--- rest25/tutorial/stdlib2.rst	2008-12-19 16:58:06.000000000 +0900
+++ rest262/tutorial/stdlib2.rst	2009-04-05 05:01:50.000000000 +0900
@@ -4,89 +4,85 @@
 Brief Tour of the Standard Library -- Part II
 *********************************************
 
 This second tour covers more advanced modules that support professional
 programming needs.  These modules rarely occur in small scripts.
 
 
 .. _tut-output-formatting:
 
 Output Formatting
 =================
 
-The :mod:`repr` (XXX reference: ../lib/module-repr.html) module provides a
-version of :func:`repr` customized for abbreviated displays of large or deeply
-nested containers::
+The :mod:`repr` module provides a version of :func:`repr` customized for
+abbreviated displays of large or deeply nested containers::
 
-   >>> import repr   
+   >>> import repr
    >>> repr.repr(set('supercalifragilisticexpialidocious'))
    "set(['a', 'c', 'd', 'e', 'f', 'g', ...])"
 
-The :mod:`pprint` (XXX reference: ../lib/module-pprint.html) module offers more
-sophisticated control over printing both built-in and user defined objects in a
-way that is readable by the interpreter.  When the result is longer than one
-line, the "pretty printer" adds line breaks and indentation to more clearly
-reveal data structure::
+The :mod:`pprint` module offers more sophisticated control over printing both
+built-in and user defined objects in a way that is readable by the interpreter.
+When the result is longer than one line, the "pretty printer" adds line breaks
+and indentation to more clearly reveal data structure::
 
    >>> import pprint
    >>> t = [[[['black', 'cyan'], 'white', ['green', 'red']], [['magenta',
    ...     'yellow'], 'blue']]]
    ...
    >>> pprint.pprint(t, width=30)
    [[[['black', 'cyan'],
       'white',
       ['green', 'red']],
      [['magenta', 'yellow'],
       'blue']]]
 
-The :mod:`textwrap` (XXX reference: ../lib/module-textwrap.html) module formats
-paragraphs of text to fit a given screen width::
+The :mod:`textwrap` module formats paragraphs of text to fit a given screen
+width::
 
    >>> import textwrap
    >>> doc = """The wrap() method is just like fill() except that it returns
    ... a list of strings instead of one big string with newlines to separate
    ... the wrapped lines."""
    ...
    >>> print textwrap.fill(doc, width=40)
    The wrap() method is just like fill()
    except that it returns a list of strings
    instead of one big string with newlines
    to separate the wrapped lines.
 
-The :mod:`locale` (XXX reference: ../lib/module-locale.html) module accesses a
-database of culture specific data formats.  The grouping attribute of locale's
-format function provides a direct way of formatting numbers with group
-separators::
+The :mod:`locale` module accesses a database of culture specific data formats.
+The grouping attribute of locale's format function provides a direct way of
+formatting numbers with group separators::
 
    >>> import locale
    >>> locale.setlocale(locale.LC_ALL, 'English_United States.1252')
    'English_United States.1252'
    >>> conv = locale.localeconv()          # get a mapping of conventions
    >>> x = 1234567.8
    >>> locale.format("%d", x, grouping=True)
    '1,234,567'
    >>> locale.format("%s%.*f", (conv['currency_symbol'],
-   ...	      conv['frac_digits'], x), grouping=True)
+   ...               conv['frac_digits'], x), grouping=True)
    '$1,234,567.80'
 
 
 .. _tut-templating:
 
 Templating
 ==========
 
-The :mod:`string` (XXX reference: ../lib/module-string.html) module includes a
-versatile :class:`Template` class with a simplified syntax suitable for editing
-by end-users.  This allows users to customize their applications without having
-to alter the application.
+The :mod:`string` module includes a versatile :class:`Template` class with a
+simplified syntax suitable for editing by end-users.  This allows users to
+customize their applications without having to alter the application.
 
 The format uses placeholder names formed by ``$`` with valid Python identifiers
 (alphanumeric characters and underscores).  Surrounding the placeholder with
 braces allows it to be followed by more alphanumeric letters with no intervening
 spaces.  Writing ``$$`` creates a single escaped ``$``::
 
    >>> from string import Template
    >>> t = Template('${village}folk send $$10 to $cause.')
    >>> t.substitute(village='Nottingham', cause='the ditch fund')
    'Nottinghamfolk send $10 to the ditch fund.'
 
 The :meth:`substitute` method raises a :exc:`KeyError` when a placeholder is not
@@ -111,120 +107,118 @@
    >>> import time, os.path
    >>> photofiles = ['img_1074.jpg', 'img_1076.jpg', 'img_1077.jpg']
    >>> class BatchRename(Template):
    ...     delimiter = '%'
    >>> fmt = raw_input('Enter rename style (%d-date %n-seqnum %f-format):  ')
    Enter rename style (%d-date %n-seqnum %f-format):  Ashley_%n%f
 
    >>> t = BatchRename(fmt)
    >>> date = time.strftime('%d%b%y')
    >>> for i, filename in enumerate(photofiles):
    ...     base, ext = os.path.splitext(filename)
    ...     newname = t.substitute(d=date, n=i, f=ext)
-   ...     print '%s --> %s' % (filename, newname)
+   ...     print '{0} --> {1}'.format(filename, newname)
 
    img_1074.jpg --> Ashley_0.jpg
    img_1076.jpg --> Ashley_1.jpg
    img_1077.jpg --> Ashley_2.jpg
 
 Another application for templating is separating program logic from the details
 of multiple output formats.  This makes it possible to substitute custom
 templates for XML files, plain text reports, and HTML web reports.
 
 
 .. _tut-binary-formats:
 
 Working with Binary Data Record Layouts
 =======================================
 
-The :mod:`struct` (XXX reference: ../lib/module-struct.html) module provides
-:func:`pack` and :func:`unpack` functions for working with variable length
-binary record formats.  The following example shows how to loop through header
-information in a ZIP file (with pack codes ``"H"`` and ``"L"`` representing two
-and four byte unsigned numbers respectively)::
+The :mod:`struct` module provides :func:`pack` and :func:`unpack` functions for
+working with variable length binary record formats.  The following example shows
+how to loop through header information in a ZIP file without using the
+:mod:`zipfile` module.  Pack codes ``"H"`` and ``"I"`` represent two and four
+byte unsigned numbers respectively.  The ``"<"`` indicates that they are
+standard size and in little-endian byte order::
 
    import struct
 
    data = open('myfile.zip', 'rb').read()
    start = 0
    for i in range(3):                      # show the first 3 file headers
        start += 14
-       fields = struct.unpack('LLLHH', data[start:start+16])
+       fields = struct.unpack('<IIIHH', data[start:start+16])
        crc32, comp_size, uncomp_size, filenamesize, extra_size = fields
 
        start += 16
        filename = data[start:start+filenamesize]
        start += filenamesize
        extra = data[start:start+extra_size]
        print filename, hex(crc32), comp_size, uncomp_size
 
        start += extra_size + comp_size     # skip to the next header
 
 
 .. _tut-multi-threading:
 
 Multi-threading
 ===============
 
 Threading is a technique for decoupling tasks which are not sequentially
 dependent.  Threads can be used to improve the responsiveness of applications
 that accept user input while other tasks run in the background.  A related use
 case is running I/O in parallel with computations in another thread.
 
-The following code shows how the high level :mod:`threading` (XXX reference:
-../lib/module-threading.html) module can run tasks in background while the main
-program continues to run::
+The following code shows how the high level :mod:`threading` module can run
+tasks in background while the main program continues to run::
 
    import threading, zipfile
 
    class AsyncZip(threading.Thread):
        def __init__(self, infile, outfile):
-           threading.Thread.__init__(self)        
+           threading.Thread.__init__(self)
            self.infile = infile
            self.outfile = outfile
        def run(self):
            f = zipfile.ZipFile(self.outfile, 'w', zipfile.ZIP_DEFLATED)
            f.write(self.infile)
            f.close()
            print 'Finished background zip of: ', self.infile
 
    background = AsyncZip('mydata.txt', 'myarchive.zip')
    background.start()
    print 'The main program continues to run in foreground.'
 
    background.join()    # Wait for the background task to finish
    print 'Main program waited until background was done.'
 
 The principal challenge of multi-threaded applications is coordinating threads
 that share data or other resources.  To that end, the threading module provides
 a number of synchronization primitives including locks, events, condition
 variables, and semaphores.
 
 While those tools are powerful, minor design errors can result in problems that
 are difficult to reproduce.  So, the preferred approach to task coordination is
 to concentrate all access to a resource in a single thread and then use the
-:mod:`Queue` (XXX reference: ../lib/module-Queue.html) module to feed that
-thread with requests from other threads.  Applications using :class:`Queue`
-objects for inter-thread communication and coordination are easier to design,
-more readable, and more reliable.
+:mod:`Queue` module to feed that thread with requests from other threads.
+Applications using :class:`Queue.Queue` objects for inter-thread communication
+and coordination are easier to design, more readable, and more reliable.
 
 
 .. _tut-logging:
 
 Logging
 =======
 
-The :mod:`logging` (XXX reference: ../lib/module-logging.html) module offers a
-full featured and flexible logging system.  At its simplest, log messages are
-sent to a file or to ``sys.stderr``::
+The :mod:`logging` module offers a full featured and flexible logging system.
+At its simplest, log messages are sent to a file or to ``sys.stderr``::
 
    import logging
    logging.debug('Debugging information')
    logging.info('Informational message')
    logging.warning('Warning:config file %s not found', 'server.conf')
    logging.error('Error occurred')
    logging.critical('Critical error -- shutting down')
 
 This produces the following output::
 
    WARNING:root:Warning:config file server.conf not found
    ERROR:root:Error occurred
@@ -238,161 +232,160 @@
 
 The logging system can be configured directly from Python or can be loaded from
 a user editable configuration file for customized logging without altering the
 application.
 
 
 .. _tut-weak-references:
 
 Weak References
 ===============
 
 Python does automatic memory management (reference counting for most objects and
-garbage collection to eliminate cycles).  The memory is freed shortly after the
-last reference to it has been eliminated.
+:term:`garbage collection` to eliminate cycles).  The memory is freed shortly
+after the last reference to it has been eliminated.
 
 This approach works fine for most applications but occasionally there is a need
 to track objects only as long as they are being used by something else.
 Unfortunately, just tracking them creates a reference that makes them permanent.
-The :mod:`weakref` (XXX reference: ../lib/module-weakref.html) module provides
-tools for tracking objects without creating a reference.  When the object is no
-longer needed, it is automatically removed from a weakref table and a callback
-is triggered for weakref objects.  Typical applications include caching objects
-that are expensive to create::
+The :mod:`weakref` module provides tools for tracking objects without creating a
+reference.  When the object is no longer needed, it is automatically removed
+from a weakref table and a callback is triggered for weakref objects.  Typical
+applications include caching objects that are expensive to create::
 
    >>> import weakref, gc
    >>> class A:
    ...     def __init__(self, value):
    ...             self.value = value
    ...     def __repr__(self):
    ...             return str(self.value)
    ...
    >>> a = A(10)                   # create a reference
    >>> d = weakref.WeakValueDictionary()
    >>> d['primary'] = a            # does not create a reference
    >>> d['primary']                # fetch the object if it is still alive
    10
    >>> del a                       # remove the one reference
    >>> gc.collect()                # run garbage collection right away
    0
    >>> d['primary']                # entry was automatically removed
    Traceback (most recent call last):
-     File "<pyshell#108>", line 1, in -toplevel-
+     File "<stdin>", line 1, in <module>
        d['primary']                # entry was automatically removed
-     File "C:/PY24/lib/weakref.py", line 46, in __getitem__
+     File "C:/python26/lib/weakref.py", line 46, in __getitem__
        o = self.data[key]()
    KeyError: 'primary'
 
 
 .. _tut-list-tools:
 
 Tools for Working with Lists
 ============================
 
 Many data structure needs can be met with the built-in list type. However,
 sometimes there is a need for alternative implementations with different
 performance trade-offs.
 
-The :mod:`array` (XXX reference: ../lib/module-array.html) module provides an
-:class:`array()` object that is like a list that stores only homogenous data and
-stores it more compactly.  The following example shows an array of numbers
-stored as two byte unsigned binary numbers (typecode ``"H"``) rather than the
-usual 16 bytes per entry for regular lists of python int objects::
+The :mod:`array` module provides an :class:`array()` object that is like a list
+that stores only homogeneous data and stores it more compactly.  The following
+example shows an array of numbers stored as two byte unsigned binary numbers
+(typecode ``"H"``) rather than the usual 16 bytes per entry for regular lists of
+python int objects::
 
    >>> from array import array
    >>> a = array('H', [4000, 10, 700, 22222])
    >>> sum(a)
    26932
    >>> a[1:3]
    array('H', [10, 700])
 
-The :mod:`collections` (XXX reference: ../lib/module-collections.html) module
-provides a :class:`deque()` object that is like a list with faster appends and
-pops from the left side but slower lookups in the middle. These objects are well
-suited for implementing queues and breadth first tree searches::
+The :mod:`collections` module provides a :class:`deque()` object that is like a
+list with faster appends and pops from the left side but slower lookups in the
+middle. These objects are well suited for implementing queues and breadth first
+tree searches::
 
    >>> from collections import deque
    >>> d = deque(["task1", "task2", "task3"])
    >>> d.append("task4")
    >>> print "Handling", d.popleft()
    Handling task1
 
    unsearched = deque([starting_node])
    def breadth_first_search(unsearched):
        node = unsearched.popleft()
        for m in gen_moves(node):
            if is_goal(m):
                return m
            unsearched.append(m)
 
 In addition to alternative list implementations, the library also offers other
-tools such as the :mod:`bisect` (XXX reference: ../lib/module-bisect.html)
-module with functions for manipulating sorted lists::
+tools such as the :mod:`bisect` module with functions for manipulating sorted
+lists::
 
    >>> import bisect
    >>> scores = [(100, 'perl'), (200, 'tcl'), (400, 'lua'), (500, 'python')]
    >>> bisect.insort(scores, (300, 'ruby'))
    >>> scores
    [(100, 'perl'), (200, 'tcl'), (300, 'ruby'), (400, 'lua'), (500, 'python')]
 
-The :mod:`heapq` (XXX reference: ../lib/module-heapq.html) module provides
-functions for implementing heaps based on regular lists.  The lowest valued
-entry is always kept at position zero.  This is useful for applications which
-repeatedly access the smallest element but do not want to run a full list sort::
+The :mod:`heapq` module provides functions for implementing heaps based on
+regular lists.  The lowest valued entry is always kept at position zero.  This
+is useful for applications which repeatedly access the smallest element but do
+not want to run a full list sort::
 
    >>> from heapq import heapify, heappop, heappush
    >>> data = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0]
    >>> heapify(data)                      # rearrange the list into heap order
    >>> heappush(data, -5)                 # add a new entry
    >>> [heappop(data) for i in range(3)]  # fetch the three smallest entries
    [-5, 0, 1]
 
 
 .. _tut-decimal-fp:
 
 Decimal Floating Point Arithmetic
 =================================
 
-The :mod:`decimal` (XXX reference: ../lib/module-decimal.html) module offers a
-:class:`Decimal` datatype for decimal floating point arithmetic.  Compared to
-the built-in :class:`float` implementation of binary floating point, the new
-class is especially helpful for financial applications and other uses which
-require exact decimal representation, control over precision, control over
-rounding to meet legal or regulatory requirements, tracking of significant
-decimal places, or for applications where the user expects the results to match
-calculations done by hand.
+The :mod:`decimal` module offers a :class:`Decimal` datatype for decimal
+floating point arithmetic.  Compared to the built-in :class:`float`
+implementation of binary floating point, the new class is especially helpful for
+financial applications and other uses which require exact decimal
+representation, control over precision, control over rounding to meet legal or
+regulatory requirements, tracking of significant decimal places, or for
+applications where the user expects the results to match calculations done by
+hand.
 
 For example, calculating a 5% tax on a 70 cent phone charge gives different
 results in decimal floating point and binary floating point. The difference
 becomes significant if the results are rounded to the nearest cent::
 
-   >>> from decimal import *       
+   >>> from decimal import *
    >>> Decimal('0.70') * Decimal('1.05')
    Decimal("0.7350")
    >>> .70 * 1.05
-   0.73499999999999999       
+   0.73499999999999999
 
 The :class:`Decimal` result keeps a trailing zero, automatically inferring four
 place significance from multiplicands with two place significance.  Decimal
 reproduces mathematics as done by hand and avoids issues that can arise when
 binary floating point cannot exactly represent decimal quantities.
 
 Exact representation enables the :class:`Decimal` class to perform modulo
 calculations and equality tests that are unsuitable for binary floating point::
 
    >>> Decimal('1.00') % Decimal('.10')
    Decimal("0.00")
    >>> 1.00 % 0.10
    0.09999999999999995
 
    >>> sum([Decimal('0.1')]*10) == Decimal('1.0')
    True
    >>> sum([0.1]*10) == 1.0
-   False      
+   False
 
 The :mod:`decimal` module provides arithmetic with as much precision as needed::
 
    >>> getcontext().prec = 36
    >>> Decimal(1) / Decimal(7)
    Decimal("0.142857142857142857142857142857142857")
 
 
