typehints/stdlib/ucollections.pyi (21 lines of code) (raw):
"""
collection and container types.
Descriptions taken from:
https://raw.githubusercontent.com/micropython/micropython/master/docs/library/collections.rst.
====================================================
.. 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.
"""
__author__ = "Howard C Lovatt"
__copyright__ = "Howard C Lovatt, 2020 onwards."
__license__ = "MIT https://opensource.org/licenses/MIT (as used by MicroPython)."
__version__ = "7.3.0" # Version set by https://github.com/hlovatt/tag2ver
from typing import overload, Any, Type, Iterable, TypeVar, Generic, Mapping, Dict, Final
_KT: Final = TypeVar("_KT")
_VT: Final = TypeVar("_VT")
def namedtuple(name: str, fields: str | Iterable[str]) -> Type[tuple[Any, ...]]:
"""
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]
"""
# noinspection PyPep8Naming
class deque:
"""
Minimal implementation of a deque that implements a FIFO buffer.
"""
def __init__(self, iterable: tuple[Any], maxlen: int, flags: int = 0, /):
"""
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.
"""
def __bool__(self) -> bool:
"""
Returns true if the `deque` isn't empty.
**Note:** The method isn't listed by ``dir(deque)`` and can't be called directly,
however ``bool(deque)`` and automatic conversion work!
"""
def __len__(self) -> int:
"""
Returns the number of items in the `deque`.
**Note:** The method isn't listed by ``dir(deque)`` and can't be called directly,
however ``len(deque)`` works!
"""
def append(self, x: Any, /) -> None:
"""
Add *x* to the right side of the deque.
Raises IndexError if overflow checking is enabled and there is no more room left.
"""
def popleft(self) -> Any:
"""
Remove and return an item from the left side of the deque.
Raises IndexError if no items are present.
"""
class OrderedDict(Dict[_KT, _VT], Generic[_KT, _VT]):
"""
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"""
@overload
def __init__(self):
"""
``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
"""
@overload
def __init__(self, **kwargs: _VT):
"""
``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
"""
@overload
def __init__(self, map: Mapping[_KT, _VT], **kwargs: _VT):
"""
``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
"""