| \documentstyle[twoside,11pt,myformat]{report} |
| |
| \title{Extending and Embedding the Python Interpreter} |
| |
| \author{ |
| Guido van Rossum \\ |
| Dept. CST, CWI, P.O. Box 94079 \\ |
| 1090 GB Amsterdam, The Netherlands \\ |
| E-mail: {\tt guido@cwi.nl} |
| } |
| |
| \date{14 Jul 1994 \\ Release 1.0.3} % XXX update before release! |
| |
| % Tell \index to actually write the .idx file |
| \makeindex |
| |
| \begin{document} |
| |
| \pagenumbering{roman} |
| |
| \maketitle |
| |
| \begin{abstract} |
| |
| \noindent |
| This document describes how to write modules in C or C++ to extend the |
| Python interpreter. It also describes how to use Python as an |
| `embedded' language, and how extension modules can be loaded |
| dynamically (at run time) into the interpreter, if the operating |
| system supports this feature. |
| |
| \end{abstract} |
| |
| \pagebreak |
| |
| { |
| \parskip = 0mm |
| \tableofcontents |
| } |
| |
| \pagebreak |
| |
| \pagenumbering{arabic} |
| |
| |
| \chapter{Extending Python with C or C++ code} |
| |
| |
| \section{Introduction} |
| |
| It is quite easy to add non-standard built-in modules to Python, if |
| you know how to program in C. A built-in module known to the Python |
| programmer as \code{foo} is generally implemented by a file called |
| \file{foomodule.c}. All but the two most essential standard built-in |
| modules also adhere to this convention, and in fact some of them form |
| excellent examples of how to create an extension. |
| |
| Extension modules can do two things that can't be done directly in |
| Python: they can implement new data types (which are different from |
| classes by the way), and they can make system calls or call C library |
| functions. Since the latter is usually the most important reason for |
| adding an extension, I'll concentrate on adding `wrappers' around C |
| library functions; the concrete example uses the wrapper for |
| \code{system()} in module \code{posix}, found in (of course) the file |
| \file{Modules/posixmodule.c}. |
| |
| Note: unless otherwise mentioned, all file references in this |
| document are relative to the toplevel directory of the Python |
| distribution --- i.e. the directory that contains the \file{configure} |
| script. |
| |
| The compilation of an extension module depends on your system setup |
| and the intended use of the module; details are given in a later |
| section. |
| |
| |
| \section{A first look at the code} |
| |
| It is important not to be impressed by the size and complexity of |
| the average extension module; much of this is straightforward |
| `boilerplate' code (starting right with the copyright notice)! |
| |
| Let's skip the boilerplate and have a look at an interesting function |
| in \file{posixmodule.c} first: |
| |
| \begin{verbatim} |
| static object * |
| posix_system(self, args) |
| object *self; |
| object *args; |
| { |
| char *command; |
| int sts; |
| if (!getargs(args, "s", &command)) |
| return NULL; |
| sts = system(command); |
| return mkvalue("i", sts); |
| } |
| \end{verbatim} |
| |
| This is the prototypical top-level function in an extension module. |
| It will be called (we'll see later how) when the Python program |
| executes statements like |
| |
| \begin{verbatim} |
| >>> import posix |
| >>> sts = posix.system('ls -l') |
| \end{verbatim} |
| |
| There is a straightforward translation from the arguments to the call |
| in Python (here the single expression \code{'ls -l'}) to the arguments that |
| are passed to the C function. The C function always has two |
| parameters, conventionally named \var{self} and \var{args}. The |
| \var{self} argument is used when the C function implements a builtin |
| method --- this is advanced material and not covered in this document. |
| In the example, \var{self} will always be a \code{NULL} pointer, since |
| we are defining a function, not a method (this is done so that the |
| interpreter doesn't have to understand two different types of C |
| functions). |
| |
| The \var{args} parameter will be a pointer to a Python object, or |
| \code{NULL} if the Python function/method was called without |
| arguments. It is necessary to do full argument type checking on each |
| call, since otherwise the Python user would be able to cause the |
| Python interpreter to `dump core' by passing invalid arguments to a |
| function in an extension module. Because argument checking and |
| converting arguments to C are such common tasks, there's a general |
| function in the Python interpreter that combines them: |
| \code{getargs()}. It uses a template string to determine both the |
| types of the Python argument and the types of the C variables into |
| which it should store the converted values.\footnote{There are |
| convenience macros \code{getnoarg()}, \code{getstrarg()}, |
| \code{getintarg()}, etc., for many common forms of \code{getargs()} |
| templates. These are relics from the past; the recommended practice |
| is to call \code{getargs()} directly.} (More about this later.) |
| |
| If \code{getargs()} returns nonzero, the argument list has the right |
| type and its components have been stored in the variables whose |
| addresses are passed. If it returns zero, an error has occurred. In |
| the latter case it has already raised an appropriate exception by so |
| the calling function should return \code{NULL} immediately --- see the |
| next section. |
| |
| |
| \section{Intermezzo: errors and exceptions} |
| |
| An important convention throughout the Python interpreter is the |
| following: when a function fails, it should set an exception condition |
| and return an error value (often a \code{NULL} pointer). Exceptions |
| are stored in a static global variable in \file{Python/errors.c}; if |
| this variable is \code{NULL} no exception has occurred. A second |
| static global variable stores the `associated value' of the exception |
| --- the second argument to \code{raise}. |
| |
| The file \file{errors.h} declares a host of functions to set various |
| types of exceptions. The most common one is \code{err_setstr()} --- |
| its arguments are an exception object (e.g. \code{RuntimeError} --- |
| actually it can be any string object) and a C string indicating the |
| cause of the error (this is converted to a string object and stored as |
| the `associated value' of the exception). Another useful function is |
| \code{err_errno()}, which only takes an exception argument and |
| constructs the associated value by inspection of the (UNIX) global |
| variable errno. The most general function is \code{err_set()}, which |
| takes two object arguments, the exception and its associated value. |
| You don't need to \code{INCREF()} the objects passed to any of these |
| functions. |
| |
| You can test non-destructively whether an exception has been set with |
| \code{err_occurred()}. However, most code never calls |
| \code{err_occurred()} to see whether an error occurred or not, but |
| relies on error return values from the functions it calls instead. |
| |
| When a function that calls another function detects that the called |
| function fails, it should return an error value (e.g. \code{NULL} or |
| \code{-1}) but not call one of the \code{err_*} functions --- one has |
| already been called. The caller is then supposed to also return an |
| error indication to {\em its} caller, again {\em without} calling |
| \code{err_*()}, and so on --- the most detailed cause of the error was |
| already reported by the function that first detected it. Once the |
| error has reached Python's interpreter main loop, this aborts the |
| currently executing Python code and tries to find an exception handler |
| specified by the Python programmer. |
| |
| (There are situations where a module can actually give a more detailed |
| error message by calling another \code{err_*} 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{err_clear()}. The only time C code should call |
| \code{err_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). |
| |
| Finally, the function \code{err_get()} gives you both error variables |
| {\em and clears them}. Note that even if an error occurred the second |
| one may be \code{NULL}. You have to \code{XDECREF()} both when you |
| are finished with them. I doubt you will need to use this function. |
| |
| Note that a failing \code{malloc()} call must also be turned into an |
| exception --- the direct caller of \code{malloc()} (or |
| \code{realloc()}) must call \code{err_nomem()} and return a failure |
| indicator itself. All the object-creating functions |
| (\code{newintobject()} etc.) already do this, so only if you call |
| \code{malloc()} directly this note is of importance. |
| |
| Also note that, with the important exception of \code{getargs()}, |
| functions that return an integer status usually return \code{0} or a |
| positive value for success and \code{-1} for failure. |
| |
| Finally, be careful about cleaning up garbage (making \code{XDECREF()} |
| or \code{DECREF()} calls for objects you have already created) when |
| you return an error! |
| |
| 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{ZeroDevisionError} which you can use directly. Of course, |
| you should chose exceptions wisely --- don't use \code{TypeError} to |
| mean that a file couldn't be opened (that should probably be |
| \code{IOError}). If anything's wrong with the argument list the |
| \code{getargs()} function raises \code{TypeError}. If you have an |
| argument whose value which must be in a particular range or must |
| satisfy other conditions, \code{ValueError} is appropriate. |
| |
| You can also define a new exception that is unique to your module. |
| For this, you usually declare a static object variable at the |
| beginning of your file, e.g. |
| |
| \begin{verbatim} |
| static object *FooError; |
| \end{verbatim} |
| |
| and initialize it in your module's initialization function |
| (\code{initfoo()}) with a string object, e.g. (leaving out the error |
| checking for simplicity): |
| |
| \begin{verbatim} |
| void |
| initfoo() |
| { |
| object *m, *d; |
| m = initmodule("foo", foo_methods); |
| d = getmoduledict(m); |
| FooError = newstringobject("foo.error"); |
| dictinsert(d, "error", FooError); |
| } |
| \end{verbatim} |
| |
| |
| \section{Back to the example} |
| |
| Going back to \code{posix_system()}, you should now be able to |
| understand this bit: |
| |
| \begin{verbatim} |
| if (!getargs(args, "s", &command)) |
| return NULL; |
| \end{verbatim} |
| |
| It returns \code{NULL} (the error indicator for functions of this |
| kind) if an error is detected in the argument list, relying on the |
| exception set by \code{getargs()}. Otherwise the string value of the |
| argument has been copied to the local variable \code{command} --- this |
| is in fact just a pointer assignment and you are not supposed to |
| modify the string to which it points. |
| |
| If a function is called with multiple arguments, the argument list |
| (the argument \code{args}) is turned into a tuple. If it is called |
| without arguments, \code{args} is \code{NULL}. \code{getargs()} knows |
| about this; see later. |
| |
| The next statement in \code{posix_system()} is a call to the C library |
| function \code{system()}, passing it the string we just got from |
| \code{getargs()}: |
| |
| \begin{verbatim} |
| sts = system(command); |
| \end{verbatim} |
| |
| Finally, \code{posix.system()} must return a value: the integer status |
| returned by the C library \code{system()} function. This is done |
| using the function \code{mkvalue()}, which is something like the |
| inverse of \code{getargs()}: it takes a format string and a variable |
| number of C values and returns a new Python object. |
| |
| \begin{verbatim} |
| return mkvalue("i", sts); |
| \end{verbatim} |
| |
| In this case, it returns an integer object (yes, even integers are |
| objects on the heap in Python!). More info on \code{mkvalue()} is |
| given later. |
| |
| If you had a function that returned no useful argument (a.k.a. a |
| procedure), you would need this idiom: |
| |
| \begin{verbatim} |
| INCREF(None); |
| return None; |
| \end{verbatim} |
| |
| \code{None} is a unique Python object representing `no value'. It |
| differs from \code{NULL}, which means `error' in most contexts. |
| |
| |
| \section{The module's function table} |
| |
| I promised to show how I made the function \code{posix_system()} |
| callable from Python programs. This is shown later in |
| \file{Modules/posixmodule.c}: |
| |
| \begin{verbatim} |
| static struct methodlist posix_methods[] = { |
| ... |
| {"system", posix_system}, |
| ... |
| {NULL, NULL} /* Sentinel */ |
| }; |
| |
| void |
| initposix() |
| { |
| (void) initmodule("posix", posix_methods); |
| } |
| \end{verbatim} |
| |
| (The actual \code{initposix()} is somewhat more complicated, but many |
| extension modules can be as simple as shown here.) When the Python |
| program first imports module \code{posix}, \code{initposix()} is |
| called, which calls \code{initmodule()} with specific parameters. |
| This creates a `module object' (which is inserted in the table |
| \code{sys.modules} under the key \code{'posix'}), and adds |
| built-in-function objects to the newly created module based upon the |
| table (of type struct methodlist) that was passed as its second |
| parameter. The function \code{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 you don't need to check for errors. |
| |
| |
| \section{Compilation and linkage} |
| |
| There are two more things to do before you can use your new extension |
| module: compiling and linking it with the Python system. If you use |
| dynamic loading, the details depend on the style of dynamic loading |
| your system uses; see the chapter on Dynamic Loading for more info |
| about this. |
| |
| If you can't use dynamic loading, or if you want to make your module a |
| permanent part of the Python interpreter, you will have to change the |
| configuration setup and rebuild the interpreter. Luckily, in the 1.0 |
| release this is very simple: just place your file (named |
| \file{foomodule.c} for example) in the \file{Modules} directory, add a |
| line to the file \file{Modules/Setup} describing your file: |
| |
| \begin{verbatim} |
| foo foomodule.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} |
| 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.) |
| |
| |
| \section{Calling Python functions from C} |
| |
| So far we have concentrated on making C functions callable from |
| Python. The reverse is also useful: calling Python functions from C. |
| This is especially the case for libraries that support so-called |
| `callback' functions. If a C interface makes use of callbacks, the |
| equivalent Python often needs to provide a callback mechanism to the |
| Python programmer; the implementation will require calling the Python |
| callback functions from a C callback. Other uses are also imaginable. |
| |
| Fortunately, the Python interpreter is easily called recursively, and |
| there is a standard interface to call a Python function. (I won't |
| dwell on how to call the Python parser with a particular string as |
| input --- if you're interested, have a look at the implementation of |
| the \samp{-c} command line option in \file{Python/pythonmain.c}.) |
| |
| Calling a Python function is easy. First, the Python program must |
| somehow pass you the Python function object. You should provide a |
| function (or some other interface) to do this. When this function is |
| called, save a pointer to the Python function object (be careful to |
| \code{INCREF()} it!) in a global variable --- or whereever you see fit. |
| For example, the following function might be part of a module |
| definition: |
| |
| \begin{verbatim} |
| static object *my_callback = NULL; |
| |
| static object * |
| my_set_callback(dummy, arg) |
| object *dummy, *arg; |
| { |
| XDECREF(my_callback); /* Dispose of previous callback */ |
| my_callback = arg; |
| XINCREF(my_callback); /* Remember new callback */ |
| /* Boilerplate for "void" return */ |
| INCREF(None); |
| return None; |
| } |
| \end{verbatim} |
| |
| This particular function doesn't do any typechecking on its argument |
| --- that will be done by \code{call_object()}, which is a bit late but |
| at least protects the Python interpreter from shooting itself in its |
| foot. (The problem with typechecking functions is that there are at |
| least five different Python object types that can be called, so the |
| test would be somewhat cumbersome.) |
| |
| The macros \code{XINCREF()} and \code{XDECREF()} increment/decrement |
| the reference count of an object and are safe in the presence of |
| \code{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{call_object()}. 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, you must pass an empty tuple. For example: |
| |
| \begin{verbatim} |
| object *arglist; |
| object *result; |
| ... |
| /* Time to call the callback */ |
| arglist = mktuple(0); |
| result = call_object(my_callback, arglist); |
| DECREF(arglist); |
| \end{verbatim} |
| |
| \code{call_object()} returns a Python object pointer: this is |
| the return value of the Python function. \code{call_object()} 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{DECREF()}-ed immediately after the call. |
| |
| The return value of \code{call_object()} 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{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 \code{NULL}. If it is, the Python function terminated by raising |
| an exception. If the C code that called \code{call_object()} 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{err_clear()}. For example: |
| |
| \begin{verbatim} |
| if (result == NULL) |
| return NULL; /* Pass error back */ |
| /* Here maybe use the result */ |
| DECREF(result); |
| \end{verbatim} |
| |
| Depending on the desired interface to the Python callback function, |
| you may also have to provide an argument list to \code{call_object()}. |
| 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{mkvalue()}. For example, if you want to pass an integral |
| event code, you might use the following code: |
| |
| \begin{verbatim} |
| object *arglist; |
| ... |
| arglist = mkvalue("(l)", eventcode); |
| result = call_object(my_callback, arglist); |
| DECREF(arglist); |
| if (result == NULL) |
| return NULL; /* Pass error back */ |
| /* Here maybe use the result */ |
| DECREF(result); |
| \end{verbatim} |
| |
| Note the placement of DECREF(argument) immediately after the call, |
| before the error check! Also note that strictly spoken this code is |
| not complete: \code{mkvalue()} may run out of memory, and this should |
| be checked. |
| |
| |
| \section{Format strings for {\tt getargs()}} |
| |
| The \code{getargs()} function is declared in \file{modsupport.h} as |
| follows: |
| |
| \begin{verbatim} |
| int getargs(object *arg, char *format, ...); |
| \end{verbatim} |
| |
| The remaining arguments must be addresses of variables whose type is |
| determined by the format string. For the conversion to succeed, the |
| \var{arg} object must match the format and the format must be exhausted. |
| Note that while \code{getargs()} checks that the Python object really |
| is of the specified type, it cannot check the validity of the |
| addresses of C variables provided in the call: if you make mistakes |
| there, your code will probably dump core. |
| |
| A non-empty format string consists of a single `format unit'. A |
| format unit describes one Python object; it is usually a single |
| character or a parenthesized sequence of format units. The type of a |
| format units is determined from its first character, the `format |
| letter': |
| |
| \begin{description} |
| |
| \item[\samp{s} (string)] |
| The Python object must be a string object. The C argument must be a |
| \code{(char**)} (i.e. the address of a character pointer), and a pointer |
| to the C string contained in the Python object is stored into it. You |
| must not provide storage to store the string; a pointer to an existing |
| string is stored into the character pointer variable whose address you |
| pass. If the next character in the format string is \samp{\#}, |
| another C argument of type \code{(int*)} must be present, and the |
| length of the Python string (not counting the trailing zero byte) is |
| stored into it. |
| |
| \item[\samp{z} (string or zero, i.e. \code{NULL})] |
| Like \samp{s}, but the object may also be None. In this case the |
| string pointer is set to \code{NULL} and if a \samp{\#} is present the |
| size is set to 0. |
| |
| \item[\samp{b} (byte, i.e. char interpreted as tiny int)] |
| The object must be a Python integer. The C argument must be a |
| \code{(char*)}. |
| |
| \item[\samp{h} (half, i.e. short)] |
| The object must be a Python integer. The C argument must be a |
| \code{(short*)}. |
| |
| \item[\samp{i} (int)] |
| The object must be a Python integer. The C argument must be an |
| \code{(int*)}. |
| |
| \item[\samp{l} (long)] |
| The object must be a (plain!) Python integer. The C argument must be |
| a \code{(long*)}. |
| |
| \item[\samp{c} (char)] |
| The Python object must be a string of length 1. The C argument must |
| be a \code{(char*)}. (Don't pass an \code{(int*)}!) |
| |
| \item[\samp{f} (float)] |
| The object must be a Python int or float. The C argument must be a |
| \code{(float*)}. |
| |
| \item[\samp{d} (double)] |
| The object must be a Python int or float. The C argument must be a |
| \code{(double*)}. |
| |
| \item[\samp{S} (string object)] |
| The object must be a Python string. The C argument must be an |
| \code{(object**)} (i.e. the address of an object pointer). The C |
| program thus gets back the actual string object that was passed, not |
| just a pointer to its array of characters and its size as for format |
| character \samp{s}. The reference count of the object has not been |
| increased. |
| |
| \item[\samp{O} (object)] |
| The object can be any Python object, including None, but not |
| \code{NULL}. The C argument must be an \code{(object**)}. This can be |
| used if an argument list must contain objects of a type for which no |
| format letter exist: the caller must then check that it has the right |
| type. The reference count of the object has not been increased. |
| |
| \item[\samp{(} (tuple)] |
| The object must be a Python tuple. Following the \samp{(} character |
| in the format string must come a number of format units describing the |
| elements of the tuple, followed by a \samp{)} character. Tuple |
| format units may be nested. (There are no exceptions for empty and |
| singleton tuples; \samp{()} specifies an empty tuple and \samp{(i)} a |
| singleton of one integer. Normally you don't want to use the latter, |
| since it is hard for the Python user to specify. |
| |
| \end{description} |
| |
| More format characters will probably be added as the need arises. It |
| should (but currently isn't) be allowed to use Python long integers |
| whereever integers are expected, and perform a range check. (A range |
| check is in fact always necessary for the \samp{b}, \samp{h} and |
| \samp{i} format letters, but this is currently not implemented.) |
| |
| Some example calls: |
| |
| \begin{verbatim} |
| int ok; |
| int i, j; |
| long k, l; |
| char *s; |
| int size; |
| |
| ok = getargs(args, ""); /* No arguments */ |
| /* Python call: f() */ |
| |
| ok = getargs(args, "s", &s); /* A string */ |
| /* Possible Python call: f('whoops!') */ |
| |
| ok = getargs(args, "(lls)", &k, &l, &s); /* Two longs and a string */ |
| /* Possible Python call: f(1, 2, 'three') */ |
| |
| ok = getargs(args, "((ii)s#)", &i, &j, &s, &size); |
| /* A pair of ints and a string, whose size is also returned */ |
| /* Possible Python call: f(1, 2, 'three') */ |
| |
| { |
| int left, top, right, bottom, h, v; |
| ok = getargs(args, "(((ii)(ii))(ii))", |
| &left, &top, &right, &bottom, &h, &v); |
| /* A rectangle and a point */ |
| /* Possible Python call: |
| f( ((0, 0), (400, 300)), (10, 10)) */ |
| } |
| \end{verbatim} |
| |
| Note that the `top level' of a non-empty format string must consist of |
| a single unit; strings like \samp{is} and \samp{(ii)s\#} are not valid |
| format strings. (But \samp{s\#} is.) If you have multiple arguments, |
| the format must therefore always be enclosed in parentheses, as in the |
| examples \samp{((ii)s\#)} and \samp{(((ii)(ii))(ii)}. (The current |
| implementation does not complain when more than one unparenthesized |
| format unit is given. Sorry.) |
| |
| The \code{getargs()} function does not support variable-length |
| argument lists. In simple cases you can fake these by trying several |
| calls to |
| \code{getargs()} until one succeeds, but you must take care to call |
| \code{err_clear()} before each retry. For example: |
| |
| \begin{verbatim} |
| static object *my_method(self, args) object *self, *args; { |
| int i, j, k; |
| |
| if (getargs(args, "(ii)", &i, &j)) { |
| k = 0; /* Use default third argument */ |
| } |
| else { |
| err_clear(); |
| if (!getargs(args, "(iii)", &i, &j, &k)) |
| return NULL; |
| } |
| /* ... use i, j and k here ... */ |
| INCREF(None); |
| return None; |
| } |
| \end{verbatim} |
| |
| (It is possible to think of an extension to the definition of format |
| strings to accommodate this directly, e.g. placing a \samp{|} in a |
| tuple might specify that the remaining arguments are optional. |
| \code{getargs()} should then return one more than the number of |
| variables stored into.) |
| |
| Advanced users note: If you set the `varargs' flag in the method list |
| for a function, the argument will always be a tuple (the `raw argument |
| list'). In this case you must enclose single and empty argument lists |
| in parentheses, e.g. \samp{(s)} and \samp{()}. |
| |
| |
| \section{The {\tt mkvalue()} function} |
| |
| This function is the counterpart to \code{getargs()}. It is declared |
| in \file{Include/modsupport.h} as follows: |
| |
| \begin{verbatim} |
| object *mkvalue(char *format, ...); |
| \end{verbatim} |
| |
| It supports exactly the same format letters as \code{getargs()}, but |
| the arguments (which are input to the function, not output) must not |
| be pointers, just values. If a byte, short or float is passed to a |
| varargs function, it is widened by the compiler to int or double, so |
| \samp{b} and \samp{h} are treated as \samp{i} and \samp{f} is |
| treated as \samp{d}. \samp{S} is treated as \samp{O}, \samp{s} is |
| treated as \samp{z}. \samp{z\#} and \samp{s\#} are supported: a |
| second argument specifies the length of the data (negative means use |
| \code{strlen()}). \samp{S} and \samp{O} add a reference to their |
| argument (so you should \code{DECREF()} it if you've just created it |
| and aren't going to use it again). |
| |
| If the argument for \samp{O} or \samp{S} is a \code{NULL} pointer, it is |
| assumed that this was caused because the call producing the argument |
| found an error and set an exception. Therefore, \code{mkvalue()} will |
| return \code{NULL} but won't set an exception if one is already set. |
| If no exception is set, \code{SystemError} is set. |
| |
| If there is an error in the format string, the \code{SystemError} |
| exception is set, since it is the calling C code's fault, not that of |
| the Python user who sees the exception. |
| |
| Example: |
| |
| \begin{verbatim} |
| return mkvalue("(ii)", 0, 0); |
| \end{verbatim} |
| |
| returns a tuple containing two zeros. (Outer parentheses in the |
| format string are actually superfluous, but you can use them for |
| compatibility with \code{getargs()}, which requires them if more than |
| one argument is expected.) |
| |
| |
| \section{Reference counts} |
| |
| Here's a useful explanation of \code{INCREF()} and \code{DECREF()} |
| (after an original by Sjoerd Mullender). |
| |
| Use \code{XINCREF()} or \code{XDECREF()} instead of \code{INCREF()} or |
| \code{DECREF()} when the argument may be \code{NULL} --- the versions |
| without \samp{X} are faster but wull dump core when they encounter a |
| \code{NULL} pointer. |
| |
| The basic idea is, if you create an extra reference to an object, you |
| must \code{INCREF()} it, if you throw away a reference to an object, |
| you must \code{DECREF()} it. Functions such as |
| \code{newstringobject()}, \code{newsizedstringobject()}, |
| \code{newintobject()}, etc. create a reference to an object. If you |
| want to throw away the object thus created, you must use |
| \code{DECREF()}. |
| |
| If you put an object into a tuple or list using \code{settupleitem()} |
| or \code{setlistitem()}, the idea is that you usually don't want to |
| keep a reference of your own around, so Python does not |
| \code{INCREF()} the elements. It does \code{DECREF()} the old value. |
| This means that if you put something into such an object using the |
| functions Python provides for this, you must \code{INCREF()} the |
| object if you also want to keep a separate reference to the object around. |
| Also, if you replace an element, you should \code{INCREF()} the old |
| element first if you want to keep it. If you didn't \code{INCREF()} |
| it before you replaced it, you are not allowed to look at it anymore, |
| since it may have been freed. |
| |
| Returning an object to Python (i.e. when your C function returns) |
| creates a reference to an object, but it does not change the reference |
| count. When your code does not keep another reference to the object, |
| you should not \code{INCREF()} or \code{DECREF()} it (assuming it is a |
| newly created object). When you do keep a reference around, you |
| should \code{INCREF()} the object. Also, when you return a global |
| object such as \code{None}, you should \code{INCREF()} it. |
| |
| If you want to return a tuple, you should consider using |
| \code{mkvalue()}. This function creates a new tuple with a reference |
| count of 1 which you can return. If any of the elements you put into |
| the tuple are objects (format codes \samp{O} or \samp{S}), they |
| are \code{INCREF()}'ed by \code{mkvalue()}. If you don't want to keep |
| references to those elements around, you should \code{DECREF()} them |
| after having called \code{mkvalue()}. |
| |
| Usually you don't have to worry about arguments. They are |
| \code{INCREF()}'ed before your function is called and |
| \code{DECREF()}'ed after your function returns. When you keep a |
| reference to an argument, you should \code{INCREF()} it and |
| \code{DECREF()} when you throw it away. Also, when you return an |
| argument, you should \code{INCREF()} it, because returning the |
| argument creates an extra reference to it. |
| |
| If you use \code{getargs()} to parse the arguments, you can get a |
| reference to an object (by using \samp{O} in the format string). This |
| object was not \code{INCREF()}'ed, so you should not \code{DECREF()} |
| it. If you want to keep the object, you must \code{INCREF()} it |
| yourself. |
| |
| If you create your own type of objects, you should use \code{NEWOBJ()} |
| to create the object. This sets the reference count to 1. If you |
| want to throw away the object, you should use \code{DECREF()}. When |
| the reference count reaches zero, your type's \code{dealloc()} |
| function is called. In it, you should \code{DECREF()} all object to |
| which you keep references in your object, but you should not use |
| \code{DECREF()} on your object. You should use \code{DEL()} instead. |
| |
| |
| \section{Writing extensions in C++} |
| |
| It is possible to write extension modules in C++. Some restrictions |
| apply: since the main program (the Python interpreter) is compiled and |
| linked by the C compiler, global or static objects with constructors |
| cannot be used. All functions that will be called directly or |
| indirectly (i.e. via function pointers) by the Python interpreter will |
| have to be declared using \code{extern "C"}; this applies to all |
| `methods' as well as to the module's initialization function. |
| It is unnecessary to enclose the Python header files in |
| \code{extern "C" \{...\}} --- they do this already. |
| |
| |
| \chapter{Embedding Python in another application} |
| |
| Embedding Python is similar to extending it, but not quite. The |
| difference is that when you extend Python, the main program of the |
| application is still the Python interpreter, while of you embed |
| Python, the main program may have nothing to do with Python --- |
| instead, some parts of the application occasionally call the Python |
| 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{initall()}. 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{run_command()}, or you |
| can pass a stdio file pointer and a file name (for identification in |
| error messages only) to \code{run_script()}. 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}. |
| |
| |
| \section{Embedding Python in C++} |
| |
| It is also possible to embed Python in a C++ program; how this is done |
| exactly will depend on the details of the C++ system used; in general |
| you will need to write the main program in C++, and use the C++ |
| compiler to compile and link your program. There is no need to |
| recompile Python itself with C++. |
| |
| |
| \chapter{Dynamic Loading} |
| |
| On most modern systems it is possible to configure Python to support |
| dynamic loading of extension modules implemented in C. When shared |
| libraries are used dynamic loading is configured automatically; |
| otherwise you have to select it as a build option (see below). Once |
| configured, dynamic loading is trivial to use: when a Python program |
| executes \code{import foo}, the search for modules tries to find a |
| file \file{foomodule.o} (\file{foomodule.so} when using shared |
| libraries) in the module search path, and if one is found, it is |
| loaded into the executing binary and executed. Once loaded, the |
| module acts just like a built-in extension module. |
| |
| The advantages of dynamic loading are twofold: the `core' Python |
| binary gets smaller, and users can extend Python with their own |
| modules implemented in C without having to build and maintain their |
| own copy of the Python interpreter. There are also disadvantages: |
| dynamic loading isn't available on all systems (this just means that |
| on some systems you have to use static loading), and dynamically |
| loading a module that was compiled for a different version of Python |
| (e.g. with a different representation of objects) may dump core. |
| |
| |
| \section{Configuring and building the interpreter for dynamic loading} |
| |
| There are three styles of dynamic loading: one using shared libraries, |
| one using SGI IRIX 4 dynamic loading, and one using GNU dynamic |
| loading. |
| |
| \subsection{Shared libraries} |
| |
| The following systems supports dynamic loading using shared libraries: |
| SunOS 4; Solaris 2; SGI IRIX 5 (but not SGI IRIX 4!); and probably all |
| systems derived from SVR4, or at least those SVR4 derivatives that |
| support shared libraries (are there any that don't?). |
| |
| You don't need to do anything to configure dynamic loading on these |
| systems --- the \file{configure} detects the presence of the |
| \file{<dlfcn.h>} header file and automatically configures dynamic |
| loading. |
| |
| \subsection{SGI dynamic loading} |
| |
| Only SGI IRIX 4 supports dynamic loading of modules using SGI dynamic |
| 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 host \file{ftp.cwi.nl}, directory \file{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. |
| |
| Once you have built \code{dl}, you can configure Python to use it. To |
| this end, you run the \file{configure} script with the option |
| \code{--with-dl=\var{directory}} where \var{directory} is the absolute |
| pathname of the \code{dl} directory. |
| |
| Now build and install Python as you normally would (see the |
| \file{README} file in the toplevel Python directory.) |
| |
| \subsection{GNU dynamic loading} |
| |
| GNU dynamic loading supports (according to its \file{README} file) the |
| following hardware and software combinations: VAX (Ultrix), Sun 3 |
| (SunOS 3.4 and 4.0), Sparc (SunOS 4.0), Sequent Symmetry (Dynix), and |
| Atari ST. There is no reason to use it on a Sparc; I haven't seen a |
| Sun 3 for years so I don't know if these have shared libraries or not. |
| |
| You need to fetch and build two packages. One is GNU DLD 3.2.3, |
| available by anonymous ftp from host \file{ftp.cwi.nl}, directory |
| \file{pub/dynload}, file \file{dld-3.2.3.tar.Z}. (As far as I know, |
| no further development on GNU DLD is being done.) The other is an |
| emulation of Jack Jansen's \code{dl} package that I wrote on top of |
| GNU DLD 3.2.3. This is available from the same host and directory, |
| file dl-dld-1.1.tar.Z. (The version number may change --- but I doubt |
| it will.) Follow the instructions in each package's \file{README} |
| file to configure build them. |
| |
| Now configure Python. Run the \file{configure} script with the option |
| \code{--with-dl-dld=\var{dl-directory},\var{dld-directory}} where |
| \var{dl-directory} is the absolute pathname of the directory where you |
| have built the \file{dl-dld} package, and \var{dld-directory} is that |
| of the GNU DLD package. The Python interpreter you build hereafter |
| will support GNU dynamic loading. |
| |
| |
| \section{Building a dynamically loadable module} |
| |
| 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{foo}, the source filename must be |
| \file{foomodule.c}, so the object name is \file{foomodule.o}. The |
| module must be written as a normal Python extension module (as |
| described earlier). |
| |
| Note that in all cases you will have to create your own Makefile that |
| compiles your module file(s). This Makefile will have to pass two |
| \samp{-I} arguments to the C compiler which will make it find the |
| Python header files. If the Make variable \var{PYTHONTOP} points to |
| the toplevel Python directory, your \var{CFLAGS} Make variable should |
| contain the options \samp{-I\$(PYTHONTOP) -I\$(PYTHONTOP)/Include}. |
| (Most header files are in the \file{Include} subdirectory, but the |
| \file{config.h} header lives in the toplevel directory.) You must |
| also add \samp{-DHAVE_CONFIG_H} to the definition of \var{CFLAGS} to |
| direct the Python headers to include \file{config.h}. |
| |
| |
| \subsection{Shared libraries} |
| |
| You must link the \samp{.o} file to produce a shared library. This is |
| done using a special invocation of the \UNIX{} loader/linker, {\em |
| ld}(1). Unfortunately the invocation differs slightly per system. |
| |
| On SunOS 4, use |
| \begin{verbatim} |
| ld foomodule.o -o foomodule.so |
| \end{verbatim} |
| |
| On Solaris 2, use |
| \begin{verbatim} |
| ld -G foomodule.o -o foomodule.so |
| \end{verbatim} |
| |
| On SGI IRIX 5, use |
| \begin{verbatim} |
| ld -shared foomodule.o -o foomodule.so |
| \end{verbatim} |
| |
| On other systems, consult the manual page for {\em 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 {\em ld} command as \samp{-l} options after the |
| \samp{.o} file. |
| |
| The resulting file \file{foomodule.so} must be copied into a directory |
| along the Python module search path. |
| |
| |
| \subsection{SGI dynamic loading} |
| |
| {bf IMPORTANT:} You must compile your extension module with the |
| additional C flag \samp{-G0} (or \samp{-G 0}). This instruct the |
| assembler to generate position-independent code. |
| |
| You don't need to link the resulting \file{foomodule.o} file; just |
| copy it into a directory along the Python module search path. |
| |
| The first time your extension is loaded, it takes some extra time and |
| a few messages may be printed. This creates a file |
| \file{foomodule.ld} which is an image that can be loaded quickly into |
| the Python interpreter process. When a new Python interpreter is |
| installed, the \code{dl} package detects this and rebuilds |
| \file{foomodule.ld}. The file \file{foomodule.ld} is placed in the |
| directory where \file{foomodule.o} was found, unless this directory is |
| unwritable; in that case it is placed in a temporary |
| directory.\footnote{Check the manual page of the \code{dl} package for |
| details.} |
| |
| If your extension modules uses additional system libraries, you must |
| create a file \file{foomodule.libs} in the same directory as the |
| \file{foomodule.o}. This file should contain one or more lines with |
| whitespace-separated options that will be passed to the linker --- |
| normally only \samp{-l} options or absolute pathnames of libraries |
| (\samp{.a} files) should be used. |
| |
| |
| \subsection{GNU dynamic loading} |
| |
| Just copy \file{foomodule.o} into a directory along the Python module |
| search path. |
| |
| If your extension modules uses additional system libraries, you must |
| create a file \file{foomodule.libs} in the same directory as the |
| \file{foomodule.o}. This file should contain one or more lines with |
| whitespace-separated absolute pathnames of libraries (\samp{.a} |
| files). No \samp{-l} options can be used. |
| |
| |
| \input{ext.ind} |
| |
| \end{document} |