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				</prE>

				<p>The returned string points into static storage; the caller should not modify its value. The value is available to Python code as the list <tt cLass="monofont">sys.copyright.</TT></P>

				<Pre>
					
const char* Py_GetCompiler()

				</prE>

				<P>Returns an indication of the compiler used to build the current Python version, in square brackets; for example</P>

				<Pre>
					
"[GCC 2.7.2.2]"

				</prE>

				<P>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 <TT clasS="monofont">sys.version.</TT></P>

				<pre>
					
const char* Py_GetBuildInfo()

				</pre>

				<p>Return information about the sequence number and build date and time of the current Python interpreter instance; for example</p>

				<pre>
					
"#67, Aug 1 1997, 22:34:28"

				</pre>

				<p>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 <tt claSs="monofont">sys.version.</tT></p>

				<prE>
					
int PySys_SetArgv(int argc, char **argv)

				</pre>

				<p>Sets <Tt clASS="monofont">sys.argv</Tt> based on <tt cLASS="monofont">argc</tt> and <tt CLASs="monofont">argv.</tt> These parameters are similar to those passed to the program's <tT CLAss="monofont">main()</tt> function with the difference that the first entry should refer to the script file to be executed rather than the executable hosting the Python interpreter. If there isn't a script that will be run, the first entry in <tt class="monofont">argv</tt> can be an empty string. If this function fails to initialize <tt class="monofont">sys.argv,</Tt> a fatal condition is signaled using <tT claSs="monofont">Py_FatalError().</tt></p>

				<H4>Thread State and the Global Interpreter Lock</h4>
					<p>The Python interpreter is not fully thread safe. In order to <a NAME="idx1073751266"></a><a naME="idx1073751267"></A><A name="idx1073751268"></A><A NAme="idx1073751269"></a><a NAME="idx1073751270"></a>support multithreaded Python programs, a global lock must be held by the current thread before it can safely access Python objects. Without the lock, even the simplest operations could cause problems in a multithreaded program: for example, when two threads simultaneously increment the reference count of the same object, the reference count could end up being incremented only once instead of twice.</p>

					<p>Therefore, the rule exists that only the thread that has acquired the global interpreter lock can operate on Python objects or call Python/C API functions. In order to support multithreaded Python programs, the interpreter regularly releases and reacquires the lock梑y default, every ten bytecode instructions (this can be changed with <tt class="monofont">sys.setcheckinterval()</tt>). The lock is also released and reacquired around potentially blocking I/O operations such as reading or writing a file, so other threads can run while the thread that requests the I/O is waiting for the I/O operation to complete.</p>

					<p>The Python interpreter needs to keep some bookkeeping information separate per thread梖or this it uses a data structure called PyThreadState. This is new in Python 1.5; in earlier versions, such a state was stored in global variables, and switching threads could cause problems. In particular, exception handling is now thread safe when the application uses <a name="idx1073751271"></a><A naMe="idx1073751272"></a><tT clasS="monofont">sys.exc_info()</tt> to access the exception last raised in the current thread.</p>

					<P>There's one global variable left, however: the pointer to the current PyThreadState structure. Although most thread packages have a way to store per-thread global data, Python's internal platform independent thread abstraction doesn't support this yet. Therefore, the current thread state must be manipulated explicitly.</P>

					<P>This is easy enough in most cases. Most code manipulating the global interpreter lock has the following simple structure:</P>

					<pre>
						
Save the thread state in a local variable.
Release the interpreter lock.
...Do some blocking I/O operation...
Reacquire the interpreter lock.
Restore the thread state from the local variable.

					</pRE>

					<P>This is so common that a pair of macros exists to simplify it:</P>

					<pre>
						
Py_BEGIN_ALLOW_THREADS
...Do some blocking I/O operation...
Py_END_ALLOW_THREADS

					</pRE>

					<P>The <Tt claSS="monofont">Py_BEGIN_ALLOW_THREADS</TT> macro opens a new block and declares a hidden local variable; the <tt class="monofont">Py_END_ALLOW_THREADS</tt> macro closes the block. Another advantage of using these two macros is that when Python is compiled without thread support, they are defined empty, thus saving the thread state and lock manipulations.</p>

					<p>When thread support is enabled, the previous block expands to the following code:</p>

					<pre>
						
PyThreadState *_save;
_save = PyEval_SaveThread();
...Do some blocking I/O operation...
    PyEval_RestoreThread(_save);

					</pre>

					<p>Using even lower level primitives, we can get roughly the same effect as follows:</p>

					<Pre>
						
PyThreadState *_save;
_save = PyThreadState_Swap(NULL);
PyEval_ReleaseLock();
...Do some blocking I/O operation...
PyEval_AcquireLock();
PyThreadState_Swap(_save);

					</Pre>

					<p>There are some subtle differences; in particular, <Tt claSs="monofont">PyEval_RestoreThread()</tt> saves and restores the value of the global variable <TT CLass="monofont">errno</tT> because the lock manipulation does not guarantee that <TT Class="monofont">errno</TT> is left alone. Also, when thread support is disabled, <TT clasS="monofont">PyEval_SaveThread()</TT> and <Tt class="monofont">PyEval_RestoreThread()</tt> don't manipulate the lock; in this case, <tt class="monofont">PyEval_ReleaseLock()</tt> and <tt cLasS="monofont">PyEval_AcquireLock()</tt> are not available. This is done so that dynamically loaded extensions compiled with thread support enabled can be loaded by an interpreter that was compiled with disabled thread support.</p>

					<P>The global interpreter lock is used to protect the pointer to the current thread state. When releasing the lock and saving the thread state, the current thread state pointer must be retrieved before the lock is released because another thread could immediately acquire the lock and store its own thread state in the global variable. Conversely, when acquiring the lock and restoring the thread state, the lock must be acquired before storing the thread state pointer.</p>

					<p>Why so much detail about this? Because when threads are created from C, they don't have the global interpreter lock, nor is there a thread state data structure for them. Such threads must bootstrap themselves into existence, by first creating a thread state data structure, acquiring the lock, and finally storing their thread state pointer, before they can start using the Python/C API. When they are done, they should reset the thread state pointer, release the lock, and finally free their thread state data structure.</p>

					<p>When <A namE="idx1073751273"></A><A Name="idx1073751274"></a><A NAMe="idx1073751275"></a><a nAME="idx1073751276"></A>creating a thread data structure, you need to provide an interpreter state data structure. The interpreter state data structure holds global data that is shared by all threads in an interpreter, for example the module administration (<tt clASS="monofont">sys.modules</Tt>). Depending on your needs, you can either create a new interpreter state data structure, or share the interpreter state data structure used by the Python main thread (to access the latter, you must obtain the thread state and access its interp member; this must be done by a thread that is created by Python or by the main thread after Python is initialized).</p>

					<pre>
						
PyInterpreterState

					</pre>

					<p>This data structure represents the state shared by a number of cooperating threads. Threads belonging to the same interpreter share their module administration and a few other internal items. There are no public members in this structure.</p>

					<p>Threads belonging to different interpreters initially share nothing, except process state like available memory, open file descriptors and such. The global interpreter lock is also shared by all threads, regardless of to which interpreter they belong.</p>

					<pre>
						
PyThreadState

					</pre>

					<p>This data structure represents the state of a single thread. The only public data member is PyInterpreterState *interp, which points to this thread's interpreter state.</p>

					<Pre>
						
void PyEval_InitThreads()

					</Pre>

					<p>Initialize and acquire the global interpreter lock. It should be called in the main thread before creating a second thread or engaging in any other thread operations such as <Tt claSs="monofont">PyEval_ReleaseLock()</tt> or <TT CLass="monofont">PyEval_ReleaseThread(tstate).</tT> It is not needed before calling <TT Class="monofont">PyEval_SaveThread()</TT> or <TT clasS="monofont">PyEval_RestoreThread().</TT></P>

					<p>This is a no-op when called for a second time. It is safe to call this function before calling <tt class="monofont">Py_Initialize().</tt></p>

					<p>When only the main thread exists, no lock operations are needed. This is a common situation (most Python programs do not use threads), and the lock operations slow the interpreter down a bit. Therefore, the lock is not created initially. This situation is equivalent to having acquired the lock: When there is only a single thread, all object accesses are safe. Therefore, when this function initializes the lock, it also acquires it. Before the Python thread module creates a new thread, knowing that either it has the lock or the lock hasn't been created yet, it calls <tt class="monofont">PyEval_InitThreads().</tT> When this call returns, it is guaranteed that the lock has been created and that it has acquired it.</p>

					<p>It is not safe to call this function when it is unknown which thread (if any) currently has the global interpreter lock.</P>

					<p>This function is not available when thread support is disabled at compile time.</p>

					<pRe>
						
void PyEval_AcquireLock()

					</pre>

					<P>Acquires the global interpreter lock. The lock must have been created earlier. If this thread already has the lock, a deadlock ensues. This function is not available when thread support is disabled at compile time.</p>

					<prE>
						
void PyEval_ReleaseLock()

					</PRE>

					<p>Releases the global interpreter lock. The lock must have been created earlier. This function is not available when thread support is disabled at compile time.</p>

					<prE>
						
void PyEval_AcquireThread(PyThreadState *tstate)

					</PRE>

					<p>Acquires the global interpreter lock and then sets the current thread state to <tt cLASS="monofont">tstate,</tt> which should not be <tt CLASs="monofont">NULL.</tt> The lock must have been created earlier. If this thread already has the lock, deadlock ensues. This function is not available when thread support is disabled at compile time.</p>