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+
+: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)
+