83 lines
2.7 KiB
ReStructuredText
83 lines
2.7 KiB
ReStructuredText
:mod:`collections` -- collection and container types
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====================================================
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.. module:: collections
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:synopsis: collection and container types
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|see_cpython_module| :mod:`python:collections`.
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This module implements advanced collection and container types to
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hold/accumulate various objects.
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Classes
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-------
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.. function:: deque(iterable, maxlen[, flags])
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Deques (double-ended queues) are a list-like container that support O(1)
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appends and pops from either side of the deque. New deques are created
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using the following arguments:
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- *iterable* must be the empty tuple, and the new deque is created empty.
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- *maxlen* must be specified and the deque will be bounded to this
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maximum length. Once the deque is full, any new items added will
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discard items from the opposite end.
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- The optional *flags* can be 1 to check for overflow when adding items.
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As well as supporting `bool` and `len`, deque objects have the following
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methods:
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.. method:: deque.append(x)
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Add *x* to the right side of the deque.
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Raises IndexError if overflow checking is enabled and there is no more room left.
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.. method:: deque.popleft()
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Remove and return an item from the left side of the deque.
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Raises IndexError if no items are present.
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.. function:: namedtuple(name, fields)
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This is factory function to create a new namedtuple type with a specific
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name and set of fields. A namedtuple is a subclass of tuple which allows
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to access its fields not just by numeric index, but also with an attribute
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access syntax using symbolic field names. Fields is a sequence of strings
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specifying field names. For compatibility with CPython it can also be a
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a string with space-separated field named (but this is less efficient).
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Example of use::
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from collections import namedtuple
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MyTuple = namedtuple("MyTuple", ("id", "name"))
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t1 = MyTuple(1, "foo")
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t2 = MyTuple(2, "bar")
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print(t1.name)
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assert t2.name == t2[1]
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.. function:: OrderedDict(...)
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``dict`` type subclass which remembers and preserves the order of keys
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added. When ordered dict is iterated over, keys/items are returned in
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the order they were added::
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from collections import OrderedDict
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# To make benefit of ordered keys, OrderedDict should be initialized
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# from sequence of (key, value) pairs.
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d = OrderedDict([("z", 1), ("a", 2)])
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# More items can be added as usual
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d["w"] = 5
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d["b"] = 3
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for k, v in d.items():
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print(k, v)
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Output::
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z 1
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a 2
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w 5
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b 3
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