micropython/docs/library/collections.rst

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