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Corrected link targets in collections.rst (GH-1052)
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@ -114,7 +114,7 @@ The class can be used to simulate nested scopes and is useful in templating.
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for templating is a read-only chain of mappings. It also features
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pushing and popping of contexts similar to the
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:meth:`~collections.ChainMap.new_child` method and the
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:meth:`~collections.ChainMap.parents` property.
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:attr:`~collections.ChainMap.parents` property.
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* The `Nested Contexts recipe
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<https://code.activestate.com/recipes/577434/>`_ has options to control
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@ -270,7 +270,7 @@ For example::
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Return a list of the *n* most common elements and their counts from the
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most common to the least. If *n* is omitted or ``None``,
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:func:`most_common` returns *all* elements in the counter.
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:meth:`most_common` returns *all* elements in the counter.
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Elements with equal counts are ordered arbitrarily:
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>>> Counter('abracadabra').most_common(3) # doctest: +SKIP
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@ -357,12 +357,12 @@ or subtracting from an empty counter.
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restrictions on its keys and values. The values are intended to be numbers
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representing counts, but you *could* store anything in the value field.
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* The :meth:`most_common` method requires only that the values be orderable.
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* The :meth:`~Counter.most_common` method requires only that the values be orderable.
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* For in-place operations such as ``c[key] += 1``, the value type need only
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support addition and subtraction. So fractions, floats, and decimals would
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work and negative values are supported. The same is also true for
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:meth:`update` and :meth:`subtract` which allow negative and zero values
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:meth:`~Counter.update` and :meth:`~Counter.subtract` which allow negative and zero values
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for both inputs and outputs.
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* The multiset methods are designed only for use cases with positive values.
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@ -370,7 +370,7 @@ or subtracting from an empty counter.
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are created. There are no type restrictions, but the value type needs to
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support addition, subtraction, and comparison.
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* The :meth:`elements` method requires integer counts. It ignores zero and
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* The :meth:`~Counter.elements` method requires integer counts. It ignores zero and
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negative counts.
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.. seealso::
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@ -388,9 +388,9 @@ or subtracting from an empty counter.
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Section 4.6.3, Exercise 19*.
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* To enumerate all distinct multisets of a given size over a given set of
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elements, see :func:`itertools.combinations_with_replacement`:
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elements, see :func:`itertools.combinations_with_replacement`::
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map(Counter, combinations_with_replacement('ABC', 2)) --> AA AB AC BB BC CC
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map(Counter, combinations_with_replacement('ABC', 2)) # --> AA AB AC BB BC CC
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:class:`deque` objects
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@ -640,9 +640,9 @@ the :meth:`~deque.rotate` method::
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# Remove an exhausted iterator.
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iterators.popleft()
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The :meth:`rotate` method provides a way to implement :class:`deque` slicing and
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The :meth:`~deque.rotate` method provides a way to implement :class:`deque` slicing and
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deletion. For example, a pure Python implementation of ``del d[n]`` relies on
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the :meth:`rotate` method to position elements to be popped::
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the ``rotate()`` method to position elements to be popped::
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def delete_nth(d, n):
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d.rotate(-n)
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@ -650,8 +650,8 @@ the :meth:`rotate` method to position elements to be popped::
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d.rotate(n)
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To implement :class:`deque` slicing, use a similar approach applying
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:meth:`rotate` to bring a target element to the left side of the deque. Remove
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old entries with :meth:`popleft`, add new entries with :meth:`extend`, and then
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:meth:`~deque.rotate` to bring a target element to the left side of the deque. Remove
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old entries with :meth:`~deque.popleft`, add new entries with :meth:`~deque.extend`, and then
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reverse the rotation.
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With minor variations on that approach, it is easy to implement Forth style
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stack manipulations such as ``dup``, ``drop``, ``swap``, ``over``, ``pick``,
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@ -712,7 +712,7 @@ stack manipulations such as ``dup``, ``drop``, ``swap``, ``over``, ``pick``,
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:class:`defaultdict` Examples
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Using :class:`list` as the :attr:`default_factory`, it is easy to group a
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Using :class:`list` as the :attr:`~defaultdict.default_factory`, it is easy to group a
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sequence of key-value pairs into a dictionary of lists:
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>>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
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@ -724,7 +724,7 @@ sequence of key-value pairs into a dictionary of lists:
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[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
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When each key is encountered for the first time, it is not already in the
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mapping; so an entry is automatically created using the :attr:`default_factory`
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mapping; so an entry is automatically created using the :attr:`~defaultdict.default_factory`
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function which returns an empty :class:`list`. The :meth:`list.append`
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operation then attaches the value to the new list. When keys are encountered
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again, the look-up proceeds normally (returning the list for that key) and the
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@ -738,7 +738,7 @@ simpler and faster than an equivalent technique using :meth:`dict.setdefault`:
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>>> sorted(d.items())
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[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
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Setting the :attr:`default_factory` to :class:`int` makes the
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Setting the :attr:`~defaultdict.default_factory` to :class:`int` makes the
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:class:`defaultdict` useful for counting (like a bag or multiset in other
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languages):
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@ -751,7 +751,7 @@ languages):
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[('i', 4), ('m', 1), ('p', 2), ('s', 4)]
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When a letter is first encountered, it is missing from the mapping, so the
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:attr:`default_factory` function calls :func:`int` to supply a default count of
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:attr:`~defaultdict.default_factory` function calls :func:`int` to supply a default count of
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zero. The increment operation then builds up the count for each letter.
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The function :func:`int` which always returns zero is just a special case of
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@ -766,7 +766,7 @@ zero):
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>>> '%(name)s %(action)s to %(object)s' % d
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'John ran to <missing>'
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Setting the :attr:`default_factory` to :class:`set` makes the
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Setting the :attr:`~defaultdict.default_factory` to :class:`set` makes the
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:class:`defaultdict` useful for building a dictionary of sets:
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>>> s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)]
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@ -973,7 +973,7 @@ The subclass shown above sets ``__slots__`` to an empty tuple. This helps
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keep memory requirements low by preventing the creation of instance dictionaries.
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Subclassing is not useful for adding new, stored fields. Instead, simply
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create a new named tuple type from the :attr:`_fields` attribute:
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create a new named tuple type from the :attr:`~somenamedtuple._fields` attribute:
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>>> Point3D = namedtuple('Point3D', Point._fields + ('z',))
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@ -989,7 +989,7 @@ fields:
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.. versionchanged:: 3.5
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Property docstrings became writeable.
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Default values can be implemented by using :meth:`_replace` to
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Default values can be implemented by using :meth:`~somenamedtuple._replace` to
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customize a prototype instance:
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>>> Account = namedtuple('Account', 'owner balance transaction_count')
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@ -1200,15 +1200,22 @@ subclass directly from :class:`str`; however, this class can be easier
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to work with because the underlying string is accessible as an
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attribute.
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.. class:: UserString([sequence])
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.. class:: UserString(seq)
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Class that simulates a string or a Unicode string object. The instance's
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Class that simulates a string object. The instance's
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content is kept in a regular string object, which is accessible via the
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:attr:`data` attribute of :class:`UserString` instances. The instance's
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contents are initially set to a copy of *sequence*. The *sequence* can
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be an instance of :class:`bytes`, :class:`str`, :class:`UserString` (or a
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subclass) or an arbitrary sequence which can be converted into a string using
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the built-in :func:`str` function.
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contents are initially set to a copy of *seq*. The *seq* argument can
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be any object which can be converted into a string using the built-in
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:func:`str` function.
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In addition to supporting the methods and operations of strings,
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:class:`UserString` instances provide the following attribute:
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.. attribute:: data
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A real :class:`str` object used to store the contents of the
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:class:`UserString` class.
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.. versionchanged:: 3.5
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New methods ``__getnewargs__``, ``__rmod__``, ``casefold``,
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