[Python-checkins] r87792 - in python/branches/py3k/Doc: glossary.rst library/threading.rst

[antoine.pitrou]

Author: antoine.pitrou
Date: Thu Jan  6 17:31:28 2011
New Revision: 87792

Log:
Elaborate about the GIL.



Modified:
   python/branches/py3k/Doc/glossary.rst
   python/branches/py3k/Doc/library/threading.rst

Modified: python/branches/py3k/Doc/glossary.rst
==============================================================================
--- python/branches/py3k/Doc/glossary.rst	(original)
+++ python/branches/py3k/Doc/glossary.rst	Thu Jan  6 17:31:28 2011
@@ -102,9 +102,10 @@
       See :pep:`343`.
 
    CPython
-      The canonical implementation of the Python programming language.  The
-      term "CPython" is used in contexts when necessary to distinguish this
-      implementation from others such as Jython or IronPython.
+      The canonical implementation of the Python programming language, as
+      distributed on `python.org <http://python.org>`_.  The term "CPython"
+      is used when necessary to distinguish this implementation from others
+      such as Jython or IronPython.
 
    decorator
       A function returning another function, usually applied as a function
@@ -263,16 +264,25 @@
       See :term:`global interpreter lock`.
 
    global interpreter lock
-      The lock used by Python threads to assure that only one thread
-      executes in the :term:`CPython` :term:`virtual machine` at a time.
-      This simplifies the CPython implementation by assuring that no two
-      processes can access the same memory at the same time.  Locking the
-      entire interpreter makes it easier for the interpreter to be
-      multi-threaded, at the expense of much of the parallelism afforded by
-      multi-processor machines.  Efforts have been made in the past to
-      create a "free-threaded" interpreter (one which locks shared data at a
-      much finer granularity), but so far none have been successful because
-      performance suffered in the common single-processor case.
+      The mechanism used by the :term:`CPython` interpreter to assure that
+      only one thread executes Python :term:`bytecode` at a time.
+      This simplifies the CPython implementation by making the object model
+      (including critical built-in types such as :class:`dict`) implicitly
+      safe against concurrent access.  Locking the entire interpreter
+      makes it easier for the interpreter to be multi-threaded, at the
+      expense of much of the parallelism afforded by multi-processor
+      machines.
+
+      However, some extension modules, either standard or third-party,
+      are designed so as to release the GIL when doing computationally-intensive
+      tasks such as compression or hashing.  Also, the GIL is always released
+      when doing I/O.
+
+      Past efforts to create a "free-threaded" interpreter (one which locks
+      shared data at a much finer granularity) have not been successful
+      because performance suffered in the common single-processor case. It
+      is believed that overcoming this performance issue would make the
+      implementation much more complicated and therefore costlier to maintain.
 
    hashable
       An object is *hashable* if it has a hash value which never changes during

Modified: python/branches/py3k/Doc/library/threading.rst
==============================================================================
--- python/branches/py3k/Doc/library/threading.rst	(original)
+++ python/branches/py3k/Doc/library/threading.rst	Thu Jan  6 17:31:28 2011
@@ -17,11 +17,23 @@
    methods and functions in this module in the Python 2.x series are still
    supported by this module.
 
+.. impl-detail::
+
+   Due to the :term:`Global Interpreter Lock`, in CPython only one thread
+   can execute Python code at once (even though certain performance-oriented
+   libraries might overcome this limitation).
+   If you want your application to make better of use of the computational
+   resources of multi-core machines, you are advised to use
+   :mod:`multiprocessing` or :class:`concurrent.futures.ProcessPoolExecutor`.
+   However, threading is still an appropriate model if you want to run
+   multiple I/O-bound tasks simultaneously.
+
 .. seealso::
 
    Latest version of the :source:`threading module Python source code
    <Lib/threading.py>`
 
+
 This module defines the following functions and objects: