\code{PyEval_CallObject()} returns a Python object pointer: this is
the return value of the Python function. \code{PyEval_CallObject()} is
\cfunction{PyEval_CallObject()} returns a Python object pointer: this is
the return value of the Python function. \cfunction{PyEval_CallObject()} is
``reference-count-neutral'' with respect to its arguments. In the
example a new tuple was created to serve as the argument list, which
is \code{Py_DECREF()}-ed immediately after the call.
is \cfunction{Py_DECREF()}-ed immediately after the call.
The return value of \code{PyEval_CallObject()} is ``new'': either it
The return value of \cfunction{PyEval_CallObject()} is ``new'': either it
is a brand new object, or it is an existing object whose reference
count has been incremented. So, unless you want to save it in a
global variable, you should somehow \code{Py_DECREF()} the result,
global variable, you should somehow \cfunction{Py_DECREF()} the result,
even (especially!) if you are not interested in its value.
Before you do this, however, it is important to check that the return
value isn't \NULL{}. If it is, the Python function terminated by raising
an exception. If the \C{} code that called \code{PyEval_CallObject()} is
called from Python, it should now return an error indication to its
Python caller, so the interpreter can print a stack trace, or the
calling Python code can handle the exception. If this is not possible
or desirable, the exception should be cleared by calling
\code{PyErr_Clear()}. For example:
value isn't \NULL{}. If it is, the Python function terminated by
raising an exception. If the \C{} code that called
\cfunction{PyEval_CallObject()} is called from Python, it should now
return an error indication to its Python caller, so the interpreter
can print a stack trace, or the calling Python code can handle the
exception. If this is not possible or desirable, the exception should
be cleared by calling \cfunction{PyErr_Clear()}. For example:
\begin{verbatim}
if (result == NULL)
@ -522,14 +528,15 @@ or desirable, the exception should be cleared by calling
\end{verbatim}
Depending on the desired interface to the Python callback function,
you may also have to provide an argument list to \code{PyEval_CallObject()}.
In some cases the argument list is also provided by the Python
program, through the same interface that specified the callback
function. It can then be saved and used in the same manner as the
function object. In other cases, you may have to construct a new
tuple to pass as the argument list. The simplest way to do this is to
call \code{Py_BuildValue()}. For example, if you want to pass an integral
event code, you might use the following code:
you may also have to provide an argument list to
\cfunction{PyEval_CallObject()}. In some cases the argument list is
also provided by the Python program, through the same interface that
specified the callback function. It can then be saved and used in the
same manner as the function object. In other cases, you may have to
construct a new tuple to pass as the argument list. The simplest way
to do this is to call \cfunction{Py_BuildValue()}. For example, if
you want to pass an integral event code, you might use the following
code:
\begin{verbatim}
PyObject *arglist;
@ -543,10 +550,10 @@ event code, you might use the following code:
Py_DECREF(result);
\end{verbatim}
Note the placement of \code{Py_DECREF(argument)} immediately after the call,
before the error check! Also note that strictly spoken this code is
not complete: \code{Py_BuildValue()} may run out of memory, and this should
be checked.
Note the placement of \samp{Py_DECREF(arglist)} immediately after the
call, before the error check! Also note that strictly spoken this
code is not complete: \cfunction{Py_BuildValue()} may run out of
memory, and this should be checked.
\section{Format Strings for \sectcode{PyArg_ParseTuple()}}
@ -594,7 +601,7 @@ must not contain embedded null bytes; if it does, a \exception{TypeError}
exception is raised.
\item[\samp{s\#} (string) {[char *, int]}]
This variant on \code{'s'} stores into two \C{} variables, the first one
This variant on \samp{s} stores into two \C{} variables, the first one
a pointer to a character string, the second one its length. In this
case the Python string may contain embedded null bytes.
@ -603,32 +610,32 @@ Like \samp{s}, but the Python object may also be \code{None}, in which
case the \C{} pointer is set to \NULL{}.
\item[\samp{z\#} (string or \code{None}) {[char *, int]}]
This is to \code{'s\#'} as \code{'z'} is to \code{'s'}.
This is to \samp{s\#} as \samp{z} is to \samp{s}.
\item[\samp{b} (integer) {[char]}]
Convert a Python integer to a tiny int, stored in a \C{} \code{char}.
Convert a Python integer to a tiny int, stored in a \C{} \ctype{char}.
\item[\samp{h} (integer) {[short int]}]
Convert a Python integer to a \C{} \code{short int}.
Convert a Python integer to a \C{} \ctype{short int}.
\item[\samp{i} (integer) {[int]}]
Convert a Python integer to a plain \C{} \code{int}.
Convert a Python integer to a plain \C{} \ctype{int}.
\item[\samp{l} (integer) {[long int]}]
Convert a Python integer to a \C{} \code{long int}.
Convert a Python integer to a \C{} \ctype{long int}.
\item[\samp{c} (string of length 1) {[char]}]
Convert a Python character, represented as a string of length 1, to a
\C{} \code{char}.
\C{} \ctype{char}.
\item[\samp{f} (float) {[float]}]
Convert a Python floating point number to a \C{} \code{float}.
Convert a Python floating point number to a \C{} \ctype{float}.
\item[\samp{d} (float) {[double]}]
Convert a Python floating point number to a \C{} \code{double}.
Convert a Python floating point number to a \C{} \ctype{double}.
\item[\samp{D} (complex) {[Py_complex]}]
Convert a Python complex number to a \C{} \code{Py_complex} structure.
Convert a Python complex number to a \C{} \ctype{Py_complex} structure.
\item[\samp{O} (object) {[PyObject *]}]
Store a Python object (without any conversion) in a \C{} object pointer.
@ -636,36 +643,36 @@ The \C{} program thus receives the actual object that was passed. The
object's reference count is not increased. The pointer stored is not
\NULL{}.
\item[\samp{O!} (object) {[\var{typeobject}, PyObject *]}]
\item[\samp{O!} (object) {[\var{typeobject}, PyObject *{]}}]
Store a Python object in a \C{} object pointer. This is similar to
\samp{O}, but takes two \C{} arguments: the first is the address of a
Python type object, the second is the address of the \C{} variable (of
type \code{PyObject *}) into which the object pointer is stored.
type \ctype{PyObject *}) into which the object pointer is stored.
If the Python object does not have the required type, a
\code{TypeError} exception is raised.
\exception{TypeError} exception is raised.
\item[\samp{O\&} (object) {[\var{converter}, \var{anything}]}]
\item[\samp{O\&} (object) {[\var{converter}, \var{anything}{]}}]
Convert a Python object to a \C{} variable through a \var{converter}
function. This takes two arguments: the first is a function, the
second is the address of a \C{} variable (of arbitrary type), converted
to \code{void *}. The \var{converter} function in turn is called as
to \ctype{void *}. The \var{converter} function in turn is called as
follows:
\code{\var{status} = \var{converter}(\var{object}, \var{address});}
where \var{object} is the Python object to be converted and
\var{address} is the \code{void *} argument that was passed to
\code{PyArg_ConvertTuple()}. The returned \var{status} should be
\var{address} is the \ctype{void *} argument that was passed to
\cfunction{PyArg_ConvertTuple()}. The returned \var{status} should be
\code{1} for a successful conversion and \code{0} if the conversion
has failed. When the conversion fails, the \var{converter} function
should raise an exception.
\item[\samp{S} (string) {[PyStringObject *]}]
Like \samp{O} but requires that the Python object is a string object.
Raises a \code{TypeError} exception if the object is not a string
object. The \C{} variable may also be declared as \code{PyObject *}.
Raises a \exception{TypeError} exception if the object is not a string
object. The \C{} variable may also be declared as \ctype{PyObject *}.
\item[\samp{(\var{items})} (tuple) {[\var{matching-items}]}]
\item[\samp{(\var{items})} (tuple) {[\var{matching-items}{]}}]
The object must be a Python tuple whose length is the number of format
units in \var{items}. The \C{} arguments must correspond to the
individual format units in \var{items}. Format units for tuples may
@ -688,13 +695,13 @@ not occur inside nested parentheses. They are:
Indicates that the remaining arguments in the Python argument list are
optional. The \C{} variables corresponding to optional arguments should
be initialized to their default value --- when an optional argument is
not specified, the \code{PyArg_ParseTuple} does not touch the contents
not specified, \cfuntion{PyArg_ParseTuple()} does not touch the contents
of the corresponding \C{} variable(s).
\item[\samp{:}]
The list of format units ends here; the string after the colon is used
as the function name in error messages (the ``associated value'' of
the exceptions that \code{PyArg_ParseTuple} raises).
the exceptions that \cfunction{PyArg_ParseTuple()} raises).
\item[\samp{;}]
The list of format units ends here; the string after the colon is used
@ -828,7 +835,7 @@ initkeywdarg()
\section{The \sectcode{Py_BuildValue()} Function}
\label{buildValue}
This function is the counterpart to \code{PyArg_ParseTuple()}. It is
This function is the counterpart to \cfunction{PyArg_ParseTuple()}. It is
declared as follows:
\begin{verbatim}
@ -836,19 +843,20 @@ PyObject *Py_BuildValue(char *format, ...);
\end{verbatim}
It recognizes a set of format units similar to the ones recognized by
\code{PyArg_ParseTuple()}, but the arguments (which are input to the
\cfunction{PyArg_ParseTuple()}, but the arguments (which are input to the
function, not output) must not be pointers, just values. It returns a
new Python object, suitable for returning from a \C{} function called
from Python.
One difference with \code{PyArg_ParseTuple()}: while the latter
One difference with \cfunction{PyArg_ParseTuple()}: while the latter
requires its first argument to be a tuple (since Python argument lists
are always represented as tuples internally), \code{BuildValue()} does
not always build a tuple. It builds a tuple only if its format string
contains two or more format units. If the format string is empty, it
returns \code{None}; if it contains exactly one format unit, it
returns whatever object is described by that format unit. To force it
to return a tuple of size 0 or one, parenthesize the format string.
are always represented as tuples internally),
\cfunction{Py_BuildValue()} does not always build a tuple. It builds
a tuple only if its format string contains two or more format units.
If the format string is empty, it returns \code{None}; if it contains
exactly one format unit, it returns whatever object is described by
that format unit. To force it to return a tuple of size 0 or one,
parenthesize the format string.
In the following description, the quoted form is the format unit; the
entry in (round) parentheses is the Python object type that the format
@ -877,7 +885,7 @@ Same as \samp{s}.
Same as \samp{s\#}.
\item[\samp{i} (integer) {[int]}]
Convert a plain \C{} \code{int} to a Python integer object.
Convert a plain \C{} \ctype{int} to a Python integer object.
\item[\samp{b} (integer) {[char]}]
Same as \samp{i}.
@ -886,14 +894,14 @@ Same as \samp{i}.
Same as \samp{i}.
\item[\samp{l} (integer) {[long int]}]
Convert a \C{} \code{long int} to a Python integer object.
Convert a \C{} \ctype{long int} to a Python integer object.
\item[\samp{c} (string of length 1) {[char]}]
Convert a \C{} \code{int} representing a character to a Python string of
Convert a \C{} \ctype{int} representing a character to a Python string of
length 1.
\item[\samp{d} (float) {[double]}]
Convert a \C{} \code{double} to a Python floating point number.
Convert a \C{} \ctype{double} to a Python floating point number.
\item[\samp{f} (float) {[float]}]
Same as \samp{d}.
@ -903,9 +911,9 @@ Pass a Python object untouched (except for its reference count, which
is incremented by one). If the object passed in is a \NULL{}
pointer, it is assumed that this was caused because the call producing
the argument found an error and set an exception. Therefore,
\code{Py_BuildValue()} will return \NULL{} but won't raise an
\cfunction{Py_BuildValue()} will return \NULL{} but won't raise an
exception. If no exception has been raised yet,
\code{PyExc_SystemError} is set.
\cdata{PyExc_SystemError} is set.
\item[\samp{S} (object) {[PyObject *]}]
Same as \samp{O}.
@ -913,7 +921,7 @@ Same as \samp{O}.
\item[\samp{O\&} (object) {[\var{converter}, \var{anything}]}]
Convert \var{anything} to a Python object through a \var{converter}
function. The function is called with \var{anything} (which should be
compatible with \code{void *}) as its argument and should return a
compatible with \ctype{void *}) as its argument and should return a
``new'' Python object, or \NULL{} if an error occurred.
\item[\samp{(\var{items})} (tuple) {[\var{matching-items}]}]
@ -932,7 +940,7 @@ and value, respectively.
\end{description}
If there is an error in the format string, the
\code{PyExc_SystemError} exception is raised and \NULL{} returned.
\cdata{PyExc_SystemError} exception is raised and \NULL{} returned.
Examples (to the left the call, to the right the resulting Python value):
@ -960,24 +968,26 @@ Examples (to the left the call, to the right the resulting Python value):
%\subsection{Introduction}
In languages like \C{} or \Cpp{}, the programmer is responsible for
dynamic allocation and deallocation of memory on the heap. In \C{}, this
is done using the functions \code{malloc()} and \code{free()}. In
\Cpp{}, the operators \code{new} and \code{delete} are used with
essentially the same meaning; they are actually implemented using
\code{malloc()} and \code{free()}, so we'll restrict the following
discussion to the latter.
dynamic allocation and deallocation of memory on the heap. In \C{},
this is done using the functions \cfunction{malloc()} and
\cfunction{free()}. In \Cpp{}, the operators \keyword{new} and
\keyword{delete} are used with essentially the same meaning; they are
actually implemented using \cfunction{malloc()} and
\cfunction{free()}, so we'll restrict the following discussion to the
latter.
Every block of memory allocated with \code{malloc()} should eventually
be returned to the pool of available memory by exactly one call to
\code{free()}. It is important to call \code{free()} at the right
time. If a block's address is forgotten but \code{free()} is not
called for it, the memory it occupies cannot be reused until the
program terminates. This is called a \dfn{memory leak}. On the other
hand, if a program calls \code{free()} for a block and then continues
to use the block, it creates a conflict with re-use of the block
through another \code{malloc()} call. This is called \dfn{using freed
memory}. It has the same bad consequences as referencing uninitialized
data --- core dumps, wrong results, mysterious crashes.
Every block of memory allocated with \cfunction{malloc()} should
eventually be returned to the pool of available memory by exactly one
call to \cfunction{free()}. It is important to call
\cfunction{free()} at the right time. If a block's address is
forgotten but \cfunction{free()} is not called for it, the memory it
occupies cannot be reused until the program terminates. This is
called a \dfn{memory leak}. On the other hand, if a program calls
\cfunction{free()} for a block and then continues to use the block, it
creates a conflict with re-use of the block through another
\cfunction{malloc()} call. This is called \dfn{using freed memory}.
It has the same bad consequences as referencing uninitialized data ---
core dumps, wrong results, mysterious crashes.
Common causes of memory leaks are unusual paths through the code. For
instance, a function may allocate a block of memory, do some
@ -994,25 +1004,25 @@ function frequently. Therefore, it's important to prevent leaks from
happening by having a coding convention or strategy that minimizes
this kind of errors.
Since Python makes heavy use of \code{malloc()} and \code{free()}, it
needs a strategy to avoid memory leaks as well as the use of freed
memory. The chosen method is called \dfn{reference counting}. The
principle is simple: every object contains a counter, which is
incremented when a reference to the object is stored somewhere, and
which is decremented when a reference to it is deleted. When the
counter reaches zero, the last reference to the object has been
deleted and the object is freed.
Since Python makes heavy use of \cfunction{malloc()} and
\cfunction{free()}, it needs a strategy to avoid memory leaks as well
as the use of freed memory. The chosen method is called
\dfn{reference counting}. The principle is simple: every object
contains a counter, which is incremented when a reference to the
object is stored somewhere, and which is decremented when a reference
to it is deleted. When the counter reaches zero, the last reference
to the object has been deleted and the object is freed.
An alternative strategy is called \dfn{automatic garbage collection}.
(Sometimes, reference counting is also referred to as a garbage
collection strategy, hence my use of ``automatic'' to distinguish the
two.) The big advantage of automatic garbage collection is that the
user doesn't need to call \code{free()} explicitly. (Another claimed
user doesn't need to call \cfunction{free()} explicitly. (Another claimed
advantage is an improvement in speed or memory usage --- this is no
hard fact however.) The disadvantage is that for \C{}, there is no
truly portable automatic garbage collector, while reference counting
can be implemented portably (as long as the functions \code{malloc()}
and \code{free()} are available --- which the \C{} Standard guarantees).
can be implemented portably (as long as the functions \cfunction{malloc()}
and \cfunction{free()} are available --- which the \C{} Standard guarantees).
Maybe some day a sufficiently portable automatic garbage collector
will be available for \C{}. Until then, we'll have to live with
reference counts.
@ -1022,8 +1032,8 @@ reference counts.
There are two macros, \code{Py_INCREF(x)} and \code{Py_DECREF(x)},
which handle the incrementing and decrementing of the reference count.
\code{Py_DECREF()} also frees the object when the count reaches zero.
For flexibility, it doesn't call \code{free()} directly --- rather, it
\cfunction{Py_DECREF()} also frees the object when the count reaches zero.
For flexibility, it doesn't call \cfunction{free()} directly --- rather, it
makes a call through a function pointer in the object's \dfn{type
object}. For this purpose (and others), every object also contains a
pointer to its type object.
@ -1033,16 +1043,16 @@ The big question now remains: when to use \code{Py_INCREF(x)} and
``owns'' an object; however, you can \dfn{own a reference} to an
object. An object's reference count is now defined as the number of
owned references to it. The owner of a reference is responsible for
calling \code{Py_DECREF()} when the reference is no longer needed.
Ownership of a reference can be transferred. There are three ways to
dispose of an owned reference: pass it on, store it, or call
\code{Py_DECREF()}. Forgetting to dispose of an owned reference creates
a memory leak.
calling \cfunction{Py_DECREF()} when the reference is no longer
needed. Ownership of a reference can be transferred. There are three
ways to dispose of an owned reference: pass it on, store it, or call
\cfunction{Py_DECREF()}. Forgetting to dispose of an owned reference
creates a memory leak.
It is also possible to \dfn{borrow}\footnote{The metaphor of
``borrowing'' a reference is not completely correct: the owner still
has a copy of the reference.} a reference to an object. The borrower
of a reference should not call \code{Py_DECREF()}. The borrower must
of a reference should not call \cfunction{Py_DECREF()}. The borrower must
not hold on to the object longer than the owner from which it was
borrowed. Using a borrowed reference after the owner has disposed of
it risks using freed memory and should be avoided
@ -1060,7 +1070,7 @@ used after the owner from which it was borrowed has in fact disposed
of it.
A borrowed reference can be changed into an owned reference by calling
\code{Py_INCREF()}. This does not affect the status of the owner from
\cfunction{Py_INCREF()}. This does not affect the status of the owner from
which the reference was borrowed --- it creates a new owned reference,
and gives full owner responsibilities (i.e., the new owner must
dispose of the reference properly, as well as the previous owner).
@ -1074,41 +1084,42 @@ transferred with the reference or not.
Most functions that return a reference to an object pass on ownership
with the reference. In particular, all functions whose function it is
to create a new object, e.g.\ \code{PyInt_FromLong()} and
\code{Py_BuildValue()}, pass ownership to the receiver. Even if in
to create a new object, e.g.\ \cfunction{PyInt_FromLong()} and
\cfunction{Py_BuildValue()}, pass ownership to the receiver. Even if in
fact, in some cases, you don't receive a reference to a brand new
object, you still receive ownership of the reference. For instance,
\code{PyInt_FromLong()} maintains a cache of popular values and can
\cfunction{PyInt_FromLong()} maintains a cache of popular values and can
return a reference to a cached item.
Many functions that extract objects from other objects also transfer
ownership with the reference, for instance
\code{PyObject_GetAttrString()}. The picture is less clear, here,
\cfunction{PyObject_GetAttrString()}. The picture is less clear, here,
however, since a few common routines are exceptions:
\code{PyTuple_GetItem()}, \code{PyList_GetItem()} and
\code{PyDict_GetItem()} (and \code{PyDict_GetItemString()}) all return
references that you borrow from the tuple, list or dictionary.
\cfunction{PyTuple_GetItem()}, \cfunction{PyList_GetItem()},
\cfunction{PyDict_GetItem()}, and \cfunction{PyDict_GetItemString()}
all return references that you borrow from the tuple, list or
dictionary.
The function \code{PyImport_AddModule()} also returns a borrowed
The function \cfunction{PyImport_AddModule()} also returns a borrowed
reference, even though it may actually create the object it returns:
this is possible because an owned reference to the object is stored in
\code{sys.modules}.
When you pass an object reference into another function, in general,
the function borrows the reference from you --- if it needs to store
it, it will use \code{Py_INCREF()} to become an independent owner.
There are exactly two important exceptions to this rule:
\code{PyTuple_SetItem()} and \code{PyList_SetItem()}. These functions
take over ownership of the item passed to them --- even if they fail!
(Note that \code{PyDict_SetItem()} and friends don't take over
ownership --- they are ``normal''.)
it, it will use \cfunction{Py_INCREF()} to become an independent
owner. There are exactly two important exceptions to this rule:
\cfunction{PyTuple_SetItem()} and \cfunction{PyList_SetItem()}. These
functions take over ownership of the item passed to them --- even if
they fail! (Note that \cfunction{PyDict_SetItem()} and friends don't
take over ownership --- they are ``normal''.)
When a \C{} function is called from Python, it borrows references to its
arguments from the caller. The caller owns a reference to the object,
so the borrowed reference's lifetime is guaranteed until the function
returns. Only when such a borrowed reference must be stored or passed
on, it must be turned into an owned reference by calling
\code{Py_INCREF()}.
\cfunction{Py_INCREF()}.
The object reference returned from a \C{} function that is called from
Python must be an owned reference --- ownership is tranferred from the
@ -1123,8 +1134,8 @@ invocations of the interpreter, which can cause the owner of a
reference to dispose of it.
The first and most important case to know about is using
\code{Py_DECREF()} on an unrelated object while borrowing a reference
to a list item. For instance:
\cfunction{Py_DECREF()} on an unrelated object while borrowing a
reference to a list item. For instance:
\begin{verbatim}
bug(PyObject *list) {
@ -1138,20 +1149,20 @@ This function first borrows a reference to \code{list[0]}, then
replaces \code{list[1]} with the value \code{0}, and finally prints
the borrowed reference. Looks harmless, right? But it's not!
Let's follow the control flow into \code{PyList_SetItem()}. The list
Let's follow the control flow into \cfunction{PyList_SetItem()}. The list
owns references to all its items, so when item 1 is replaced, it has
to dispose of the original item 1. Now let's suppose the original
item 1 was an instance of a user-defined class, and let's further
suppose that the class defined a \code{__del__()} method. If this
suppose that the class defined a \method{__del__()} method. If this
class instance has a reference count of 1, disposing of it will call
its \code{__del__()} method.
its \method{__del__()} method.
Since it is written in Python, the \code{__del__()} method can execute
Since it is written in Python, the \method{__del__()} method can execute
arbitrary Python code. Could it perhaps do something to invalidate
the reference to \code{item} in \code{bug()}? You bet! Assuming that
the list passed into \code{bug()} is accessible to the
\code{__del__()} method, it could execute a statement to the effect of
\code{del list[0]}, and assuming this was the last reference to that
the reference to \code{item} in \cfunction{bug()}? You bet! Assuming
that the list passed into \cfunction{bug()} is accessible to the
\method{__del__()} method, it could execute a statement to the effect of
\samp{del list[0]}, and assuming this was the last reference to that
object, it would free the memory associated with it, thereby
invalidating \code{item}.
@ -1171,7 +1182,7 @@ no_bug(PyObject *list) {
This is a true story. An older version of Python contained variants
of this bug and someone spent a considerable amount of time in a \C{}
debugger to figure out why his \code{__del__()} methods would fail...
debugger to figure out why his \method{__del__()} methods would fail...
The second case of problems with a borrowed reference is a variant
involving threads. Normally, multiple threads in the Python
@ -1208,11 +1219,11 @@ there would be a lot of redundant tests and the code would run slower.
It is better to test for \NULL{} only at the ``source'', i.e.\
when a pointer that may be \NULL{} is received, e.g.\ from
\code{malloc()} or from a function that may raise an exception.
\cfunction{malloc()} or from a function that may raise an exception.
The macros \code{Py_INCREF()} and \code{Py_DECREF()}
The macros \cfunction{Py_INCREF()} and \cfunction{Py_DECREF()}
don't check for \NULL{} pointers --- however, their variants
\code{Py_XINCREF()} and \code{Py_XDECREF()} do.
\cfunction{Py_XINCREF()} and \cfunction{Py_XDECREF()} do.
The macros for checking for a particular object type
(\code{Py\var{type}_Check()}) don't check for \NULL{} pointers ---
@ -1259,16 +1270,17 @@ interpreter to run some Python code.
So if you are embedding Python, you are providing your own main
program. One of the things this main program has to do is initialize
the Python interpreter. At the very least, you have to call the
function \code{Py_Initialize()}. There are optional calls to pass command
line arguments to Python. Then later you can call the interpreter
from any part of the application.
function \cfunction{Py_Initialize()}. There are optional calls to
pass command line arguments to Python. Then later you can call the
interpreter from any part of the application.
There are several different ways to call the interpreter: you can pass
a string containing Python statements to \code{PyRun_SimpleString()},
or you can pass a stdio file pointer and a file name (for
identification in error messages only) to \code{PyRun_SimpleFile()}. You
can also call the lower-level operations described in the previous
chapters to construct and use Python objects.
a string containing Python statements to
\cfunction{PyRun_SimpleString()}, or you can pass a stdio file pointer
and a file name (for identification in error messages only) to
\cfunction{PyRun_SimpleFile()}. You can also call the lower-level
operations described in the previous chapters to construct and use
Python objects.
A simple demo of embedding Python can be found in the directory
\file{Demo/embed}.
@ -1336,9 +1348,9 @@ loading. (SGI IRIX 5 might also support it but it is inferior to
using shared libraries so there is no reason to; a small test didn't
work right away so I gave up trying to support it.)
Before you build Python, you first need to fetch and build the \code{dl}
package written by Jack Jansen. This is available by anonymous ftp
from \url{ftp://ftp.cwi.nl/pub/dynload}, file
Before you build Python, you first need to fetch and build the
\code{dl} package written by Jack Jansen. This is available by
anonymous ftp from \url{ftp://ftp.cwi.nl/pub/dynload}, file
\file{dl-1.6.tar.Z}. (The version number may change.) Follow the
instructions in the package's \file{README} file to build it.
@ -1387,7 +1399,7 @@ will support GNU dynamic loading.
Since there are three styles of dynamic loading, there are also three
groups of instructions for building a dynamically loadable module.
Instructions common for all three styles are given first. Assuming
your module is called \code{spam}, the source filename must be
your module is called \module{spam}, the source filename must be
\file{spammodule.c}, so the object name is \file{spammodule.o}. The
module must be written as a normal Python extension module (as
described earlier).
@ -1425,12 +1437,12 @@ On SGI IRIX 5, use
ld -shared spammodule.o -o spammodule.so
\end{verbatim}
On other systems, consult the manual page for \code{ld}(1) to find what
flags, if any, must be used.
On other systems, consult the manual page for \manpage{ld}{1} to find
what flags, if any, must be used.
If your extension module uses system libraries that haven't already
been linked with Python (e.g. a windowing system), these must be
passed to the \code{ld} command as \samp{-l} options after the
passed to the \program{ld} command as \samp{-l} options after the
\samp{.o} file.
The resulting file \file{spammodule.so} must be copied into a directory