diff --git a/Doc/library/collections.rst b/Doc/library/collections.rst
new file mode 100644
index 0000000..c2c9262
--- /dev/null
+++ b/Doc/library/collections.rst
@@ -0,0 +1,414 @@
+
+:mod:`collections` --- High-performance container datatypes
+===========================================================
+
+.. module:: collections
+   :synopsis: High-performance datatypes
+.. moduleauthor:: Raymond Hettinger <python@rcn.com>
+.. sectionauthor:: Raymond Hettinger <python@rcn.com>
+
+
+.. versionadded:: 2.4
+
+This module implements high-performance container datatypes.  Currently,
+there are two datatypes, :class:`deque` and :class:`defaultdict`, and
+one datatype factory function, :func:`NamedTuple`. Python already
+includes built-in containers, :class:`dict`, :class:`list`,
+:class:`set`, and :class:`tuple`. In addition, the optional :mod:`bsddb`
+module has a :meth:`bsddb.btopen` method that can be used to create in-memory
+or file based ordered dictionaries with string keys.
+
+Future editions of the standard library may include balanced trees and
+ordered dictionaries.
+
+.. versionchanged:: 2.5
+   Added :class:`defaultdict`.
+
+.. versionchanged:: 2.6
+   Added :class:`NamedTuple`.
+
+
+.. _deque-objects:
+
+:class:`deque` objects
+----------------------
+
+
+.. class:: deque([iterable])
+
+   Returns a new deque object initialized left-to-right (using :meth:`append`) with
+   data from *iterable*.  If *iterable* is not specified, the new deque is empty.
+
+   Deques are a generalization of stacks and queues (the name is pronounced "deck"
+   and is short for "double-ended queue").  Deques support thread-safe, memory
+   efficient appends and pops from either side of the deque with approximately the
+   same O(1) performance in either direction.
+
+   Though :class:`list` objects support similar operations, they are optimized for
+   fast fixed-length operations and incur O(n) memory movement costs for
+   ``pop(0)`` and ``insert(0, v)`` operations which change both the size and
+   position of the underlying data representation.
+
+   .. versionadded:: 2.4
+
+Deque objects support the following methods:
+
+
+.. method:: deque.append(x)
+
+   Add *x* to the right side of the deque.
+
+
+.. method:: deque.appendleft(x)
+
+   Add *x* to the left side of the deque.
+
+
+.. method:: deque.clear()
+
+   Remove all elements from the deque leaving it with length 0.
+
+
+.. method:: deque.extend(iterable)
+
+   Extend the right side of the deque by appending elements from the iterable
+   argument.
+
+
+.. method:: deque.extendleft(iterable)
+
+   Extend the left side of the deque by appending elements from *iterable*.  Note,
+   the series of left appends results in reversing the order of elements in the
+   iterable argument.
+
+
+.. method:: deque.pop()
+
+   Remove and return an element from the right side of the deque. If no elements
+   are present, raises an :exc:`IndexError`.
+
+
+.. method:: deque.popleft()
+
+   Remove and return an element from the left side of the deque. If no elements are
+   present, raises an :exc:`IndexError`.
+
+
+.. method:: deque.remove(value)
+
+   Removed the first occurrence of *value*.  If not found, raises a
+   :exc:`ValueError`.
+
+   .. versionadded:: 2.5
+
+
+.. method:: deque.rotate(n)
+
+   Rotate the deque *n* steps to the right.  If *n* is negative, rotate to the
+   left.  Rotating one step to the right is equivalent to:
+   ``d.appendleft(d.pop())``.
+
+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::
+
+   >>> 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()	
+   G
+   H
+   I
+
+   >>> d.append('j')                    # add a new entry to the right side
+   >>> d.appendleft('f')                # add a new entry to the left side
+   >>> d                                # show the representation of the deque
+   deque(['f', 'g', 'h', 'i', 'j'])
+
+   >>> d.pop()                          # return and remove the rightmost item
+   'j'
+   >>> d.popleft()                      # return and remove the leftmost item
+   'f'
+   >>> list(d)                          # list the contents of the deque
+   ['g', 'h', 'i']
+   >>> d[0]                             # peek at leftmost item
+   'g'
+   >>> d[-1]                            # peek at rightmost item
+   'i'
+
+   >>> list(reversed(d))                # list the contents of a deque in reverse
+   ['i', 'h', 'g']
+   >>> 'h' in d                         # search the deque
+   True
+   >>> d.extend('jkl')                  # add multiple elements at once
+   >>> d
+   deque(['g', 'h', 'i', 'j', 'k', 'l'])
+   >>> d.rotate(1)                      # right rotation
+   >>> d
+   deque(['l', 'g', 'h', 'i', 'j', 'k'])
+   >>> d.rotate(-1)                     # left rotation
+   >>> d
+   deque(['g', 'h', 'i', 'j', 'k', 'l'])
+
+   >>> deque(reversed(d))               # make a new deque in reverse order
+   deque(['l', 'k', 'j', 'i', 'h', 'g'])
+   >>> d.clear()                        # empty the deque
+   >>> d.pop()                          # cannot pop from an empty deque
+   Traceback (most recent call last):
+     File "<pyshell#6>", line 1, in -toplevel-
+       d.pop()
+   IndexError: pop from an empty deque
+
+   >>> d.extendleft('abc')              # extendleft() reverses the input order
+   >>> d
+   deque(['c', 'b', 'a'])
+
+
+.. _deque-recipes:
+
+Recipes
+^^^^^^^
+
+This section shows various approaches to working with deques.
+
+The :meth:`rotate` method provides a way to implement :class:`deque` slicing and
+deletion.  For example, a pure python implementation of ``del d[n]`` relies on
+the :meth:`rotate` method to position elements to be popped::
+
+   def delete_nth(d, n):
+       d.rotate(-n)
+       d.popleft()
+       d.rotate(n)
+
+To implement :class:`deque` slicing, use a similar approach applying
+:meth:`rotate` to bring a target element to the left side of the deque. Remove
+old entries with :meth:`popleft`, add new entries with :meth:`extend`, and then
+reverse the rotation.
+
+With minor variations on that approach, it is easy to implement Forth style
+stack manipulations such as ``dup``, ``drop``, ``swap``, ``over``, ``pick``,
+``rot``, and ``roll``.
+
+A roundrobin task server can be built from a :class:`deque` using
+:meth:`popleft` to select the current task and :meth:`append` to add it back to
+the tasklist if the input stream is not exhausted::
+
+   >>> def roundrobin(*iterables):
+   ...     pending = deque(iter(i) for i in iterables)
+   ...     while pending:
+   ...         task = pending.popleft()
+   ...         try:
+   ...             yield next(task)
+   ...         except StopIteration:
+   ...             continue
+   ...         pending.append(task)
+   ...
+   >>> for value in roundrobin('abc', 'd', 'efgh'):
+   ...     print value
+
+   a
+   d
+   e
+   b
+   f
+   c
+   g
+   h
+
+
+Multi-pass data reduction algorithms can be succinctly expressed and efficiently
+coded by extracting elements with multiple calls to :meth:`popleft`, applying
+the reduction function, and calling :meth:`append` to add the result back to the
+queue.
+
+For example, building a balanced binary tree of nested lists entails reducing
+two adjacent nodes into one by grouping them in a list::
+
+   >>> def maketree(iterable):
+   ...     d = deque(iterable)
+   ...     while len(d) > 1:
+   ...         pair = [d.popleft(), d.popleft()]
+   ...         d.append(pair)
+   ...     return list(d)
+   ...
+   >>> print maketree('abcdefgh')
+   [[[['a', 'b'], ['c', 'd']], [['e', 'f'], ['g', 'h']]]]
+
+
+
+.. _defaultdict-objects:
+
+:class:`defaultdict` objects
+----------------------------
+
+
+.. class:: defaultdict([default_factory[, ...]])
+
+   Returns a new dictionary-like object.  :class:`defaultdict` is a subclass of the
+   builtin :class:`dict` class.  It overrides one method and adds one writable
+   instance variable.  The remaining functionality is the same as for the
+   :class:`dict` class and is not documented here.
+
+   The first argument provides the initial value for the :attr:`default_factory`
+   attribute; it defaults to ``None``. All remaining arguments are treated the same
+   as if they were passed to the :class:`dict` constructor, including keyword
+   arguments.
+
+   .. versionadded:: 2.5
+
+:class:`defaultdict` objects support the following method in addition to the
+standard :class:`dict` operations:
+
+
+.. method:: defaultdict.__missing__(key)
+
+   If the :attr:`default_factory` attribute is ``None``, this raises an
+   :exc:`KeyError` exception with the *key* as argument.
+
+   If :attr:`default_factory` is not ``None``, it is called without arguments to
+   provide a default value for the given *key*, this value is inserted in the
+   dictionary for the *key*, and returned.
+
+   If calling :attr:`default_factory` raises an exception this exception is
+   propagated unchanged.
+
+   This method is called by the :meth:`__getitem__` method of the :class:`dict`
+   class when the requested key is not found; whatever it returns or raises is then
+   returned or raised by :meth:`__getitem__`.
+
+:class:`defaultdict` objects support the following instance variable:
+
+
+.. attribute:: defaultdict.default_factory
+
+   This attribute is used by the :meth:`__missing__` method; it is initialized from
+   the first argument to the constructor, if present, or to ``None``,  if absent.
+
+
+.. _defaultdict-examples:
+
+:class:`defaultdict` Examples
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Using :class:`list` as the :attr:`default_factory`, it is easy to group a
+sequence of key-value pairs into a dictionary of lists::
+
+   >>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
+   >>> d = defaultdict(list)
+   >>> for k, v in s:
+   ...     d[k].append(v)
+   ...
+   >>> d.items()
+   [('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
+
+When each key is encountered for the first time, it is not already in the
+mapping; so an entry is automatically created using the :attr:`default_factory`
+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`::
+
+   >>> d = {}
+   >>> for k, v in s:
+   ...     d.setdefault(k, []).append(v)
+   ...
+   >>> d.items()
+   [('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
+
+Setting the :attr:`default_factory` to :class:`int` makes the
+:class:`defaultdict` useful for counting (like a bag or multiset in other
+languages)::
+
+   >>> s = 'mississippi'
+   >>> d = defaultdict(int)
+   >>> for k in s:
+   ...     d[k] += 1
+   ...
+   >>> d.items()
+   [('i', 4), ('p', 2), ('s', 4), ('m', 1)]
+
+When a letter is first encountered, it is missing from the mapping, so the
+:attr:`default_factory` function calls :func:`int` to supply a default count of
+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 a lambda function which can supply any constant value (not just
+zero)::
+
+   >>> def constant_factory(value):
+   ...     return lambda: value
+   >>> d = defaultdict(constant_factory('<missing>'))
+   >>> d.update(name='John', action='ran')
+   >>> '%(name)s %(action)s to %(object)s' % d
+   'John ran to <missing>'
+
+Setting the :attr:`default_factory` to :class:`set` makes the
+: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)
+   >>> for k, v in s:
+   ...     d[k].add(v)
+   ...
+   >>> d.items()
+   [('blue', set([2, 4])), ('red', set([1, 3]))]
+
+
+.. _named-tuple-factory:
+
+:func:`NamedTuple` datatype factory function
+--------------------------------------------
+
+
+.. function:: NamedTuple(typename, fieldnames)
+
+   Returns a new tuple subclass named *typename*.  The new subclass is used to
+   create tuple-like objects that have fields accessable by attribute lookup as
+   well as being indexable and iterable.  Instances of the subclass also have a
+   helpful docstring (with typename and fieldnames) and a helpful :meth:`__repr__`
+   method which lists the tuple contents in a ``name=value`` format.
+
+   .. versionadded:: 2.6
+
+   The *fieldnames* are specified in a single string and are separated by spaces.
+   Any valid Python identifier may be used for a field name.
+
+   Example::
+
+      >>> Point = NamedTuple('Point', 'x y')
+      >>> Point.__doc__           # docstring for the new datatype
+      'Point(x, y)'
+      >>> p = Point(11, y=22)     # instantiate with positional or keyword arguments
+      >>> p[0] + p[1]             # works just like the tuple (11, 22)
+      33
+      >>> x, y = p                # unpacks just like a tuple
+      >>> x, y
+      (11, 22)
+      >>> p.x + p.y               # fields also accessable by name
+      33
+      >>> p                       # readable __repr__ with name=value style
+      Point(x=11, y=22)  
+
+   The use cases are the same as those for tuples.  The named factories assign
+   meaning to each tuple position and allow for more readable, self-documenting
+   code.  Named tuples can also be used to assign field names  to tuples returned
+   by the :mod:`csv` or :mod:`sqlite3` modules. For example::
+
+      from itertools import starmap
+      import csv
+      EmployeeRecord = NamedTuple('EmployeeRecord', 'name age title department paygrade')
+      for record in starmap(EmployeeRecord, csv.reader(open("employees.csv", "rb"))):
+          print record
+
+   To cast an individual record stored as :class:`list`, :class:`tuple`, or some
+   other iterable type, use the star-operator to unpack the values::
+
+      >>> Color = NamedTuple('Color', 'name code')
+      >>> m = dict(red=1, green=2, blue=3)
+      >>> print Color(*m.popitem())
+      Color(name='blue', code=3)
+