Update more-itertools-8.10.0

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JonnyWong16 2021-10-14 21:13:45 -07:00
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@ -1,2 +1,4 @@
from more_itertools.more import * # noqa
from more_itertools.recipes import * # noqa
from .more import * # noqa
from .recipes import * # noqa
__version__ = '8.10.0'

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@ -0,0 +1,2 @@
from .more import *
from .recipes import *

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556
lib/more_itertools/more.pyi Normal file
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@ -0,0 +1,556 @@
"""Stubs for more_itertools.more"""
from typing import (
Any,
Callable,
Container,
Dict,
Generic,
Hashable,
Iterable,
Iterator,
List,
Optional,
Reversible,
Sequence,
Sized,
Tuple,
Union,
TypeVar,
type_check_only,
)
from types import TracebackType
from typing_extensions import ContextManager, Protocol, Type, overload
# Type and type variable definitions
_T = TypeVar('_T')
_T1 = TypeVar('_T1')
_T2 = TypeVar('_T2')
_U = TypeVar('_U')
_V = TypeVar('_V')
_W = TypeVar('_W')
_T_co = TypeVar('_T_co', covariant=True)
_GenFn = TypeVar('_GenFn', bound=Callable[..., Iterator[object]])
_Raisable = Union[BaseException, 'Type[BaseException]']
@type_check_only
class _SizedIterable(Protocol[_T_co], Sized, Iterable[_T_co]): ...
@type_check_only
class _SizedReversible(Protocol[_T_co], Sized, Reversible[_T_co]): ...
def chunked(
iterable: Iterable[_T], n: Optional[int], strict: bool = ...
) -> Iterator[List[_T]]: ...
@overload
def first(iterable: Iterable[_T]) -> _T: ...
@overload
def first(iterable: Iterable[_T], default: _U) -> Union[_T, _U]: ...
@overload
def last(iterable: Iterable[_T]) -> _T: ...
@overload
def last(iterable: Iterable[_T], default: _U) -> Union[_T, _U]: ...
@overload
def nth_or_last(iterable: Iterable[_T], n: int) -> _T: ...
@overload
def nth_or_last(
iterable: Iterable[_T], n: int, default: _U
) -> Union[_T, _U]: ...
class peekable(Generic[_T], Iterator[_T]):
def __init__(self, iterable: Iterable[_T]) -> None: ...
def __iter__(self) -> peekable[_T]: ...
def __bool__(self) -> bool: ...
@overload
def peek(self) -> _T: ...
@overload
def peek(self, default: _U) -> Union[_T, _U]: ...
def prepend(self, *items: _T) -> None: ...
def __next__(self) -> _T: ...
@overload
def __getitem__(self, index: int) -> _T: ...
@overload
def __getitem__(self, index: slice) -> List[_T]: ...
def collate(*iterables: Iterable[_T], **kwargs: Any) -> Iterable[_T]: ...
def consumer(func: _GenFn) -> _GenFn: ...
def ilen(iterable: Iterable[object]) -> int: ...
def iterate(func: Callable[[_T], _T], start: _T) -> Iterator[_T]: ...
def with_iter(
context_manager: ContextManager[Iterable[_T]],
) -> Iterator[_T]: ...
def one(
iterable: Iterable[_T],
too_short: Optional[_Raisable] = ...,
too_long: Optional[_Raisable] = ...,
) -> _T: ...
def distinct_permutations(
iterable: Iterable[_T], r: Optional[int] = ...
) -> Iterator[Tuple[_T, ...]]: ...
def intersperse(
e: _U, iterable: Iterable[_T], n: int = ...
) -> Iterator[Union[_T, _U]]: ...
def unique_to_each(*iterables: Iterable[_T]) -> List[List[_T]]: ...
@overload
def windowed(
seq: Iterable[_T], n: int, *, step: int = ...
) -> Iterator[Tuple[Optional[_T], ...]]: ...
@overload
def windowed(
seq: Iterable[_T], n: int, fillvalue: _U, step: int = ...
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
def substrings(iterable: Iterable[_T]) -> Iterator[Tuple[_T, ...]]: ...
def substrings_indexes(
seq: Sequence[_T], reverse: bool = ...
) -> Iterator[Tuple[Sequence[_T], int, int]]: ...
class bucket(Generic[_T, _U], Container[_U]):
def __init__(
self,
iterable: Iterable[_T],
key: Callable[[_T], _U],
validator: Optional[Callable[[object], object]] = ...,
) -> None: ...
def __contains__(self, value: object) -> bool: ...
def __iter__(self) -> Iterator[_U]: ...
def __getitem__(self, value: object) -> Iterator[_T]: ...
def spy(
iterable: Iterable[_T], n: int = ...
) -> Tuple[List[_T], Iterator[_T]]: ...
def interleave(*iterables: Iterable[_T]) -> Iterator[_T]: ...
def interleave_longest(*iterables: Iterable[_T]) -> Iterator[_T]: ...
def interleave_evenly(
iterables: List[Iterable[_T]], lengths: Optional[List[int]] = ...
) -> Iterator[_T]: ...
def collapse(
iterable: Iterable[Any],
base_type: Optional[type] = ...,
levels: Optional[int] = ...,
) -> Iterator[Any]: ...
@overload
def side_effect(
func: Callable[[_T], object],
iterable: Iterable[_T],
chunk_size: None = ...,
before: Optional[Callable[[], object]] = ...,
after: Optional[Callable[[], object]] = ...,
) -> Iterator[_T]: ...
@overload
def side_effect(
func: Callable[[List[_T]], object],
iterable: Iterable[_T],
chunk_size: int,
before: Optional[Callable[[], object]] = ...,
after: Optional[Callable[[], object]] = ...,
) -> Iterator[_T]: ...
def sliced(
seq: Sequence[_T], n: int, strict: bool = ...
) -> Iterator[Sequence[_T]]: ...
def split_at(
iterable: Iterable[_T],
pred: Callable[[_T], object],
maxsplit: int = ...,
keep_separator: bool = ...,
) -> Iterator[List[_T]]: ...
def split_before(
iterable: Iterable[_T], pred: Callable[[_T], object], maxsplit: int = ...
) -> Iterator[List[_T]]: ...
def split_after(
iterable: Iterable[_T], pred: Callable[[_T], object], maxsplit: int = ...
) -> Iterator[List[_T]]: ...
def split_when(
iterable: Iterable[_T],
pred: Callable[[_T, _T], object],
maxsplit: int = ...,
) -> Iterator[List[_T]]: ...
def split_into(
iterable: Iterable[_T], sizes: Iterable[Optional[int]]
) -> Iterator[List[_T]]: ...
@overload
def padded(
iterable: Iterable[_T],
*,
n: Optional[int] = ...,
next_multiple: bool = ...
) -> Iterator[Optional[_T]]: ...
@overload
def padded(
iterable: Iterable[_T],
fillvalue: _U,
n: Optional[int] = ...,
next_multiple: bool = ...,
) -> Iterator[Union[_T, _U]]: ...
@overload
def repeat_last(iterable: Iterable[_T]) -> Iterator[_T]: ...
@overload
def repeat_last(
iterable: Iterable[_T], default: _U
) -> Iterator[Union[_T, _U]]: ...
def distribute(n: int, iterable: Iterable[_T]) -> List[Iterator[_T]]: ...
@overload
def stagger(
iterable: Iterable[_T],
offsets: _SizedIterable[int] = ...,
longest: bool = ...,
) -> Iterator[Tuple[Optional[_T], ...]]: ...
@overload
def stagger(
iterable: Iterable[_T],
offsets: _SizedIterable[int] = ...,
longest: bool = ...,
fillvalue: _U = ...,
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
class UnequalIterablesError(ValueError):
def __init__(
self, details: Optional[Tuple[int, int, int]] = ...
) -> None: ...
@overload
def zip_equal(__iter1: Iterable[_T1]) -> Iterator[Tuple[_T1]]: ...
@overload
def zip_equal(
__iter1: Iterable[_T1], __iter2: Iterable[_T2]
) -> Iterator[Tuple[_T1, _T2]]: ...
@overload
def zip_equal(
__iter1: Iterable[_T],
__iter2: Iterable[_T],
__iter3: Iterable[_T],
*iterables: Iterable[_T]
) -> Iterator[Tuple[_T, ...]]: ...
@overload
def zip_offset(
__iter1: Iterable[_T1],
*,
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: None = None
) -> Iterator[Tuple[Optional[_T1]]]: ...
@overload
def zip_offset(
__iter1: Iterable[_T1],
__iter2: Iterable[_T2],
*,
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: None = None
) -> Iterator[Tuple[Optional[_T1], Optional[_T2]]]: ...
@overload
def zip_offset(
__iter1: Iterable[_T],
__iter2: Iterable[_T],
__iter3: Iterable[_T],
*iterables: Iterable[_T],
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: None = None
) -> Iterator[Tuple[Optional[_T], ...]]: ...
@overload
def zip_offset(
__iter1: Iterable[_T1],
*,
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: _U,
) -> Iterator[Tuple[Union[_T1, _U]]]: ...
@overload
def zip_offset(
__iter1: Iterable[_T1],
__iter2: Iterable[_T2],
*,
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: _U,
) -> Iterator[Tuple[Union[_T1, _U], Union[_T2, _U]]]: ...
@overload
def zip_offset(
__iter1: Iterable[_T],
__iter2: Iterable[_T],
__iter3: Iterable[_T],
*iterables: Iterable[_T],
offsets: _SizedIterable[int],
longest: bool = ...,
fillvalue: _U,
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
def sort_together(
iterables: Iterable[Iterable[_T]],
key_list: Iterable[int] = ...,
key: Optional[Callable[..., Any]] = ...,
reverse: bool = ...,
) -> List[Tuple[_T, ...]]: ...
def unzip(iterable: Iterable[Sequence[_T]]) -> Tuple[Iterator[_T], ...]: ...
def divide(n: int, iterable: Iterable[_T]) -> List[Iterator[_T]]: ...
def always_iterable(
obj: object,
base_type: Union[
type, Tuple[Union[type, Tuple[Any, ...]], ...], None
] = ...,
) -> Iterator[Any]: ...
def adjacent(
predicate: Callable[[_T], bool],
iterable: Iterable[_T],
distance: int = ...,
) -> Iterator[Tuple[bool, _T]]: ...
def groupby_transform(
iterable: Iterable[_T],
keyfunc: Optional[Callable[[_T], _U]] = ...,
valuefunc: Optional[Callable[[_T], _V]] = ...,
reducefunc: Optional[Callable[..., _W]] = ...,
) -> Iterator[Tuple[_T, _W]]: ...
class numeric_range(Generic[_T, _U], Sequence[_T], Hashable, Reversible[_T]):
@overload
def __init__(self, __stop: _T) -> None: ...
@overload
def __init__(self, __start: _T, __stop: _T) -> None: ...
@overload
def __init__(self, __start: _T, __stop: _T, __step: _U) -> None: ...
def __bool__(self) -> bool: ...
def __contains__(self, elem: object) -> bool: ...
def __eq__(self, other: object) -> bool: ...
@overload
def __getitem__(self, key: int) -> _T: ...
@overload
def __getitem__(self, key: slice) -> numeric_range[_T, _U]: ...
def __hash__(self) -> int: ...
def __iter__(self) -> Iterator[_T]: ...
def __len__(self) -> int: ...
def __reduce__(
self,
) -> Tuple[Type[numeric_range[_T, _U]], Tuple[_T, _T, _U]]: ...
def __repr__(self) -> str: ...
def __reversed__(self) -> Iterator[_T]: ...
def count(self, value: _T) -> int: ...
def index(self, value: _T) -> int: ... # type: ignore
def count_cycle(
iterable: Iterable[_T], n: Optional[int] = ...
) -> Iterable[Tuple[int, _T]]: ...
def mark_ends(
iterable: Iterable[_T],
) -> Iterable[Tuple[bool, bool, _T]]: ...
def locate(
iterable: Iterable[object],
pred: Callable[..., Any] = ...,
window_size: Optional[int] = ...,
) -> Iterator[int]: ...
def lstrip(
iterable: Iterable[_T], pred: Callable[[_T], object]
) -> Iterator[_T]: ...
def rstrip(
iterable: Iterable[_T], pred: Callable[[_T], object]
) -> Iterator[_T]: ...
def strip(
iterable: Iterable[_T], pred: Callable[[_T], object]
) -> Iterator[_T]: ...
class islice_extended(Generic[_T], Iterator[_T]):
def __init__(
self, iterable: Iterable[_T], *args: Optional[int]
) -> None: ...
def __iter__(self) -> islice_extended[_T]: ...
def __next__(self) -> _T: ...
def __getitem__(self, index: slice) -> islice_extended[_T]: ...
def always_reversible(iterable: Iterable[_T]) -> Iterator[_T]: ...
def consecutive_groups(
iterable: Iterable[_T], ordering: Callable[[_T], int] = ...
) -> Iterator[Iterator[_T]]: ...
@overload
def difference(
iterable: Iterable[_T],
func: Callable[[_T, _T], _U] = ...,
*,
initial: None = ...
) -> Iterator[Union[_T, _U]]: ...
@overload
def difference(
iterable: Iterable[_T], func: Callable[[_T, _T], _U] = ..., *, initial: _U
) -> Iterator[_U]: ...
class SequenceView(Generic[_T], Sequence[_T]):
def __init__(self, target: Sequence[_T]) -> None: ...
@overload
def __getitem__(self, index: int) -> _T: ...
@overload
def __getitem__(self, index: slice) -> Sequence[_T]: ...
def __len__(self) -> int: ...
class seekable(Generic[_T], Iterator[_T]):
def __init__(
self, iterable: Iterable[_T], maxlen: Optional[int] = ...
) -> None: ...
def __iter__(self) -> seekable[_T]: ...
def __next__(self) -> _T: ...
def __bool__(self) -> bool: ...
@overload
def peek(self) -> _T: ...
@overload
def peek(self, default: _U) -> Union[_T, _U]: ...
def elements(self) -> SequenceView[_T]: ...
def seek(self, index: int) -> None: ...
class run_length:
@staticmethod
def encode(iterable: Iterable[_T]) -> Iterator[Tuple[_T, int]]: ...
@staticmethod
def decode(iterable: Iterable[Tuple[_T, int]]) -> Iterator[_T]: ...
def exactly_n(
iterable: Iterable[_T], n: int, predicate: Callable[[_T], object] = ...
) -> bool: ...
def circular_shifts(iterable: Iterable[_T]) -> List[Tuple[_T, ...]]: ...
def make_decorator(
wrapping_func: Callable[..., _U], result_index: int = ...
) -> Callable[..., Callable[[Callable[..., Any]], Callable[..., _U]]]: ...
@overload
def map_reduce(
iterable: Iterable[_T],
keyfunc: Callable[[_T], _U],
valuefunc: None = ...,
reducefunc: None = ...,
) -> Dict[_U, List[_T]]: ...
@overload
def map_reduce(
iterable: Iterable[_T],
keyfunc: Callable[[_T], _U],
valuefunc: Callable[[_T], _V],
reducefunc: None = ...,
) -> Dict[_U, List[_V]]: ...
@overload
def map_reduce(
iterable: Iterable[_T],
keyfunc: Callable[[_T], _U],
valuefunc: None = ...,
reducefunc: Callable[[List[_T]], _W] = ...,
) -> Dict[_U, _W]: ...
@overload
def map_reduce(
iterable: Iterable[_T],
keyfunc: Callable[[_T], _U],
valuefunc: Callable[[_T], _V],
reducefunc: Callable[[List[_V]], _W],
) -> Dict[_U, _W]: ...
def rlocate(
iterable: Iterable[_T],
pred: Callable[..., object] = ...,
window_size: Optional[int] = ...,
) -> Iterator[int]: ...
def replace(
iterable: Iterable[_T],
pred: Callable[..., object],
substitutes: Iterable[_U],
count: Optional[int] = ...,
window_size: int = ...,
) -> Iterator[Union[_T, _U]]: ...
def partitions(iterable: Iterable[_T]) -> Iterator[List[List[_T]]]: ...
def set_partitions(
iterable: Iterable[_T], k: Optional[int] = ...
) -> Iterator[List[List[_T]]]: ...
class time_limited(Generic[_T], Iterator[_T]):
def __init__(
self, limit_seconds: float, iterable: Iterable[_T]
) -> None: ...
def __iter__(self) -> islice_extended[_T]: ...
def __next__(self) -> _T: ...
@overload
def only(
iterable: Iterable[_T], *, too_long: Optional[_Raisable] = ...
) -> Optional[_T]: ...
@overload
def only(
iterable: Iterable[_T], default: _U, too_long: Optional[_Raisable] = ...
) -> Union[_T, _U]: ...
def ichunked(iterable: Iterable[_T], n: int) -> Iterator[Iterator[_T]]: ...
def distinct_combinations(
iterable: Iterable[_T], r: int
) -> Iterator[Tuple[_T, ...]]: ...
def filter_except(
validator: Callable[[Any], object],
iterable: Iterable[_T],
*exceptions: Type[BaseException]
) -> Iterator[_T]: ...
def map_except(
function: Callable[[Any], _U],
iterable: Iterable[_T],
*exceptions: Type[BaseException]
) -> Iterator[_U]: ...
def map_if(
iterable: Iterable[Any],
pred: Callable[[Any], bool],
func: Callable[[Any], Any],
func_else: Optional[Callable[[Any], Any]] = ...,
) -> Iterator[Any]: ...
def sample(
iterable: Iterable[_T],
k: int,
weights: Optional[Iterable[float]] = ...,
) -> List[_T]: ...
def is_sorted(
iterable: Iterable[_T],
key: Optional[Callable[[_T], _U]] = ...,
reverse: bool = False,
) -> bool: ...
class AbortThread(BaseException):
pass
class callback_iter(Generic[_T], Iterator[_T]):
def __init__(
self,
func: Callable[..., Any],
callback_kwd: str = ...,
wait_seconds: float = ...,
) -> None: ...
def __enter__(self) -> callback_iter[_T]: ...
def __exit__(
self,
exc_type: Optional[Type[BaseException]],
exc_value: Optional[BaseException],
traceback: Optional[TracebackType],
) -> Optional[bool]: ...
def __iter__(self) -> callback_iter[_T]: ...
def __next__(self) -> _T: ...
def _reader(self) -> Iterator[_T]: ...
@property
def done(self) -> bool: ...
@property
def result(self) -> Any: ...
def windowed_complete(
iterable: Iterable[_T], n: int
) -> Iterator[Tuple[_T, ...]]: ...
def all_unique(
iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ...
) -> bool: ...
def nth_product(index: int, *args: Iterable[_T]) -> Tuple[_T, ...]: ...
def nth_permutation(
iterable: Iterable[_T], r: int, index: int
) -> Tuple[_T, ...]: ...
def value_chain(*args: Union[_T, Iterable[_T]]) -> Iterable[_T]: ...
def product_index(element: Iterable[_T], *args: Iterable[_T]) -> int: ...
def combination_index(
element: Iterable[_T], iterable: Iterable[_T]
) -> int: ...
def permutation_index(
element: Iterable[_T], iterable: Iterable[_T]
) -> int: ...
def repeat_each(iterable: Iterable[_T], n: int = ...) -> Iterator[_T]: ...
class countable(Generic[_T], Iterator[_T]):
def __init__(self, iterable: Iterable[_T]) -> None: ...
def __iter__(self) -> countable[_T]: ...
def __next__(self) -> _T: ...
def chunked_even(iterable: Iterable[_T], n: int) -> Iterator[List[_T]]: ...
def zip_broadcast(
*objects: Union[_T, Iterable[_T]],
scalar_types: Union[
type, Tuple[Union[type, Tuple[Any, ...]], ...], None
] = ...,
strict: bool = ...
) -> Iterable[Tuple[_T, ...]]: ...

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@ -7,20 +7,27 @@ Some backward-compatible usability improvements have been made.
.. [1] http://docs.python.org/library/itertools.html#recipes
"""
import warnings
from collections import deque
from itertools import (
chain, combinations, count, cycle, groupby, islice, repeat, starmap, tee
chain,
combinations,
count,
cycle,
groupby,
islice,
repeat,
starmap,
tee,
zip_longest,
)
import operator
from random import randrange, sample, choice
from six import PY2
from six.moves import filter, filterfalse, map, range, zip, zip_longest
__all__ = [
'accumulate',
'all_equal',
'consume',
'convolve',
'dotproduct',
'first_true',
'flatten',
@ -30,6 +37,7 @@ __all__ = [
'nth',
'nth_combination',
'padnone',
'pad_none',
'pairwise',
'partition',
'powerset',
@ -49,46 +57,17 @@ __all__ = [
]
def accumulate(iterable, func=operator.add):
"""
Return an iterator whose items are the accumulated results of a function
(specified by the optional *func* argument) that takes two arguments.
By default, returns accumulated sums with :func:`operator.add`.
>>> list(accumulate([1, 2, 3, 4, 5])) # Running sum
[1, 3, 6, 10, 15]
>>> list(accumulate([1, 2, 3], func=operator.mul)) # Running product
[1, 2, 6]
>>> list(accumulate([0, 1, -1, 2, 3, 2], func=max)) # Running maximum
[0, 1, 1, 2, 3, 3]
This function is available in the ``itertools`` module for Python 3.2 and
greater.
"""
it = iter(iterable)
try:
total = next(it)
except StopIteration:
return
else:
yield total
for element in it:
total = func(total, element)
yield total
def take(n, iterable):
"""Return first *n* items of the iterable as a list.
>>> take(3, range(10))
[0, 1, 2]
>>> take(5, range(3))
[0, 1, 2]
Effectively a short replacement for ``next`` based iterator consumption
when you want more than one item, but less than the whole iterator.
If there are fewer than *n* items in the iterable, all of them are
returned.
>>> take(10, range(3))
[0, 1, 2]
"""
return list(islice(iterable, n))
@ -200,10 +179,10 @@ def quantify(iterable, pred=bool):
return sum(map(pred, iterable))
def padnone(iterable):
def pad_none(iterable):
"""Returns the sequence of elements and then returns ``None`` indefinitely.
>>> take(5, padnone(range(3)))
>>> take(5, pad_none(range(3)))
[0, 1, 2, None, None]
Useful for emulating the behavior of the built-in :func:`map` function.
@ -214,6 +193,9 @@ def padnone(iterable):
return chain(iterable, repeat(None))
padnone = pad_none
def ncycles(iterable, n):
"""Returns the sequence elements *n* times
@ -273,25 +255,44 @@ def repeatfunc(func, times=None, *args):
return starmap(func, repeat(args, times))
def pairwise(iterable):
def _pairwise(iterable):
"""Returns an iterator of paired items, overlapping, from the original
>>> take(4, pairwise(count()))
[(0, 1), (1, 2), (2, 3), (3, 4)]
On Python 3.10 and above, this is an alias for :func:`itertools.pairwise`.
"""
a, b = tee(iterable)
next(b, None)
return zip(a, b)
yield from zip(a, b)
def grouper(n, iterable, fillvalue=None):
try:
from itertools import pairwise as itertools_pairwise
except ImportError:
pairwise = _pairwise
else:
def pairwise(iterable):
yield from itertools_pairwise(iterable)
pairwise.__doc__ = _pairwise.__doc__
def grouper(iterable, n, fillvalue=None):
"""Collect data into fixed-length chunks or blocks.
>>> list(grouper(3, 'ABCDEFG', 'x'))
>>> list(grouper('ABCDEFG', 3, 'x'))
[('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')]
"""
if isinstance(iterable, int):
warnings.warn(
"grouper expects iterable as first parameter", DeprecationWarning
)
n, iterable = iterable, n
args = [iter(iterable)] * n
return zip_longest(fillvalue=fillvalue, *args)
@ -309,9 +310,6 @@ def roundrobin(*iterables):
"""
# Recipe credited to George Sakkis
pending = len(iterables)
if PY2:
nexts = cycle(iter(it).next for it in iterables)
else:
nexts = cycle(iter(it).__next__ for it in iterables)
while pending:
try:
@ -334,10 +332,23 @@ def partition(pred, iterable):
>>> list(even_items), list(odd_items)
([0, 2, 4, 6, 8], [1, 3, 5, 7, 9])
If *pred* is None, :func:`bool` is used.
>>> iterable = [0, 1, False, True, '', ' ']
>>> false_items, true_items = partition(None, iterable)
>>> list(false_items), list(true_items)
([0, False, ''], [1, True, ' '])
"""
# partition(is_odd, range(10)) --> 0 2 4 6 8 and 1 3 5 7 9
t1, t2 = tee(iterable)
return filterfalse(pred, t1), filter(pred, t2)
if pred is None:
pred = bool
evaluations = ((pred(x), x) for x in iterable)
t1, t2 = tee(evaluations)
return (
(x for (cond, x) in t1 if not cond),
(x for (cond, x) in t2 if cond),
)
def powerset(iterable):
@ -375,24 +386,29 @@ def unique_everseen(iterable, key=None):
Sequences with a mix of hashable and unhashable items can be used.
The function will be slower (i.e., `O(n^2)`) for unhashable items.
Remember that ``list`` objects are unhashable - you can use the *key*
parameter to transform the list to a tuple (which is hashable) to
avoid a slowdown.
>>> iterable = ([1, 2], [2, 3], [1, 2])
>>> list(unique_everseen(iterable)) # Slow
[[1, 2], [2, 3]]
>>> list(unique_everseen(iterable, key=tuple)) # Faster
[[1, 2], [2, 3]]
Similary, you may want to convert unhashable ``set`` objects with
``key=frozenset``. For ``dict`` objects,
``key=lambda x: frozenset(x.items())`` can be used.
"""
seenset = set()
seenset_add = seenset.add
seenlist = []
seenlist_add = seenlist.append
if key is None:
use_key = key is not None
for element in iterable:
try:
if element not in seenset:
seenset_add(element)
yield element
except TypeError:
if element not in seenlist:
seenlist_add(element)
yield element
else:
for element in iterable:
k = key(element)
k = key(element) if use_key else element
try:
if k not in seenset:
seenset_add(k)
@ -426,6 +442,16 @@ def iter_except(func, exception, first=None):
>>> list(iter_except(l.pop, IndexError))
[2, 1, 0]
Multiple exceptions can be specified as a stopping condition:
>>> l = [1, 2, 3, '...', 4, 5, 6]
>>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError)))
[7, 6, 5]
>>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError)))
[4, 3, 2]
>>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError)))
[]
"""
try:
if first is not None:
@ -456,7 +482,7 @@ def first_true(iterable, default=None, pred=None):
return next(filter(pred, iterable), default)
def random_product(*args, **kwds):
def random_product(*args, repeat=1):
"""Draw an item at random from each of the input iterables.
>>> random_product('abc', range(4), 'XYZ') # doctest:+SKIP
@ -472,7 +498,7 @@ def random_product(*args, **kwds):
``itertools.product(*args, **kwarg)``.
"""
pools = [tuple(pool) for pool in args] * kwds.get('repeat', 1)
pools = [tuple(pool) for pool in args] * repeat
return tuple(choice(pool) for pool in pools)
@ -535,6 +561,12 @@ def nth_combination(iterable, r, index):
sort position *index* directly, without computing the previous
subsequences.
>>> nth_combination(range(5), 3, 5)
(0, 3, 4)
``ValueError`` will be raised If *r* is negative or greater than the length
of *iterable*.
``IndexError`` will be raised if the given *index* is invalid.
"""
pool = tuple(iterable)
n = len(pool)
@ -571,7 +603,28 @@ def prepend(value, iterator):
>>> list(prepend(value, iterator))
['0', '1', '2', '3']
To prepend multiple values, see :func:`itertools.chain`.
To prepend multiple values, see :func:`itertools.chain`
or :func:`value_chain`.
"""
return chain([value], iterator)
def convolve(signal, kernel):
"""Convolve the iterable *signal* with the iterable *kernel*.
>>> signal = (1, 2, 3, 4, 5)
>>> kernel = [3, 2, 1]
>>> list(convolve(signal, kernel))
[3, 8, 14, 20, 26, 14, 5]
Note: the input arguments are not interchangeable, as the *kernel*
is immediately consumed and stored.
"""
kernel = tuple(kernel)[::-1]
n = len(kernel)
window = deque([0], maxlen=n) * n
for x in chain(signal, repeat(0, n - 1)):
window.append(x)
yield sum(map(operator.mul, kernel, window))

View file

@ -0,0 +1,105 @@
"""Stubs for more_itertools.recipes"""
from typing import (
Any,
Callable,
Iterable,
Iterator,
List,
Optional,
Tuple,
TypeVar,
Union,
)
from typing_extensions import overload, Type
# Type and type variable definitions
_T = TypeVar('_T')
_U = TypeVar('_U')
def take(n: int, iterable: Iterable[_T]) -> List[_T]: ...
def tabulate(
function: Callable[[int], _T], start: int = ...
) -> Iterator[_T]: ...
def tail(n: int, iterable: Iterable[_T]) -> Iterator[_T]: ...
def consume(iterator: Iterable[object], n: Optional[int] = ...) -> None: ...
@overload
def nth(iterable: Iterable[_T], n: int) -> Optional[_T]: ...
@overload
def nth(iterable: Iterable[_T], n: int, default: _U) -> Union[_T, _U]: ...
def all_equal(iterable: Iterable[object]) -> bool: ...
def quantify(
iterable: Iterable[_T], pred: Callable[[_T], bool] = ...
) -> int: ...
def pad_none(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ...
def padnone(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ...
def ncycles(iterable: Iterable[_T], n: int) -> Iterator[_T]: ...
def dotproduct(vec1: Iterable[object], vec2: Iterable[object]) -> object: ...
def flatten(listOfLists: Iterable[Iterable[_T]]) -> Iterator[_T]: ...
def repeatfunc(
func: Callable[..., _U], times: Optional[int] = ..., *args: Any
) -> Iterator[_U]: ...
def pairwise(iterable: Iterable[_T]) -> Iterator[Tuple[_T, _T]]: ...
@overload
def grouper(
iterable: Iterable[_T], n: int
) -> Iterator[Tuple[Optional[_T], ...]]: ...
@overload
def grouper(
iterable: Iterable[_T], n: int, fillvalue: _U
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
@overload
def grouper( # Deprecated interface
iterable: int, n: Iterable[_T]
) -> Iterator[Tuple[Optional[_T], ...]]: ...
@overload
def grouper( # Deprecated interface
iterable: int, n: Iterable[_T], fillvalue: _U
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
def roundrobin(*iterables: Iterable[_T]) -> Iterator[_T]: ...
def partition(
pred: Optional[Callable[[_T], object]], iterable: Iterable[_T]
) -> Tuple[Iterator[_T], Iterator[_T]]: ...
def powerset(iterable: Iterable[_T]) -> Iterator[Tuple[_T, ...]]: ...
def unique_everseen(
iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ...
) -> Iterator[_T]: ...
def unique_justseen(
iterable: Iterable[_T], key: Optional[Callable[[_T], object]] = ...
) -> Iterator[_T]: ...
@overload
def iter_except(
func: Callable[[], _T],
exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]],
first: None = ...,
) -> Iterator[_T]: ...
@overload
def iter_except(
func: Callable[[], _T],
exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]],
first: Callable[[], _U],
) -> Iterator[Union[_T, _U]]: ...
@overload
def first_true(
iterable: Iterable[_T], *, pred: Optional[Callable[[_T], object]] = ...
) -> Optional[_T]: ...
@overload
def first_true(
iterable: Iterable[_T],
default: _U,
pred: Optional[Callable[[_T], object]] = ...,
) -> Union[_T, _U]: ...
def random_product(
*args: Iterable[_T], repeat: int = ...
) -> Tuple[_T, ...]: ...
def random_permutation(
iterable: Iterable[_T], r: Optional[int] = ...
) -> Tuple[_T, ...]: ...
def random_combination(iterable: Iterable[_T], r: int) -> Tuple[_T, ...]: ...
def random_combination_with_replacement(
iterable: Iterable[_T], r: int
) -> Tuple[_T, ...]: ...
def nth_combination(
iterable: Iterable[_T], r: int, index: int
) -> Tuple[_T, ...]: ...
def prepend(value: _T, iterator: Iterable[_U]) -> Iterator[Union[_T, _U]]: ...
def convolve(signal: Iterable[_T], kernel: Iterable[_T]) -> Iterator[_T]: ...

File diff suppressed because it is too large Load diff

View file

@ -1,616 +0,0 @@
from doctest import DocTestSuite
from unittest import TestCase
from itertools import combinations
from six.moves import range
import more_itertools as mi
def load_tests(loader, tests, ignore):
# Add the doctests
tests.addTests(DocTestSuite('more_itertools.recipes'))
return tests
class AccumulateTests(TestCase):
"""Tests for ``accumulate()``"""
def test_empty(self):
"""Test that an empty input returns an empty output"""
self.assertEqual(list(mi.accumulate([])), [])
def test_default(self):
"""Test accumulate with the default function (addition)"""
self.assertEqual(list(mi.accumulate([1, 2, 3])), [1, 3, 6])
def test_bogus_function(self):
"""Test accumulate with an invalid function"""
with self.assertRaises(TypeError):
list(mi.accumulate([1, 2, 3], func=lambda x: x))
def test_custom_function(self):
"""Test accumulate with a custom function"""
self.assertEqual(
list(mi.accumulate((1, 2, 3, 2, 1), func=max)), [1, 2, 3, 3, 3]
)
class TakeTests(TestCase):
"""Tests for ``take()``"""
def test_simple_take(self):
"""Test basic usage"""
t = mi.take(5, range(10))
self.assertEqual(t, [0, 1, 2, 3, 4])
def test_null_take(self):
"""Check the null case"""
t = mi.take(0, range(10))
self.assertEqual(t, [])
def test_negative_take(self):
"""Make sure taking negative items results in a ValueError"""
self.assertRaises(ValueError, lambda: mi.take(-3, range(10)))
def test_take_too_much(self):
"""Taking more than an iterator has remaining should return what the
iterator has remaining.
"""
t = mi.take(10, range(5))
self.assertEqual(t, [0, 1, 2, 3, 4])
class TabulateTests(TestCase):
"""Tests for ``tabulate()``"""
def test_simple_tabulate(self):
"""Test the happy path"""
t = mi.tabulate(lambda x: x)
f = tuple([next(t) for _ in range(3)])
self.assertEqual(f, (0, 1, 2))
def test_count(self):
"""Ensure tabulate accepts specific count"""
t = mi.tabulate(lambda x: 2 * x, -1)
f = (next(t), next(t), next(t))
self.assertEqual(f, (-2, 0, 2))
class TailTests(TestCase):
"""Tests for ``tail()``"""
def test_greater(self):
"""Length of iterable is greater than requested tail"""
self.assertEqual(list(mi.tail(3, 'ABCDEFG')), ['E', 'F', 'G'])
def test_equal(self):
"""Length of iterable is equal to the requested tail"""
self.assertEqual(
list(mi.tail(7, 'ABCDEFG')), ['A', 'B', 'C', 'D', 'E', 'F', 'G']
)
def test_less(self):
"""Length of iterable is less than requested tail"""
self.assertEqual(
list(mi.tail(8, 'ABCDEFG')), ['A', 'B', 'C', 'D', 'E', 'F', 'G']
)
class ConsumeTests(TestCase):
"""Tests for ``consume()``"""
def test_sanity(self):
"""Test basic functionality"""
r = (x for x in range(10))
mi.consume(r, 3)
self.assertEqual(3, next(r))
def test_null_consume(self):
"""Check the null case"""
r = (x for x in range(10))
mi.consume(r, 0)
self.assertEqual(0, next(r))
def test_negative_consume(self):
"""Check that negative consumsion throws an error"""
r = (x for x in range(10))
self.assertRaises(ValueError, lambda: mi.consume(r, -1))
def test_total_consume(self):
"""Check that iterator is totally consumed by default"""
r = (x for x in range(10))
mi.consume(r)
self.assertRaises(StopIteration, lambda: next(r))
class NthTests(TestCase):
"""Tests for ``nth()``"""
def test_basic(self):
"""Make sure the nth item is returned"""
l = range(10)
for i, v in enumerate(l):
self.assertEqual(mi.nth(l, i), v)
def test_default(self):
"""Ensure a default value is returned when nth item not found"""
l = range(3)
self.assertEqual(mi.nth(l, 100, "zebra"), "zebra")
def test_negative_item_raises(self):
"""Ensure asking for a negative item raises an exception"""
self.assertRaises(ValueError, lambda: mi.nth(range(10), -3))
class AllEqualTests(TestCase):
"""Tests for ``all_equal()``"""
def test_true(self):
"""Everything is equal"""
self.assertTrue(mi.all_equal('aaaaaa'))
self.assertTrue(mi.all_equal([0, 0, 0, 0]))
def test_false(self):
"""Not everything is equal"""
self.assertFalse(mi.all_equal('aaaaab'))
self.assertFalse(mi.all_equal([0, 0, 0, 1]))
def test_tricky(self):
"""Not everything is identical, but everything is equal"""
items = [1, complex(1, 0), 1.0]
self.assertTrue(mi.all_equal(items))
def test_empty(self):
"""Return True if the iterable is empty"""
self.assertTrue(mi.all_equal(''))
self.assertTrue(mi.all_equal([]))
def test_one(self):
"""Return True if the iterable is singular"""
self.assertTrue(mi.all_equal('0'))
self.assertTrue(mi.all_equal([0]))
class QuantifyTests(TestCase):
"""Tests for ``quantify()``"""
def test_happy_path(self):
"""Make sure True count is returned"""
q = [True, False, True]
self.assertEqual(mi.quantify(q), 2)
def test_custom_predicate(self):
"""Ensure non-default predicates return as expected"""
q = range(10)
self.assertEqual(mi.quantify(q, lambda x: x % 2 == 0), 5)
class PadnoneTests(TestCase):
"""Tests for ``padnone()``"""
def test_happy_path(self):
"""wrapper iterator should return None indefinitely"""
r = range(2)
p = mi.padnone(r)
self.assertEqual([0, 1, None, None], [next(p) for _ in range(4)])
class NcyclesTests(TestCase):
"""Tests for ``nyclces()``"""
def test_happy_path(self):
"""cycle a sequence three times"""
r = ["a", "b", "c"]
n = mi.ncycles(r, 3)
self.assertEqual(
["a", "b", "c", "a", "b", "c", "a", "b", "c"],
list(n)
)
def test_null_case(self):
"""asking for 0 cycles should return an empty iterator"""
n = mi.ncycles(range(100), 0)
self.assertRaises(StopIteration, lambda: next(n))
def test_pathalogical_case(self):
"""asking for negative cycles should return an empty iterator"""
n = mi.ncycles(range(100), -10)
self.assertRaises(StopIteration, lambda: next(n))
class DotproductTests(TestCase):
"""Tests for ``dotproduct()``'"""
def test_happy_path(self):
"""simple dotproduct example"""
self.assertEqual(400, mi.dotproduct([10, 10], [20, 20]))
class FlattenTests(TestCase):
"""Tests for ``flatten()``"""
def test_basic_usage(self):
"""ensure list of lists is flattened one level"""
f = [[0, 1, 2], [3, 4, 5]]
self.assertEqual(list(range(6)), list(mi.flatten(f)))
def test_single_level(self):
"""ensure list of lists is flattened only one level"""
f = [[0, [1, 2]], [[3, 4], 5]]
self.assertEqual([0, [1, 2], [3, 4], 5], list(mi.flatten(f)))
class RepeatfuncTests(TestCase):
"""Tests for ``repeatfunc()``"""
def test_simple_repeat(self):
"""test simple repeated functions"""
r = mi.repeatfunc(lambda: 5)
self.assertEqual([5, 5, 5, 5, 5], [next(r) for _ in range(5)])
def test_finite_repeat(self):
"""ensure limited repeat when times is provided"""
r = mi.repeatfunc(lambda: 5, times=5)
self.assertEqual([5, 5, 5, 5, 5], list(r))
def test_added_arguments(self):
"""ensure arguments are applied to the function"""
r = mi.repeatfunc(lambda x: x, 2, 3)
self.assertEqual([3, 3], list(r))
def test_null_times(self):
"""repeat 0 should return an empty iterator"""
r = mi.repeatfunc(range, 0, 3)
self.assertRaises(StopIteration, lambda: next(r))
class PairwiseTests(TestCase):
"""Tests for ``pairwise()``"""
def test_base_case(self):
"""ensure an iterable will return pairwise"""
p = mi.pairwise([1, 2, 3])
self.assertEqual([(1, 2), (2, 3)], list(p))
def test_short_case(self):
"""ensure an empty iterator if there's not enough values to pair"""
p = mi.pairwise("a")
self.assertRaises(StopIteration, lambda: next(p))
class GrouperTests(TestCase):
"""Tests for ``grouper()``"""
def test_even(self):
"""Test when group size divides evenly into the length of
the iterable.
"""
self.assertEqual(
list(mi.grouper(3, 'ABCDEF')), [('A', 'B', 'C'), ('D', 'E', 'F')]
)
def test_odd(self):
"""Test when group size does not divide evenly into the length of the
iterable.
"""
self.assertEqual(
list(mi.grouper(3, 'ABCDE')), [('A', 'B', 'C'), ('D', 'E', None)]
)
def test_fill_value(self):
"""Test that the fill value is used to pad the final group"""
self.assertEqual(
list(mi.grouper(3, 'ABCDE', 'x')),
[('A', 'B', 'C'), ('D', 'E', 'x')]
)
class RoundrobinTests(TestCase):
"""Tests for ``roundrobin()``"""
def test_even_groups(self):
"""Ensure ordered output from evenly populated iterables"""
self.assertEqual(
list(mi.roundrobin('ABC', [1, 2, 3], range(3))),
['A', 1, 0, 'B', 2, 1, 'C', 3, 2]
)
def test_uneven_groups(self):
"""Ensure ordered output from unevenly populated iterables"""
self.assertEqual(
list(mi.roundrobin('ABCD', [1, 2], range(0))),
['A', 1, 'B', 2, 'C', 'D']
)
class PartitionTests(TestCase):
"""Tests for ``partition()``"""
def test_bool(self):
"""Test when pred() returns a boolean"""
lesser, greater = mi.partition(lambda x: x > 5, range(10))
self.assertEqual(list(lesser), [0, 1, 2, 3, 4, 5])
self.assertEqual(list(greater), [6, 7, 8, 9])
def test_arbitrary(self):
"""Test when pred() returns an integer"""
divisibles, remainders = mi.partition(lambda x: x % 3, range(10))
self.assertEqual(list(divisibles), [0, 3, 6, 9])
self.assertEqual(list(remainders), [1, 2, 4, 5, 7, 8])
class PowersetTests(TestCase):
"""Tests for ``powerset()``"""
def test_combinatorics(self):
"""Ensure a proper enumeration"""
p = mi.powerset([1, 2, 3])
self.assertEqual(
list(p),
[(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)]
)
class UniqueEverseenTests(TestCase):
"""Tests for ``unique_everseen()``"""
def test_everseen(self):
"""ensure duplicate elements are ignored"""
u = mi.unique_everseen('AAAABBBBCCDAABBB')
self.assertEqual(
['A', 'B', 'C', 'D'],
list(u)
)
def test_custom_key(self):
"""ensure the custom key comparison works"""
u = mi.unique_everseen('aAbACCc', key=str.lower)
self.assertEqual(list('abC'), list(u))
def test_unhashable(self):
"""ensure things work for unhashable items"""
iterable = ['a', [1, 2, 3], [1, 2, 3], 'a']
u = mi.unique_everseen(iterable)
self.assertEqual(list(u), ['a', [1, 2, 3]])
def test_unhashable_key(self):
"""ensure things work for unhashable items with a custom key"""
iterable = ['a', [1, 2, 3], [1, 2, 3], 'a']
u = mi.unique_everseen(iterable, key=lambda x: x)
self.assertEqual(list(u), ['a', [1, 2, 3]])
class UniqueJustseenTests(TestCase):
"""Tests for ``unique_justseen()``"""
def test_justseen(self):
"""ensure only last item is remembered"""
u = mi.unique_justseen('AAAABBBCCDABB')
self.assertEqual(list('ABCDAB'), list(u))
def test_custom_key(self):
"""ensure the custom key comparison works"""
u = mi.unique_justseen('AABCcAD', str.lower)
self.assertEqual(list('ABCAD'), list(u))
class IterExceptTests(TestCase):
"""Tests for ``iter_except()``"""
def test_exact_exception(self):
"""ensure the exact specified exception is caught"""
l = [1, 2, 3]
i = mi.iter_except(l.pop, IndexError)
self.assertEqual(list(i), [3, 2, 1])
def test_generic_exception(self):
"""ensure the generic exception can be caught"""
l = [1, 2]
i = mi.iter_except(l.pop, Exception)
self.assertEqual(list(i), [2, 1])
def test_uncaught_exception_is_raised(self):
"""ensure a non-specified exception is raised"""
l = [1, 2, 3]
i = mi.iter_except(l.pop, KeyError)
self.assertRaises(IndexError, lambda: list(i))
def test_first(self):
"""ensure first is run before the function"""
l = [1, 2, 3]
f = lambda: 25
i = mi.iter_except(l.pop, IndexError, f)
self.assertEqual(list(i), [25, 3, 2, 1])
class FirstTrueTests(TestCase):
"""Tests for ``first_true()``"""
def test_something_true(self):
"""Test with no keywords"""
self.assertEqual(mi.first_true(range(10)), 1)
def test_nothing_true(self):
"""Test default return value."""
self.assertIsNone(mi.first_true([0, 0, 0]))
def test_default(self):
"""Test with a default keyword"""
self.assertEqual(mi.first_true([0, 0, 0], default='!'), '!')
def test_pred(self):
"""Test with a custom predicate"""
self.assertEqual(
mi.first_true([2, 4, 6], pred=lambda x: x % 3 == 0), 6
)
class RandomProductTests(TestCase):
"""Tests for ``random_product()``
Since random.choice() has different results with the same seed across
python versions 2.x and 3.x, these tests use highly probably events to
create predictable outcomes across platforms.
"""
def test_simple_lists(self):
"""Ensure that one item is chosen from each list in each pair.
Also ensure that each item from each list eventually appears in
the chosen combinations.
Odds are roughly 1 in 7.1 * 10e16 that one item from either list will
not be chosen after 100 samplings of one item from each list. Just to
be safe, better use a known random seed, too.
"""
nums = [1, 2, 3]
lets = ['a', 'b', 'c']
n, m = zip(*[mi.random_product(nums, lets) for _ in range(100)])
n, m = set(n), set(m)
self.assertEqual(n, set(nums))
self.assertEqual(m, set(lets))
self.assertEqual(len(n), len(nums))
self.assertEqual(len(m), len(lets))
def test_list_with_repeat(self):
"""ensure multiple items are chosen, and that they appear to be chosen
from one list then the next, in proper order.
"""
nums = [1, 2, 3]
lets = ['a', 'b', 'c']
r = list(mi.random_product(nums, lets, repeat=100))
self.assertEqual(2 * 100, len(r))
n, m = set(r[::2]), set(r[1::2])
self.assertEqual(n, set(nums))
self.assertEqual(m, set(lets))
self.assertEqual(len(n), len(nums))
self.assertEqual(len(m), len(lets))
class RandomPermutationTests(TestCase):
"""Tests for ``random_permutation()``"""
def test_full_permutation(self):
"""ensure every item from the iterable is returned in a new ordering
15 elements have a 1 in 1.3 * 10e12 of appearing in sorted order, so
we fix a seed value just to be sure.
"""
i = range(15)
r = mi.random_permutation(i)
self.assertEqual(set(i), set(r))
if i == r:
raise AssertionError("Values were not permuted")
def test_partial_permutation(self):
"""ensure all returned items are from the iterable, that the returned
permutation is of the desired length, and that all items eventually
get returned.
Sampling 100 permutations of length 5 from a set of 15 leaves a
(2/3)^100 chance that an item will not be chosen. Multiplied by 15
items, there is a 1 in 2.6e16 chance that at least 1 item will not
show up in the resulting output. Using a random seed will fix that.
"""
items = range(15)
item_set = set(items)
all_items = set()
for _ in range(100):
permutation = mi.random_permutation(items, 5)
self.assertEqual(len(permutation), 5)
permutation_set = set(permutation)
self.assertLessEqual(permutation_set, item_set)
all_items |= permutation_set
self.assertEqual(all_items, item_set)
class RandomCombinationTests(TestCase):
"""Tests for ``random_combination()``"""
def test_pseudorandomness(self):
"""ensure different subsets of the iterable get returned over many
samplings of random combinations"""
items = range(15)
all_items = set()
for _ in range(50):
combination = mi.random_combination(items, 5)
all_items |= set(combination)
self.assertEqual(all_items, set(items))
def test_no_replacement(self):
"""ensure that elements are sampled without replacement"""
items = range(15)
for _ in range(50):
combination = mi.random_combination(items, len(items))
self.assertEqual(len(combination), len(set(combination)))
self.assertRaises(
ValueError, lambda: mi.random_combination(items, len(items) + 1)
)
class RandomCombinationWithReplacementTests(TestCase):
"""Tests for ``random_combination_with_replacement()``"""
def test_replacement(self):
"""ensure that elements are sampled with replacement"""
items = range(5)
combo = mi.random_combination_with_replacement(items, len(items) * 2)
self.assertEqual(2 * len(items), len(combo))
if len(set(combo)) == len(combo):
raise AssertionError("Combination contained no duplicates")
def test_pseudorandomness(self):
"""ensure different subsets of the iterable get returned over many
samplings of random combinations"""
items = range(15)
all_items = set()
for _ in range(50):
combination = mi.random_combination_with_replacement(items, 5)
all_items |= set(combination)
self.assertEqual(all_items, set(items))
class NthCombinationTests(TestCase):
def test_basic(self):
iterable = 'abcdefg'
r = 4
for index, expected in enumerate(combinations(iterable, r)):
actual = mi.nth_combination(iterable, r, index)
self.assertEqual(actual, expected)
def test_long(self):
actual = mi.nth_combination(range(180), 4, 2000000)
expected = (2, 12, 35, 126)
self.assertEqual(actual, expected)
def test_invalid_r(self):
for r in (-1, 3):
with self.assertRaises(ValueError):
mi.nth_combination([], r, 0)
def test_invalid_index(self):
with self.assertRaises(IndexError):
mi.nth_combination('abcdefg', 3, -36)
class PrependTests(TestCase):
def test_basic(self):
value = 'a'
iterator = iter('bcdefg')
actual = list(mi.prepend(value, iterator))
expected = list('abcdefg')
self.assertEqual(actual, expected)
def test_multiple(self):
value = 'ab'
iterator = iter('cdefg')
actual = tuple(mi.prepend(value, iterator))
expected = ('ab',) + tuple('cdefg')
self.assertEqual(actual, expected)