Make collections' doctests executable.

(The <BLANKLINE>s will be stripped from presentation output.)

Doc/library/collections.rst

@@ -7,9 +7,14 @@
 .. moduleauthor:: Raymond Hettinger <python@rcn.com>
 .. sectionauthor:: Raymond Hettinger <python@rcn.com>
 
-
 .. 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`.
@@ -235,7 +240,9 @@ In addition to the above, deques support iteration, pickling, ``len(d)``,
 ``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
@@ -319,7 +326,7 @@ a reduction function, and calling :meth:`append` to add the result back to the
 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 @@ standard :class:`dict` operations:
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 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 @@ function which returns an empty :class:`list`.  The :meth:`list.append`
 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 @@ simpler and faster than an equivalent technique using :meth:`dict.setdefault`::
 
 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 @@ zero.  The increment operation then builds up the count for each letter.
 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 @@ zero)::
    '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 @@ they add the ability to access fields by name instead of position index.
 
    .. 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 @@ field names, the method and attribute names start with an underscore.
 
    Class method that makes a new instance from an existing sequence or iterable.
 
-::
+.. doctest::
 
       >>> t = [11, 22]
       >>> Point._make(t)
@@ -573,16 +583,15 @@ field names, the method and attribute names start with an underscore.
 
 .. 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 @@ field names, the method and attribute names start with an underscore.
    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 @@ field names, the method and attribute names start with an underscore.
       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 @@ To convert a dictionary to a named tuple, use the double-star-operator [#]_::
 
 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 @@ a fixed-width print format::
 
     >>> 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 @@ The subclass shown above sets ``__slots__`` to an empty tuple.  This keeps
 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)