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.
Bugs and caveats: The destruction of modules and objects in modules is done in random order; this may cause destructors (__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 Py_Initialize() and Py_Finalize() more than once.
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, 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 init function is not called. Note that this is different from what happens when an extension is imported after the interpreter has been completely re-initialized by calling Py_Finalize() and Py_Initialize(); in that case, the extension's init function is called again.
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 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.)
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 "/usr/local/plat" subtree while platform independent may be installed in "/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 mount or automount programs to share "/usr/local" between platforms while having "/usr/local/plat" be a different filesystem for each platform.
"1.5 (#67, Dec 31 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 sys.version.
"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 sys.copyright.
"[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 sys.version.
"#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 sys.version.
guido@python.org