collections – collection and container types¶
Though this MicroPython-based library may be available for use in some builds of CircuitPython, it is unsupported and its functionality may change in the future, perhaps significantly. As CircuitPython continues to develop, it may be changed to comply more closely with the corresponding standard Python library. You will likely need to change your code later if you rely on any non-standard functionality it currently provides.
This module implements advanced collection and container types to hold/accumulate various objects.
- collections.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.
Add x to the right side of the deque. Raises IndexError if overflow checking is enabled and there is no more room left.
Remove and return an item from the left side of the deque. Raises IndexError if no items are present.
- collections.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
dicttype 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)
z 1 a 2 w 5 b 3