--- a/Doc/library/collections.rst	Sat Mar 22 20:08:43 2008 +0000
+++ b/Doc/library/collections.rst	Sat Mar 22 21:06:20 2008 +0000
@@ -7,12 +7,17 @@
 .. moduleauthor:: Raymond Hettinger <python@rcn.com>
 .. sectionauthor:: Raymond Hettinger <python@rcn.com>
 
+.. versionadded:: 2.4
 
-.. versionadded:: 2.4
+.. testsetup:: *
+
+   from collections import *
+   import itertools
+   __name__ = '<doctest>'
 
 This module implements high-performance container datatypes.  Currently,
 there are two datatypes, :class:`deque` and :class:`defaultdict`, and
-one datatype factory function, :func:`namedtuple`. 
+one datatype factory function, :func:`namedtuple`.
 
 .. versionchanged:: 2.5
    Added :class:`defaultdict`.
@@ -21,17 +26,17 @@
    Added :func:`namedtuple`.
 
 The specialized containers provided in this module provide alternatives
-to Python's general purpose built-in containers, :class:`dict`, 
+to Python's general purpose built-in containers, :class:`dict`,
 :class:`list`, :class:`set`, and :class:`tuple`.
 
 Besides the containers provided here, the optional :mod:`bsddb`
-module offers the ability to create in-memory or file based ordered 
+module offers the ability to create in-memory or file based ordered
 dictionaries with string keys using the :meth:`bsddb.btopen` method.
 
 In addition to containers, the collections module provides some ABCs
-(abstract base classes) that can be used to test whether a class 
+(abstract base classes) that can be used to test whether a class
 provides a particular interface, for example, is it hashable or
-a mapping. 
+a mapping.
 
 .. versionchanged:: 2.6
    Added abstract base classes.
@@ -113,15 +118,15 @@
 
 Notes on using :class:`Set` and :class:`MutableSet` as a mixin:
 
-(1) 
+(1)
    Since some set operations create new sets, the default mixin methods need
-   a way to create new instances from an iterable. The class constructor is 
-   assumed to have a signature in the form ``ClassName(iterable)``.  
+   a way to create new instances from an iterable. The class constructor is
+   assumed to have a signature in the form ``ClassName(iterable)``.
    That assumption is factored-out to a singleinternal classmethod called
    :meth:`_from_iterable` which calls ``cls(iterable)`` to produce a new set.
    If the :class:`Set` mixin is being used in a class with a different
-   constructor signature, you will need to override :meth:`from_iterable` 
-   with a classmethod that can construct new instances from 
+   constructor signature, you will need to override :meth:`from_iterable`
+   with a classmethod that can construct new instances from
    an iterable argument.
 
 (2)
@@ -235,12 +240,14 @@
 ``reversed(d)``, ``copy.copy(d)``, ``copy.deepcopy(d)``, membership testing with
 the :keyword:`in` operator, and subscript references such as ``d[-1]``.
 
-Example::
+Example:
+
+.. doctest::
 
    >>> from collections import deque
    >>> d = deque('ghi')                 # make a new deque with three items
    >>> for elem in d:                   # iterate over the deque's elements
-   ...     print elem.upper()	
+   ...     print elem.upper()
    G
    H
    I
@@ -319,7 +326,7 @@
 deque.
 
 For example, building a balanced binary tree of nested lists entails reducing
-two adjacent nodes into one by grouping them in a list::
+two adjacent nodes into one by grouping them in a list:
 
    >>> def maketree(iterable):
    ...     d = deque(iterable)
@@ -393,7 +400,7 @@
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Using :class:`list` as the :attr:`default_factory`, it is easy to group a
-sequence of key-value pairs into a dictionary of lists::
+sequence of key-value pairs into a dictionary of lists:
 
    >>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
    >>> d = defaultdict(list)
@@ -409,7 +416,7 @@
 operation then attaches the value to the new list.  When keys are encountered
 again, the look-up proceeds normally (returning the list for that key) and the
 :meth:`list.append` operation adds another value to the list. This technique is
-simpler and faster than an equivalent technique using :meth:`dict.setdefault`::
+simpler and faster than an equivalent technique using :meth:`dict.setdefault`:
 
    >>> d = {}
    >>> for k, v in s:
@@ -420,7 +427,7 @@
 
 Setting the :attr:`default_factory` to :class:`int` makes the
 :class:`defaultdict` useful for counting (like a bag or multiset in other
-languages)::
+languages):
 
    >>> s = 'mississippi'
    >>> d = defaultdict(int)
@@ -437,7 +444,7 @@
 The function :func:`int` which always returns zero is just a special case of
 constant functions.  A faster and more flexible way to create constant functions
 is to use :func:`itertools.repeat` which can supply any constant value (not just
-zero)::
+zero):
 
    >>> def constant_factory(value):
    ...     return itertools.repeat(value).next
@@ -447,7 +454,7 @@
    'John ran to <missing>'
 
 Setting the :attr:`default_factory` to :class:`set` makes the
-:class:`defaultdict` useful for building a dictionary of sets::
+:class:`defaultdict` useful for building a dictionary of sets:
 
    >>> s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)]
    >>> d = defaultdict(set)
@@ -492,41 +499,44 @@
 
    .. versionadded:: 2.6
 
-Example::
+Example:
+
+.. doctest::
+   :options: +NORMALIZE_WHITESPACE
 
    >>> Point = namedtuple('Point', 'x y', verbose=True)
    class Point(tuple):
            'Point(x, y)'
-
+   <BLANKLINE>
            __slots__ = ()
-
+   <BLANKLINE>
            _fields = ('x', 'y')
-
+   <BLANKLINE>
            def __new__(cls, x, y):
                return tuple.__new__(cls, (x, y))
-
+   <BLANKLINE>
            @classmethod
-           def _make(cls, iterable):
+           def _make(cls, iterable, new=tuple.__new__, len=len):
                'Make a new Point object from a sequence or iterable'
-               result = tuple.__new__(cls, iterable)
+               result = new(cls, iterable)
                if len(result) != 2:
                    raise TypeError('Expected 2 arguments, got %d' % len(result))
                return result
-
+   <BLANKLINE>
            def __repr__(self):
                return 'Point(x=%r, y=%r)' % self
-
+   <BLANKLINE>
            def _asdict(t):
                'Return a new dict which maps field names to their values'
                return {'x': t[0], 'y': t[1]}
-
+   <BLANKLINE>
            def _replace(self, **kwds):
                'Return a new Point object replacing specified fields with new values'
                result = self._make(map(kwds.pop, ('x', 'y'), self))
                if kwds:
                    raise ValueError('Got unexpected field names: %r' % kwds.keys())
                return result
-
+   <BLANKLINE>
            x = property(itemgetter(0))
            y = property(itemgetter(1))
 
@@ -565,7 +575,7 @@
 
    Class method that makes a new instance from an existing sequence or iterable.
 
-::
+.. doctest::
 
       >>> t = [11, 22]
       >>> Point._make(t)
@@ -573,16 +583,15 @@
 
 .. method:: somenamedtuple._asdict()
 
-   Return a new dict which maps field names to their corresponding values:
-
-::
+   Return a new dict which maps field names to their corresponding values::
 
       >>> p._asdict()
       {'x': 11, 'y': 22}
-      
+
 .. method:: somenamedtuple._replace(kwargs)
 
-   Return a new instance of the named tuple replacing specified fields with new values:
+   Return a new instance of the named tuple replacing specified fields with new
+   values:
 
 ::
 
@@ -598,7 +607,7 @@
    Tuple of strings listing the field names.  Useful for introspection
    and for creating new named tuple types from existing named tuples.
 
-::
+.. doctest::
 
       >>> p._fields            # view the field names
       ('x', 'y')
@@ -609,12 +618,12 @@
       Pixel(x=11, y=22, red=128, green=255, blue=0)
 
 To retrieve a field whose name is stored in a string, use the :func:`getattr`
-function::
+function:
 
     >>> getattr(p, 'x')
     11
 
-To convert a dictionary to a named tuple, use the double-star-operator [#]_::
+To convert a dictionary to a named tuple, use the double-star-operator [#]_:
 
    >>> d = {'x': 11, 'y': 22}
    >>> Point(**d)
@@ -622,7 +631,7 @@
 
 Since a named tuple is a regular Python class, it is easy to add or change
 functionality with a subclass.  Here is how to add a calculated field and
-a fixed-width print format::
+a fixed-width print format:
 
     >>> class Point(namedtuple('Point', 'x y')):
     ...     __slots__ = ()
@@ -634,7 +643,6 @@
 
     >>> for p in Point(3, 4), Point(14, 5/7.):
     ...     print p
-
     Point: x= 3.000  y= 4.000  hypot= 5.000
     Point: x=14.000  y= 0.714  hypot=14.018
 
@@ -642,12 +650,12 @@
 keep memory requirements low by preventing the creation of instance dictionaries.
 
 Subclassing is not useful for adding new, stored fields.  Instead, simply
-create a new named tuple type from the :attr:`_fields` attribute::
+create a new named tuple type from the :attr:`_fields` attribute:
 
     >>> Point3D = namedtuple('Point3D', Point._fields + ('z',))
 
 Default values can be implemented by using :meth:`_replace` to
-customize a prototype instance::
+customize a prototype instance:
 
     >>> Account = namedtuple('Account', 'owner balance transaction_count')
     >>> default_account = Account('<owner name>', 0.0, 0)