From 4a944d7a47410a7e1dac67e77bdf0fb3560b5439 Mon Sep 17 00:00:00 2001 From: Guido van Rossum Date: Thu, 14 Aug 1997 20:35:38 +0000 Subject: Added more stuff on initialization (still rudimentary) --- Doc/api.tex | 558 +++++++++++++++++++++++++++++++++++++++++++------------- Doc/api/api.tex | 558 +++++++++++++++++++++++++++++++++++++++++++------------- 2 files changed, 866 insertions(+), 250 deletions(-) diff --git a/Doc/api.tex b/Doc/api.tex index 95b7b58..3a0ddb0 100644 --- a/Doc/api.tex +++ b/Doc/api.tex @@ -42,123 +42,123 @@ API functions in detail. The Application Programmer's Interface to Python gives C and C++ programmers access to the Python interpreter at a variety of levels. -There are two fundamentally different reasons for using the Python/C -API. (The API is equally usable from C++, but for brevity it is -generally referred to as the Python/C API.) The first reason is to -write ``extension modules'' for specific purposes; these are C modules -that extend the Python interpreter. This is probably the most common -use. The second reason is to use Python as a component in a larger -application; this technique is generally referred to as ``embedding'' +There are two fundamentally different reasons for using the Python/C +API. (The API is equally usable from C++, but for brevity it is +generally referred to as the Python/C API.) The first reason is to +write ``extension modules'' for specific purposes; these are C modules +that extend the Python interpreter. This is probably the most common +use. The second reason is to use Python as a component in a larger +application; this technique is generally referred to as ``embedding'' Python in an application. -Writing an extension module is a relatively well-understood process, -where a ``cookbook'' approach works well. There are several tools -that automate the process to some extent. While people have embedded -Python in other applications since its early existence, the process of -embedding Python is less straightforward that writing an extension. -Python 1.5 introduces a number of new API functions as well as some -changes to the build process that make embedding much simpler. +Writing an extension module is a relatively well-understood process, +where a ``cookbook'' approach works well. There are several tools +that automate the process to some extent. While people have embedded +Python in other applications since its early existence, the process of +embedding Python is less straightforward that writing an extension. +Python 1.5 introduces a number of new API functions as well as some +changes to the build process that make embedding much simpler. This manual describes the 1.5 state of affair (as of Python 1.5a3). % XXX Eventually, take the historical notes out -Many API functions are useful independent of whether you're embedding -or extending Python; moreover, most applications that embed Python -will need to provide a custom extension as well, so it's probably a -good idea to become familiar with writing an extension before +Many API functions are useful independent of whether you're embedding +or extending Python; moreover, most applications that embed Python +will need to provide a custom extension as well, so it's probably a +good idea to become familiar with writing an extension before attempting to embed Python in a real application. \section{Objects, Types and Reference Counts} -Most Python/C API functions have one or more arguments as well as a -return value of type \code{PyObject *}. This type is a pointer -(obviously!) to an opaque data type representing an arbitrary Python -object. Since all Python object types are treated the same way by the -Python language in most situations (e.g., assignments, scope rules, -and argument passing), it is only fitting that they should be +Most Python/C API functions have one or more arguments as well as a +return value of type \code{PyObject *}. This type is a pointer +(obviously!) to an opaque data type representing an arbitrary Python +object. Since all Python object types are treated the same way by the +Python language in most situations (e.g., assignments, scope rules, +and argument passing), it is only fitting that they should be represented by a single C type. All Python objects live on the heap: -you never declare an automatic or static variable of type -\code{PyObject}, only pointer variables of type \code{PyObject *} can +you never declare an automatic or static variable of type +\code{PyObject}, only pointer variables of type \code{PyObject *} can be declared. -All Python objects (even Python integers) have a ``type'' and a -``reference count''. An object's type determines what kind of object -it is (e.g., an integer, a list, or a user-defined function; there are -many more as explained in the Python Language Reference Manual). For -each of the well-known types there is a macro to check whether an -object is of that type; for instance, \code{PyList_Check(a)} is true +All Python objects (even Python integers) have a ``type'' and a +``reference count''. An object's type determines what kind of object +it is (e.g., an integer, a list, or a user-defined function; there are +many more as explained in the Python Language Reference Manual). For +each of the well-known types there is a macro to check whether an +object is of that type; for instance, \code{PyList_Check(a)} is true iff the object pointed to by \code{a} is a Python list. -The reference count is important only because today's computers have a -finite (and often severly limited) memory size; it counts how many -different places there are that have a reference to an object. Such a -place could be another object, or a global (or static) C variable, or -a local variable in some C function. When an object's reference count -becomes zero, the object is deallocated. If it contains references to -other objects, their reference count is decremented. Those other -objects may be deallocated in turn, if this decrement makes their -reference count become zero, and so on. (There's an obvious problem -with objects that reference each other here; for now, the solution is +The reference count is important only because today's computers have a +finite (and often severly limited) memory size; it counts how many +different places there are that have a reference to an object. Such a +place could be another object, or a global (or static) C variable, or +a local variable in some C function. When an object's reference count +becomes zero, the object is deallocated. If it contains references to +other objects, their reference count is decremented. Those other +objects may be deallocated in turn, if this decrement makes their +reference count become zero, and so on. (There's an obvious problem +with objects that reference each other here; for now, the solution is ``don't do that''.) -Reference counts are always manipulated explicitly. The normal way is -to use the macro \code{Py_INCREF(a)} to increment an object's -reference count by one, and \code{Py_DECREF(a)} to decrement it by -one. The latter macro is considerably more complex than the former, -since it must check whether the reference count becomes zero and then -cause the object's deallocator, which is a function pointer contained -in the object's type structure. The type-specific deallocator takes -care of decrementing the reference counts for other objects contained -in the object, and so on, if this is a compound object type such as a -list. There's no chance that the reference count can overflow; at -least as many bits are used to hold the reference count as there are -distinct memory locations in virtual memory (assuming -\code{sizeof(long) >= sizeof(char *)}). Thus, the reference count +Reference counts are always manipulated explicitly. The normal way is +to use the macro \code{Py_INCREF(a)} to increment an object's +reference count by one, and \code{Py_DECREF(a)} to decrement it by +one. The latter macro is considerably more complex than the former, +since it must check whether the reference count becomes zero and then +cause the object's deallocator, which is a function pointer contained +in the object's type structure. The type-specific deallocator takes +care of decrementing the reference counts for other objects contained +in the object, and so on, if this is a compound object type such as a +list. There's no chance that the reference count can overflow; at +least as many bits are used to hold the reference count as there are +distinct memory locations in virtual memory (assuming +\code{sizeof(long) >= sizeof(char *)}). Thus, the reference count increment is a simple operation. -It is not necessary to increment an object's reference count for every -local variable that contains a pointer to an object. In theory, the -oject's reference count goes up by one when the variable is made to -point to it and it goes down by one when the variable goes out of -scope. However, these two cancel each other out, so at the end the -reference count hasn't changed. The only real reason to use the -reference count is to prevent the object from being deallocated as -long as our variable is pointing to it. If we know that there is at -least one other reference to the object that lives at least as long as -our variable, there is no need to increment the reference count -temporarily. An important situation where this arises is in objects -that are passed as arguments to C functions in an extension module -that are called from Python; the call mechanism guarantees to hold a +It is not necessary to increment an object's reference count for every +local variable that contains a pointer to an object. In theory, the +oject's reference count goes up by one when the variable is made to +point to it and it goes down by one when the variable goes out of +scope. However, these two cancel each other out, so at the end the +reference count hasn't changed. The only real reason to use the +reference count is to prevent the object from being deallocated as +long as our variable is pointing to it. If we know that there is at +least one other reference to the object that lives at least as long as +our variable, there is no need to increment the reference count +temporarily. An important situation where this arises is in objects +that are passed as arguments to C functions in an extension module +that are called from Python; the call mechanism guarantees to hold a reference to every argument for the duration of the call. -However, a common pitfall is to extract an object from a list and -holding on to it for a while without incrementing its reference count. -Some other operation might conceivably remove the object from the -list, decrementing its reference count and possible deallocating it. -The real danger is that innocent-looking operations may invoke -arbitrary Python code which could do this; there is a code path which -allows control to flow back to the user from a \code{Py_DECREF()}, so +However, a common pitfall is to extract an object from a list and +holding on to it for a while without incrementing its reference count. +Some other operation might conceivably remove the object from the +list, decrementing its reference count and possible deallocating it. +The real danger is that innocent-looking operations may invoke +arbitrary Python code which could do this; there is a code path which +allows control to flow back to the user from a \code{Py_DECREF()}, so almost any operation is potentially dangerous. -A safe approach is to always use the generic operations (functions -whose name begins with \code{PyObject_}, \code{PyNumber_}, -\code{PySequence_} or \code{PyMapping_}). These operations always -increment the reference count of the object they return. This leaves -the caller with the responsibility to call \code{Py_DECREF()} when +A safe approach is to always use the generic operations (functions +whose name begins with \code{PyObject_}, \code{PyNumber_}, +\code{PySequence_} or \code{PyMapping_}). These operations always +increment the reference count of the object they return. This leaves +the caller with the responsibility to call \code{Py_DECREF()} when they are done with the result; this soon becomes second nature. -There are very few other data types that play a significant role in -the Python/C API; most are all simple C types such as \code{int}, -\code{long}, \code{double} and \code{char *}. A few structure types -are used to describe static tables used to list the functions exported -by a module or the data attributes of a new object type. These will +There are very few other data types that play a significant role in +the Python/C API; most are all simple C types such as \code{int}, +\code{long}, \code{double} and \code{char *}. A few structure types +are used to describe static tables used to list the functions exported +by a module or the data attributes of a new object type. These will be discussed together with the functions that use them. \section{Exceptions} -The Python programmer only needs to deal with exceptions if specific -error handling is required; unhandled exceptions are automatically -propagated to the caller, then to the caller's caller, and so on, till -they reach the top-level interpreter, where they are reported to the +The Python programmer only needs to deal with exceptions if specific +error handling is required; unhandled exceptions are automatically +propagated to the caller, then to the caller's caller, and so on, till +they reach the top-level interpreter, where they are reported to the user accompanied by a stack trace. For C programmers, however, error checking always has to be explicit. @@ -166,57 +166,63 @@ For C programmers, however, error checking always has to be explicit. \section{Embedding Python} -The one important task that only embedders of the Python interpreter -have to worry about is the initialization (and possibly the -finalization) of the Python interpreter. Most functionality of the -interpreter can only be used after the interpreter has been +The one important task that only embedders of the Python interpreter +have to worry about is the initialization (and possibly the +finalization) of the Python interpreter. Most functionality of the +interpreter can only be used after the interpreter has been initialized. - -The basic initialization function is \code{Py_Initialize()}. This -initializes the table of loaded modules, and creates the fundamental -modules \code{__builtin__}, \code{__main__} and \code{sys}. It also +The basic initialization function is \code{Py_Initialize()}. This +initializes the table of loaded modules, and creates the fundamental +modules \code{__builtin__}, \code{__main__} and \code{sys}. It also initializes the module search path (\code{sys.path}). -\code{Py_Initialize()} does not set the ``script argument list'' -(\code{sys.argv}). If this variable is needed by Python code that -will be executed later, it must be set explicitly with a call to -\code{PySys_SetArgv(\var{argc}, \var{argv})} subsequent to the call +\code{Py_Initialize()} does not set the ``script argument list'' +(\code{sys.argv}). If this variable is needed by Python code that +will be executed later, it must be set explicitly with a call to +\code{PySys_SetArgv(\var{argc}, \var{argv})} subsequent to the call to \code{Py_Initialize()}. -On Unix, \code{Py_Initialize()} calculates the module search path -based upon its best guess for the location of the standard Python -interpreter executable, assuming that the Python library is found in a -fixed location relative to the Python interpreter executable. In -particular, it looks for a directory named \code{lib/python1.5} -(replacing \code{1.5} with the current interpreter version) relative -to the parent directory where the executable named \code{python} is -found on the shell command search path (the environment variable -\code{$PATH}). For instance, if the Python executable is found in -\code{/usr/local/bin/python}, it will assume that the libraries are in -\code{/usr/local/lib/python1.5}. In fact, this also the ``fallback'' -location, used when no executable file named \code{python} is found -along \code{\$PATH}. The user can change this behavior by setting the -environment variable \code{\$PYTHONHOME}, and can insert additional -directories in front of the standard path by setting +On Unix, \code{Py_Initialize()} calculates the module search path +based upon its best guess for the location of the standard Python +interpreter executable, assuming that the Python library is found in a +fixed location relative to the Python interpreter executable. In +particular, it looks for a directory named \code{lib/python1.5} +(replacing \code{1.5} with the current interpreter version) relative +to the parent directory where the executable named \code{python} is +found on the shell command search path (the environment variable +\code{$PATH}). For instance, if the Python executable is found in +\code{/usr/local/bin/python}, it will assume that the libraries are in +\code{/usr/local/lib/python1.5}. In fact, this also the ``fallback'' +location, used when no executable file named \code{python} is found +along \code{\$PATH}. The user can change this behavior by setting the +environment variable \code{\$PYTHONHOME}, and can insert additional +directories in front of the standard path by setting \code{\$PYTHONPATH}. -The embedding application can steer the search by calling -\code{Py_SetProgramName(\var{file})} \emph{before} calling -\code{Py_Initialize()}. Note that \code[$PYTHONHOME} still overrides -this and \code{\$PYTHONPATH} is still inserted in front of the +The embedding application can steer the search by calling +\code{Py_SetProgramName(\var{file})} \emph{before} calling +\code{Py_Initialize()}. Note that \code[$PYTHONHOME} still overrides +this and \code{\$PYTHONPATH} is still inserted in front of the standard path. -Sometimes, it is desirable to ``uninitialize'' Python. For instance, -the application may want to start over (make another call to -\code{Py_Initialize()}) or the application is simply done with its -use of Python and wants to free all memory allocated by Python. This +Sometimes, it is desirable to ``uninitialize'' Python. For instance, +the application may want to start over (make another call to +\code{Py_Initialize()}) or the application is simply done with its +use of Python and wants to free all memory allocated by Python. This can be accomplished by calling \code{Py_Finalize()}. % XXX More... \section{Embedding Python in Threaded Applications} -%XXX more here + + + + + + + + \chapter{Old Introduction} @@ -1258,6 +1264,308 @@ e.g. to check that an object is a dictionary, use \begin{cfuncdesc}{TYPE}{_PyObject_NEW_VAR}{TYPE, PyTypeObject *, int size} \end{cfuncdesc} +\chapter{Initialization, Finalization, and Threads} + +% XXX Check argument/return type of all these + +\begin{cfuncdesc}{void}{Py_Initialize}{} +Initialize the Python interpreter. In an application embedding +Python, this should be called before using any other Python/C API +functions; with the exception of \code{Py_SetProgramName()}, +\code{PyEval_InitThreads()}, \code{PyEval_ReleaseLock()}, and +\code{PyEval_AcquireLock()}. This initializes the table of loaded +modules (\code{sys.modules}), and creates the fundamental modules +\code{__builtin__}, \code{__main__} and \code{sys}. It also +initializes the module search path (\code{sys.path}). It does not set +\code{sys.argv}; use \code{PySys_SetArgv()} for that. It is a fatal +error to call it for a second time without calling +\code{Py_Finalize()} first. There is no return value; it is a fatal +error if the initialization fails. +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{Py_Finalize}{} +Undo all initializations made by \code{Py_Initialize()} and subsequent +use of Python/C API functions, and destroy all sub-interpreters (see +\code{Py_NewInterpreter()} below) that were created and not yet +destroyed since the last call to \code{Py_Initialize()}. Ideally, +this frees all memory allocated by the Python interpreter. It is a +fatal error to call it for a second time without calling +\code{Py_Initialize()} again first. There is no return value; errors +during finalization are ignored. + +This function is provided for a number of reasons. An embedding +application might want to restart Python without having to restart the +application itself. An application that has loaded the Python +interpreter from a dynamically loadable library (or DLL) might want to +free all memory allocated by Python before unloading the DLL. During a +hunt for memory leaks in an application a developer might want to free +all memory allocated by Python before exiting from the application. + +\emph{Bugs and caveats:} The destruction of modules and objects in +modules is done in random order; this may cause destructors +(\code{__del__} methods) to fail when they depend on other objects +(even functions) or modules. Dynamically loaded extension modules +loaded by Python are not unloaded. Small amounts of memory allocated +by the Python interpreter may not be freed (if you find a leak, please +report it). Memory tied up in circular references between objects is +not freed. Some memory allocated by extension modules may not be +freed. Some extension may not work properly if their initialization +routine is called more than once; this can happen if an applcation +calls \code{Py_Initialize()} and \code{Py_Finalize()} more than once. +\end{cfuncdesc} + +\begin{cfuncdesc}{PyThreadState *}{Py_NewInterpreter}{} +Create a new sub-interpreter. This is an (almost) totally separate +environment for the execution of Python code. In particular, the new +interpreter has separate, independent versions of all imported +modules, including the fundamental modules \code{__builtin__}, +\code{__main__} and \code{sys}. The table of loaded modules +(\code{sys.modules}) and the module search path (\code{sys.path}) are +also separate. The new environment has no \code{sys.argv} variable. +It has new standard I/O stream file objects \code{sys.stdin}, +\code{sys.stdout} and \code{sys.stderr} (however these refer to the +same underlying \code{FILE} structures in the C library). + +The return value points to the first thread state created in the new +sub-interpreter. This thread state is made the current thread state. +Note that no actual thread is created; see the discussion of thread +states below. If creation of the new interpreter is unsuccessful, +\code{NULL} is returned; no exception is set since the exception state +is stored in the current thread state and there may not be a current +thread state. (Like all other Python/C API functions, the global +interpreter lock must be held before calling this function and is +still held when it returns; however, unlike most other Python/C API +functions, there needn't be a current thread state on entry.) + +Extension modules are shared between (sub-)interpreters as follows: +the first time a particular extension is imported, it is initialized +normally, and a (shallow) copy of its module's dictionary is +squirreled away. When the same extension is imported by another +(sub-)interpreter, a new module is initialized and filled with the +contents of this copy; the extension's \code{init} function is not +called. Note that this is different from what happens when as +extension is imported after the interpreter has been completely +re-initialized by calling \code{Py_Finalize()} and +\code{Py_Initialize()}; in that case, the extension's \code{init} +function \emph{is} called again. + +\emph{Bugs and caveats:} Because sub-interpreters (and the main +interpreter) are part of the same process, the insulation between them +isn't perfect -- for example, using low-level file operations like +\code{os.close()} they can (accidentally or maliciously) affect each +other's open files. Because of the way extensions are shared between +(sub-)interpreters, some extensions may not work properly; this is +especially likely when the extension makes use of (static) global +variables, or when the extension manipulates its module's dictionary +after its initialization. It is possible to insert objects created in +one sub-interpreter into a namespace of another sub-interpreter; this +should be done with great care to avoid sharing user-defined +functions, methods, instances or classes between sub-interpreters, +since import operations executed by such objects may affect the +wrong (sub-)interpreter's dictionary of loaded modules. (XXX This is +a hard-to-fix bug that will be addressed in a future release.) +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{Py_EndInterpreter}{PyThreadState *tstate} +Destroy the (sub-)interpreter represented by the given thread state. +The given thread state must be the current thread state. See the +discussion of thread states below. When the call returns, the current +thread state is \code{NULL}. All thread states associated with this +interpreted are destroyed. (The global interpreter lock must be held +before calling this function and is still held when it returns.) +\code{Py_Finalize()} will destroy all sub-interpreters that haven't +been explicitly destroyed at that point. +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{Py_SetProgramName}{char *name} +This function should be called before \code{Py_Initialize()} is called +for the first time, if it is called at all. It tells the interpreter +the value of the \code{argv[0]} argument to the \code{main()} function +of the program. This is used by \code{Py_GetPath()} and some other +functions below to find the Python run-time libraries relative to the +interpreter executable. The default value is \code{"python"}. The +argument should point to a zero-terminated character string in static +storage whose contents will not change for the duration of the +program's execution. No code in the Python interpreter will change +the contents of this storage. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetProgramName}{} +Return the program name set with \code{Py_SetProgramName()}, or the +default. The returned string points into static storage; the caller +should not modify its value. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetPrefix}{} +Return the ``prefix'' for installed platform-independent files. This +is derived through a number of complicated rules from the program name +set with \code{Py_SetProgramName()} and some environment variables; +for example, if the program name is \code{"/usr/local/bin/python"}, +the prefix is \code{"/usr/local"}. The returned string points into +static storage; the caller should not modify its value. This +corresponds to the \code{prefix} variable in the top-level +\code{Makefile} and the \code{--prefix} argument to the +\code{configure} script at build time. The value is available to +Python code as \code{sys.prefix}. It is only useful on Unix. See +also the next function. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetExecPrefix}{} +Return the ``exec-prefix'' for installed platform-\emph{de}pendent +files. This is derived through a number of complicated rules from the +program name set with \code{Py_SetProgramName()} and some environment +variables; for example, if the program name is +\code{"/usr/local/bin/python"}, the exec-prefix is +\code{"/usr/local"}. The returned string points into static storage; +the caller should not modify its value. This corresponds to the +\code{exec_prefix} variable in the top-level \code{Makefile} and the +\code{--exec_prefix} argument to the \code{configure} script at build +time. The value is available to Python code as +\code{sys.exec_prefix}. It is only useful on Unix. + +Background: The exec-prefix differs from the prefix when platform +dependent files (such as executables and shared libraries) are +installed in a different directory tree. In a typical installation, +platform dependent files may be installed in the +\code{"/usr/local/plat"} subtree while platform independent may be +installed in \code{"/usr/local"}. + +Generally speaking, a platform is a combination of hardware and +software families, e.g. Sparc machines running the Solaris 2.x +operating system are considered the same platform, but Intel machines +running Solaris 2.x are another platform, and Intel machines running +Linux are yet another platform. Different major revisions of the same +operating system generally also form different platforms. Non-Unix +operating systems are a different story; the installation strategies +on those systems are so different that the prefix and exec-prefix are +meaningless, and set to the empty string. Note that compiled Python +bytecode files are platform independent (but not independent from the +Python version by which they were compiled!). + +System administrators will know how to configure the \code{mount} or +\code{automount} programs to share \code{"/usr/local"} between platforms +while having \code{"/usr/local/plat"} be a different filesystem for each +platform. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetProgramFullPath}{} +Return the full program name of the Python executable; this is +computed as a side-effect of deriving the default module search path +from the program name (set by \code{Py_SetProgramName() above). The +returned string points into static storage; the caller should not +modify its value. The value is available to Python code as +\code{sys.executable}. % XXX is that the right sys.name? +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetPath}{} +Return the default module search path; this is computed from the +program name (set by \code{Py_SetProgramName() above) and some +environment variables. The returned string consists of a series of +directory names separated by a platform dependent delimiter character. +The delimiter character is \code{':'} on Unix, \code{';'} on +DOS/Windows, and \code{'\n'} (the ASCII newline character) on +Macintosh. The returned string points into static storage; the caller +should not modify its value. The value is available to Python code +as the list \code{sys.path}, which may be modified to change the +future search path for loaded modules. + +% XXX should give the exact rules +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetVersion}{} +Return the version of this Python interpreter. This is a string that +looks something like + +\code{"1.5a3 (#67, Aug 1 1997, 22:34:28) [GCC 2.7.2.2]"}. + +The first word (up to the first space character) is the current Python +version; the first three characters are the major and minor version +separated by a period. The returned string points into static storage; +the caller should not modify its value. The value is available to +Python code as the list \code{sys.version}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetPlatform}{} +Return the platform identifier for the current platform. On Unix, +this is formed from the ``official'' name of the operating system, +converted to lower case, followed by the major revision number; e.g., +for Solaris 2.x, which is also known as SunOS 5.x, the value is +\code{"sunos5"}. On Macintosh, it is \code{"mac"}. On Windows, it +is \code{"win"}. The returned string points into static storage; +the caller should not modify its value. The value is available to +Python code as \code{sys.platform}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetCopyright}{} +Return the official copyright string for the current Python version, +for example + +\code{"Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam"} + +The returned string points into static storage; the caller should not +modify its value. The value is available to Python code as the list +\code{sys.copyright}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetCompiler}{} +Return an indication of the compiler used to build the current Python +version, in square brackets, for example + +\code{"[GCC 2.7.2.2]"} + +The returned string points into static storage; the caller should not +modify its value. The value is available to Python code as part of +the variable \code{sys.version}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetBuildInfo}{} +Return information about the sequence number and build date and time +of the current Python interpreter instance, for example + +\code{"#67, Aug 1 1997, 22:34:28"} + +The returned string points into static storage; the caller should not +modify its value. The value is available to Python code as part of +the variable \code{sys.version}. +\end{cfuncdesc} + +\begin{cfuncdesc}{int}{PySys_SetArgv}{int argc, char **argv} +% XXX +\end{cfuncdesc} + +% XXX Other PySys thingies (doesn't really belong in this chapter) + +\section{Thread State and the Global Interpreter Lock} + +\begin{cfuncdesc}{void}{PyEval_AcquireLock}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_ReleaseLock}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_AcquireThread}{PyThreadState *tstate} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_ReleaseThread}{PyThreadState *tstate} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_RestoreThread}{PyThreadState *tstate} +\end{cfuncdesc} + +\begin{cfuncdesc}{PyThreadState *}{PyEval_SaveThread}{} +\end{cfuncdesc} + +% XXX These aren't really C functions! +\begin{cfuncdesc}{Py_BEGIN_ALLOW_THREADS}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{Py_BEGIN_END_THREADS}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{Py_BEGIN_XXX_THREADS}{} +\end{cfuncdesc} + + XXX To be done: PyObject, PyVarObject diff --git a/Doc/api/api.tex b/Doc/api/api.tex index 95b7b58..3a0ddb0 100644 --- a/Doc/api/api.tex +++ b/Doc/api/api.tex @@ -42,123 +42,123 @@ API functions in detail. The Application Programmer's Interface to Python gives C and C++ programmers access to the Python interpreter at a variety of levels. -There are two fundamentally different reasons for using the Python/C -API. (The API is equally usable from C++, but for brevity it is -generally referred to as the Python/C API.) The first reason is to -write ``extension modules'' for specific purposes; these are C modules -that extend the Python interpreter. This is probably the most common -use. The second reason is to use Python as a component in a larger -application; this technique is generally referred to as ``embedding'' +There are two fundamentally different reasons for using the Python/C +API. (The API is equally usable from C++, but for brevity it is +generally referred to as the Python/C API.) The first reason is to +write ``extension modules'' for specific purposes; these are C modules +that extend the Python interpreter. This is probably the most common +use. The second reason is to use Python as a component in a larger +application; this technique is generally referred to as ``embedding'' Python in an application. -Writing an extension module is a relatively well-understood process, -where a ``cookbook'' approach works well. There are several tools -that automate the process to some extent. While people have embedded -Python in other applications since its early existence, the process of -embedding Python is less straightforward that writing an extension. -Python 1.5 introduces a number of new API functions as well as some -changes to the build process that make embedding much simpler. +Writing an extension module is a relatively well-understood process, +where a ``cookbook'' approach works well. There are several tools +that automate the process to some extent. While people have embedded +Python in other applications since its early existence, the process of +embedding Python is less straightforward that writing an extension. +Python 1.5 introduces a number of new API functions as well as some +changes to the build process that make embedding much simpler. This manual describes the 1.5 state of affair (as of Python 1.5a3). % XXX Eventually, take the historical notes out -Many API functions are useful independent of whether you're embedding -or extending Python; moreover, most applications that embed Python -will need to provide a custom extension as well, so it's probably a -good idea to become familiar with writing an extension before +Many API functions are useful independent of whether you're embedding +or extending Python; moreover, most applications that embed Python +will need to provide a custom extension as well, so it's probably a +good idea to become familiar with writing an extension before attempting to embed Python in a real application. \section{Objects, Types and Reference Counts} -Most Python/C API functions have one or more arguments as well as a -return value of type \code{PyObject *}. This type is a pointer -(obviously!) to an opaque data type representing an arbitrary Python -object. Since all Python object types are treated the same way by the -Python language in most situations (e.g., assignments, scope rules, -and argument passing), it is only fitting that they should be +Most Python/C API functions have one or more arguments as well as a +return value of type \code{PyObject *}. This type is a pointer +(obviously!) to an opaque data type representing an arbitrary Python +object. Since all Python object types are treated the same way by the +Python language in most situations (e.g., assignments, scope rules, +and argument passing), it is only fitting that they should be represented by a single C type. All Python objects live on the heap: -you never declare an automatic or static variable of type -\code{PyObject}, only pointer variables of type \code{PyObject *} can +you never declare an automatic or static variable of type +\code{PyObject}, only pointer variables of type \code{PyObject *} can be declared. -All Python objects (even Python integers) have a ``type'' and a -``reference count''. An object's type determines what kind of object -it is (e.g., an integer, a list, or a user-defined function; there are -many more as explained in the Python Language Reference Manual). For -each of the well-known types there is a macro to check whether an -object is of that type; for instance, \code{PyList_Check(a)} is true +All Python objects (even Python integers) have a ``type'' and a +``reference count''. An object's type determines what kind of object +it is (e.g., an integer, a list, or a user-defined function; there are +many more as explained in the Python Language Reference Manual). For +each of the well-known types there is a macro to check whether an +object is of that type; for instance, \code{PyList_Check(a)} is true iff the object pointed to by \code{a} is a Python list. -The reference count is important only because today's computers have a -finite (and often severly limited) memory size; it counts how many -different places there are that have a reference to an object. Such a -place could be another object, or a global (or static) C variable, or -a local variable in some C function. When an object's reference count -becomes zero, the object is deallocated. If it contains references to -other objects, their reference count is decremented. Those other -objects may be deallocated in turn, if this decrement makes their -reference count become zero, and so on. (There's an obvious problem -with objects that reference each other here; for now, the solution is +The reference count is important only because today's computers have a +finite (and often severly limited) memory size; it counts how many +different places there are that have a reference to an object. Such a +place could be another object, or a global (or static) C variable, or +a local variable in some C function. When an object's reference count +becomes zero, the object is deallocated. If it contains references to +other objects, their reference count is decremented. Those other +objects may be deallocated in turn, if this decrement makes their +reference count become zero, and so on. (There's an obvious problem +with objects that reference each other here; for now, the solution is ``don't do that''.) -Reference counts are always manipulated explicitly. The normal way is -to use the macro \code{Py_INCREF(a)} to increment an object's -reference count by one, and \code{Py_DECREF(a)} to decrement it by -one. The latter macro is considerably more complex than the former, -since it must check whether the reference count becomes zero and then -cause the object's deallocator, which is a function pointer contained -in the object's type structure. The type-specific deallocator takes -care of decrementing the reference counts for other objects contained -in the object, and so on, if this is a compound object type such as a -list. There's no chance that the reference count can overflow; at -least as many bits are used to hold the reference count as there are -distinct memory locations in virtual memory (assuming -\code{sizeof(long) >= sizeof(char *)}). Thus, the reference count +Reference counts are always manipulated explicitly. The normal way is +to use the macro \code{Py_INCREF(a)} to increment an object's +reference count by one, and \code{Py_DECREF(a)} to decrement it by +one. The latter macro is considerably more complex than the former, +since it must check whether the reference count becomes zero and then +cause the object's deallocator, which is a function pointer contained +in the object's type structure. The type-specific deallocator takes +care of decrementing the reference counts for other objects contained +in the object, and so on, if this is a compound object type such as a +list. There's no chance that the reference count can overflow; at +least as many bits are used to hold the reference count as there are +distinct memory locations in virtual memory (assuming +\code{sizeof(long) >= sizeof(char *)}). Thus, the reference count increment is a simple operation. -It is not necessary to increment an object's reference count for every -local variable that contains a pointer to an object. In theory, the -oject's reference count goes up by one when the variable is made to -point to it and it goes down by one when the variable goes out of -scope. However, these two cancel each other out, so at the end the -reference count hasn't changed. The only real reason to use the -reference count is to prevent the object from being deallocated as -long as our variable is pointing to it. If we know that there is at -least one other reference to the object that lives at least as long as -our variable, there is no need to increment the reference count -temporarily. An important situation where this arises is in objects -that are passed as arguments to C functions in an extension module -that are called from Python; the call mechanism guarantees to hold a +It is not necessary to increment an object's reference count for every +local variable that contains a pointer to an object. In theory, the +oject's reference count goes up by one when the variable is made to +point to it and it goes down by one when the variable goes out of +scope. However, these two cancel each other out, so at the end the +reference count hasn't changed. The only real reason to use the +reference count is to prevent the object from being deallocated as +long as our variable is pointing to it. If we know that there is at +least one other reference to the object that lives at least as long as +our variable, there is no need to increment the reference count +temporarily. An important situation where this arises is in objects +that are passed as arguments to C functions in an extension module +that are called from Python; the call mechanism guarantees to hold a reference to every argument for the duration of the call. -However, a common pitfall is to extract an object from a list and -holding on to it for a while without incrementing its reference count. -Some other operation might conceivably remove the object from the -list, decrementing its reference count and possible deallocating it. -The real danger is that innocent-looking operations may invoke -arbitrary Python code which could do this; there is a code path which -allows control to flow back to the user from a \code{Py_DECREF()}, so +However, a common pitfall is to extract an object from a list and +holding on to it for a while without incrementing its reference count. +Some other operation might conceivably remove the object from the +list, decrementing its reference count and possible deallocating it. +The real danger is that innocent-looking operations may invoke +arbitrary Python code which could do this; there is a code path which +allows control to flow back to the user from a \code{Py_DECREF()}, so almost any operation is potentially dangerous. -A safe approach is to always use the generic operations (functions -whose name begins with \code{PyObject_}, \code{PyNumber_}, -\code{PySequence_} or \code{PyMapping_}). These operations always -increment the reference count of the object they return. This leaves -the caller with the responsibility to call \code{Py_DECREF()} when +A safe approach is to always use the generic operations (functions +whose name begins with \code{PyObject_}, \code{PyNumber_}, +\code{PySequence_} or \code{PyMapping_}). These operations always +increment the reference count of the object they return. This leaves +the caller with the responsibility to call \code{Py_DECREF()} when they are done with the result; this soon becomes second nature. -There are very few other data types that play a significant role in -the Python/C API; most are all simple C types such as \code{int}, -\code{long}, \code{double} and \code{char *}. A few structure types -are used to describe static tables used to list the functions exported -by a module or the data attributes of a new object type. These will +There are very few other data types that play a significant role in +the Python/C API; most are all simple C types such as \code{int}, +\code{long}, \code{double} and \code{char *}. A few structure types +are used to describe static tables used to list the functions exported +by a module or the data attributes of a new object type. These will be discussed together with the functions that use them. \section{Exceptions} -The Python programmer only needs to deal with exceptions if specific -error handling is required; unhandled exceptions are automatically -propagated to the caller, then to the caller's caller, and so on, till -they reach the top-level interpreter, where they are reported to the +The Python programmer only needs to deal with exceptions if specific +error handling is required; unhandled exceptions are automatically +propagated to the caller, then to the caller's caller, and so on, till +they reach the top-level interpreter, where they are reported to the user accompanied by a stack trace. For C programmers, however, error checking always has to be explicit. @@ -166,57 +166,63 @@ For C programmers, however, error checking always has to be explicit. \section{Embedding Python} -The one important task that only embedders of the Python interpreter -have to worry about is the initialization (and possibly the -finalization) of the Python interpreter. Most functionality of the -interpreter can only be used after the interpreter has been +The one important task that only embedders of the Python interpreter +have to worry about is the initialization (and possibly the +finalization) of the Python interpreter. Most functionality of the +interpreter can only be used after the interpreter has been initialized. - -The basic initialization function is \code{Py_Initialize()}. This -initializes the table of loaded modules, and creates the fundamental -modules \code{__builtin__}, \code{__main__} and \code{sys}. It also +The basic initialization function is \code{Py_Initialize()}. This +initializes the table of loaded modules, and creates the fundamental +modules \code{__builtin__}, \code{__main__} and \code{sys}. It also initializes the module search path (\code{sys.path}). -\code{Py_Initialize()} does not set the ``script argument list'' -(\code{sys.argv}). If this variable is needed by Python code that -will be executed later, it must be set explicitly with a call to -\code{PySys_SetArgv(\var{argc}, \var{argv})} subsequent to the call +\code{Py_Initialize()} does not set the ``script argument list'' +(\code{sys.argv}). If this variable is needed by Python code that +will be executed later, it must be set explicitly with a call to +\code{PySys_SetArgv(\var{argc}, \var{argv})} subsequent to the call to \code{Py_Initialize()}. -On Unix, \code{Py_Initialize()} calculates the module search path -based upon its best guess for the location of the standard Python -interpreter executable, assuming that the Python library is found in a -fixed location relative to the Python interpreter executable. In -particular, it looks for a directory named \code{lib/python1.5} -(replacing \code{1.5} with the current interpreter version) relative -to the parent directory where the executable named \code{python} is -found on the shell command search path (the environment variable -\code{$PATH}). For instance, if the Python executable is found in -\code{/usr/local/bin/python}, it will assume that the libraries are in -\code{/usr/local/lib/python1.5}. In fact, this also the ``fallback'' -location, used when no executable file named \code{python} is found -along \code{\$PATH}. The user can change this behavior by setting the -environment variable \code{\$PYTHONHOME}, and can insert additional -directories in front of the standard path by setting +On Unix, \code{Py_Initialize()} calculates the module search path +based upon its best guess for the location of the standard Python +interpreter executable, assuming that the Python library is found in a +fixed location relative to the Python interpreter executable. In +particular, it looks for a directory named \code{lib/python1.5} +(replacing \code{1.5} with the current interpreter version) relative +to the parent directory where the executable named \code{python} is +found on the shell command search path (the environment variable +\code{$PATH}). For instance, if the Python executable is found in +\code{/usr/local/bin/python}, it will assume that the libraries are in +\code{/usr/local/lib/python1.5}. In fact, this also the ``fallback'' +location, used when no executable file named \code{python} is found +along \code{\$PATH}. The user can change this behavior by setting the +environment variable \code{\$PYTHONHOME}, and can insert additional +directories in front of the standard path by setting \code{\$PYTHONPATH}. -The embedding application can steer the search by calling -\code{Py_SetProgramName(\var{file})} \emph{before} calling -\code{Py_Initialize()}. Note that \code[$PYTHONHOME} still overrides -this and \code{\$PYTHONPATH} is still inserted in front of the +The embedding application can steer the search by calling +\code{Py_SetProgramName(\var{file})} \emph{before} calling +\code{Py_Initialize()}. Note that \code[$PYTHONHOME} still overrides +this and \code{\$PYTHONPATH} is still inserted in front of the standard path. -Sometimes, it is desirable to ``uninitialize'' Python. For instance, -the application may want to start over (make another call to -\code{Py_Initialize()}) or the application is simply done with its -use of Python and wants to free all memory allocated by Python. This +Sometimes, it is desirable to ``uninitialize'' Python. For instance, +the application may want to start over (make another call to +\code{Py_Initialize()}) or the application is simply done with its +use of Python and wants to free all memory allocated by Python. This can be accomplished by calling \code{Py_Finalize()}. % XXX More... \section{Embedding Python in Threaded Applications} -%XXX more here + + + + + + + + \chapter{Old Introduction} @@ -1258,6 +1264,308 @@ e.g. to check that an object is a dictionary, use \begin{cfuncdesc}{TYPE}{_PyObject_NEW_VAR}{TYPE, PyTypeObject *, int size} \end{cfuncdesc} +\chapter{Initialization, Finalization, and Threads} + +% XXX Check argument/return type of all these + +\begin{cfuncdesc}{void}{Py_Initialize}{} +Initialize the Python interpreter. In an application embedding +Python, this should be called before using any other Python/C API +functions; with the exception of \code{Py_SetProgramName()}, +\code{PyEval_InitThreads()}, \code{PyEval_ReleaseLock()}, and +\code{PyEval_AcquireLock()}. This initializes the table of loaded +modules (\code{sys.modules}), and creates the fundamental modules +\code{__builtin__}, \code{__main__} and \code{sys}. It also +initializes the module search path (\code{sys.path}). It does not set +\code{sys.argv}; use \code{PySys_SetArgv()} for that. It is a fatal +error to call it for a second time without calling +\code{Py_Finalize()} first. There is no return value; it is a fatal +error if the initialization fails. +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{Py_Finalize}{} +Undo all initializations made by \code{Py_Initialize()} and subsequent +use of Python/C API functions, and destroy all sub-interpreters (see +\code{Py_NewInterpreter()} below) that were created and not yet +destroyed since the last call to \code{Py_Initialize()}. Ideally, +this frees all memory allocated by the Python interpreter. It is a +fatal error to call it for a second time without calling +\code{Py_Initialize()} again first. There is no return value; errors +during finalization are ignored. + +This function is provided for a number of reasons. An embedding +application might want to restart Python without having to restart the +application itself. An application that has loaded the Python +interpreter from a dynamically loadable library (or DLL) might want to +free all memory allocated by Python before unloading the DLL. During a +hunt for memory leaks in an application a developer might want to free +all memory allocated by Python before exiting from the application. + +\emph{Bugs and caveats:} The destruction of modules and objects in +modules is done in random order; this may cause destructors +(\code{__del__} methods) to fail when they depend on other objects +(even functions) or modules. Dynamically loaded extension modules +loaded by Python are not unloaded. Small amounts of memory allocated +by the Python interpreter may not be freed (if you find a leak, please +report it). Memory tied up in circular references between objects is +not freed. Some memory allocated by extension modules may not be +freed. Some extension may not work properly if their initialization +routine is called more than once; this can happen if an applcation +calls \code{Py_Initialize()} and \code{Py_Finalize()} more than once. +\end{cfuncdesc} + +\begin{cfuncdesc}{PyThreadState *}{Py_NewInterpreter}{} +Create a new sub-interpreter. This is an (almost) totally separate +environment for the execution of Python code. In particular, the new +interpreter has separate, independent versions of all imported +modules, including the fundamental modules \code{__builtin__}, +\code{__main__} and \code{sys}. The table of loaded modules +(\code{sys.modules}) and the module search path (\code{sys.path}) are +also separate. The new environment has no \code{sys.argv} variable. +It has new standard I/O stream file objects \code{sys.stdin}, +\code{sys.stdout} and \code{sys.stderr} (however these refer to the +same underlying \code{FILE} structures in the C library). + +The return value points to the first thread state created in the new +sub-interpreter. This thread state is made the current thread state. +Note that no actual thread is created; see the discussion of thread +states below. If creation of the new interpreter is unsuccessful, +\code{NULL} is returned; no exception is set since the exception state +is stored in the current thread state and there may not be a current +thread state. (Like all other Python/C API functions, the global +interpreter lock must be held before calling this function and is +still held when it returns; however, unlike most other Python/C API +functions, there needn't be a current thread state on entry.) + +Extension modules are shared between (sub-)interpreters as follows: +the first time a particular extension is imported, it is initialized +normally, and a (shallow) copy of its module's dictionary is +squirreled away. When the same extension is imported by another +(sub-)interpreter, a new module is initialized and filled with the +contents of this copy; the extension's \code{init} function is not +called. Note that this is different from what happens when as +extension is imported after the interpreter has been completely +re-initialized by calling \code{Py_Finalize()} and +\code{Py_Initialize()}; in that case, the extension's \code{init} +function \emph{is} called again. + +\emph{Bugs and caveats:} Because sub-interpreters (and the main +interpreter) are part of the same process, the insulation between them +isn't perfect -- for example, using low-level file operations like +\code{os.close()} they can (accidentally or maliciously) affect each +other's open files. Because of the way extensions are shared between +(sub-)interpreters, some extensions may not work properly; this is +especially likely when the extension makes use of (static) global +variables, or when the extension manipulates its module's dictionary +after its initialization. It is possible to insert objects created in +one sub-interpreter into a namespace of another sub-interpreter; this +should be done with great care to avoid sharing user-defined +functions, methods, instances or classes between sub-interpreters, +since import operations executed by such objects may affect the +wrong (sub-)interpreter's dictionary of loaded modules. (XXX This is +a hard-to-fix bug that will be addressed in a future release.) +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{Py_EndInterpreter}{PyThreadState *tstate} +Destroy the (sub-)interpreter represented by the given thread state. +The given thread state must be the current thread state. See the +discussion of thread states below. When the call returns, the current +thread state is \code{NULL}. All thread states associated with this +interpreted are destroyed. (The global interpreter lock must be held +before calling this function and is still held when it returns.) +\code{Py_Finalize()} will destroy all sub-interpreters that haven't +been explicitly destroyed at that point. +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{Py_SetProgramName}{char *name} +This function should be called before \code{Py_Initialize()} is called +for the first time, if it is called at all. It tells the interpreter +the value of the \code{argv[0]} argument to the \code{main()} function +of the program. This is used by \code{Py_GetPath()} and some other +functions below to find the Python run-time libraries relative to the +interpreter executable. The default value is \code{"python"}. The +argument should point to a zero-terminated character string in static +storage whose contents will not change for the duration of the +program's execution. No code in the Python interpreter will change +the contents of this storage. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetProgramName}{} +Return the program name set with \code{Py_SetProgramName()}, or the +default. The returned string points into static storage; the caller +should not modify its value. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetPrefix}{} +Return the ``prefix'' for installed platform-independent files. This +is derived through a number of complicated rules from the program name +set with \code{Py_SetProgramName()} and some environment variables; +for example, if the program name is \code{"/usr/local/bin/python"}, +the prefix is \code{"/usr/local"}. The returned string points into +static storage; the caller should not modify its value. This +corresponds to the \code{prefix} variable in the top-level +\code{Makefile} and the \code{--prefix} argument to the +\code{configure} script at build time. The value is available to +Python code as \code{sys.prefix}. It is only useful on Unix. See +also the next function. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetExecPrefix}{} +Return the ``exec-prefix'' for installed platform-\emph{de}pendent +files. This is derived through a number of complicated rules from the +program name set with \code{Py_SetProgramName()} and some environment +variables; for example, if the program name is +\code{"/usr/local/bin/python"}, the exec-prefix is +\code{"/usr/local"}. The returned string points into static storage; +the caller should not modify its value. This corresponds to the +\code{exec_prefix} variable in the top-level \code{Makefile} and the +\code{--exec_prefix} argument to the \code{configure} script at build +time. The value is available to Python code as +\code{sys.exec_prefix}. It is only useful on Unix. + +Background: The exec-prefix differs from the prefix when platform +dependent files (such as executables and shared libraries) are +installed in a different directory tree. In a typical installation, +platform dependent files may be installed in the +\code{"/usr/local/plat"} subtree while platform independent may be +installed in \code{"/usr/local"}. + +Generally speaking, a platform is a combination of hardware and +software families, e.g. Sparc machines running the Solaris 2.x +operating system are considered the same platform, but Intel machines +running Solaris 2.x are another platform, and Intel machines running +Linux are yet another platform. Different major revisions of the same +operating system generally also form different platforms. Non-Unix +operating systems are a different story; the installation strategies +on those systems are so different that the prefix and exec-prefix are +meaningless, and set to the empty string. Note that compiled Python +bytecode files are platform independent (but not independent from the +Python version by which they were compiled!). + +System administrators will know how to configure the \code{mount} or +\code{automount} programs to share \code{"/usr/local"} between platforms +while having \code{"/usr/local/plat"} be a different filesystem for each +platform. +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetProgramFullPath}{} +Return the full program name of the Python executable; this is +computed as a side-effect of deriving the default module search path +from the program name (set by \code{Py_SetProgramName() above). The +returned string points into static storage; the caller should not +modify its value. The value is available to Python code as +\code{sys.executable}. % XXX is that the right sys.name? +\end{cfuncdesc} + +\begin{cfuncdesc}{char *}{Py_GetPath}{} +Return the default module search path; this is computed from the +program name (set by \code{Py_SetProgramName() above) and some +environment variables. The returned string consists of a series of +directory names separated by a platform dependent delimiter character. +The delimiter character is \code{':'} on Unix, \code{';'} on +DOS/Windows, and \code{'\n'} (the ASCII newline character) on +Macintosh. The returned string points into static storage; the caller +should not modify its value. The value is available to Python code +as the list \code{sys.path}, which may be modified to change the +future search path for loaded modules. + +% XXX should give the exact rules +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetVersion}{} +Return the version of this Python interpreter. This is a string that +looks something like + +\code{"1.5a3 (#67, Aug 1 1997, 22:34:28) [GCC 2.7.2.2]"}. + +The first word (up to the first space character) is the current Python +version; the first three characters are the major and minor version +separated by a period. The returned string points into static storage; +the caller should not modify its value. The value is available to +Python code as the list \code{sys.version}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetPlatform}{} +Return the platform identifier for the current platform. On Unix, +this is formed from the ``official'' name of the operating system, +converted to lower case, followed by the major revision number; e.g., +for Solaris 2.x, which is also known as SunOS 5.x, the value is +\code{"sunos5"}. On Macintosh, it is \code{"mac"}. On Windows, it +is \code{"win"}. The returned string points into static storage; +the caller should not modify its value. The value is available to +Python code as \code{sys.platform}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetCopyright}{} +Return the official copyright string for the current Python version, +for example + +\code{"Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam"} + +The returned string points into static storage; the caller should not +modify its value. The value is available to Python code as the list +\code{sys.copyright}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetCompiler}{} +Return an indication of the compiler used to build the current Python +version, in square brackets, for example + +\code{"[GCC 2.7.2.2]"} + +The returned string points into static storage; the caller should not +modify its value. The value is available to Python code as part of +the variable \code{sys.version}. +\end{cfuncdesc} + +\begin{cfuncdesc}{const char *}{Py_GetBuildInfo}{} +Return information about the sequence number and build date and time +of the current Python interpreter instance, for example + +\code{"#67, Aug 1 1997, 22:34:28"} + +The returned string points into static storage; the caller should not +modify its value. The value is available to Python code as part of +the variable \code{sys.version}. +\end{cfuncdesc} + +\begin{cfuncdesc}{int}{PySys_SetArgv}{int argc, char **argv} +% XXX +\end{cfuncdesc} + +% XXX Other PySys thingies (doesn't really belong in this chapter) + +\section{Thread State and the Global Interpreter Lock} + +\begin{cfuncdesc}{void}{PyEval_AcquireLock}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_ReleaseLock}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_AcquireThread}{PyThreadState *tstate} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_ReleaseThread}{PyThreadState *tstate} +\end{cfuncdesc} + +\begin{cfuncdesc}{void}{PyEval_RestoreThread}{PyThreadState *tstate} +\end{cfuncdesc} + +\begin{cfuncdesc}{PyThreadState *}{PyEval_SaveThread}{} +\end{cfuncdesc} + +% XXX These aren't really C functions! +\begin{cfuncdesc}{Py_BEGIN_ALLOW_THREADS}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{Py_BEGIN_END_THREADS}{} +\end{cfuncdesc} + +\begin{cfuncdesc}{Py_BEGIN_XXX_THREADS}{} +\end{cfuncdesc} + + XXX To be done: PyObject, PyVarObject -- cgit v0.12