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# Copyright 2022 Amethyst Reese
# Licensed under the MIT license
"""
Async-compatible version of itertools standard library functions.
These functions build on top of the async builtins components,
enabling use of both standard iterables and async iterables, without
needing to use if/else clauses or awkward logic. Standard iterables
get wrapped in async generators, and all functions are designed for
use with `await`, `async for`, etc.
See https://docs.python.org/3/library/itertools.html for reference.
"""
import asyncio
import builtins
import itertools
import operator
from typing import Any, AsyncIterator, List, Optional, overload, Tuple
from .builtins import enumerate, iter, list, next, zip
from .helpers import maybe_await
from .types import (
Accumulator,
AnyFunction,
AnyIterable,
AnyIterableIterable,
AnyStop,
KeyFunction,
N,
Predicate,
R,
T,
)
async def accumulate(
itr: AnyIterable[T], func: Accumulator[T] = operator.add
) -> AsyncIterator[T]:
"""
Yield the running accumulation of an iterable and operator.
Accepts both a standard function or a coroutine for accumulation.
Example::
data = [1, 2, 3, 4]
async def mul(a, b):
return a * b
async for total in accumulate(data, func=mul):
... # 1, 2, 6, 24
"""
itr = iter(itr)
try:
total: T = await next(itr)
except AnyStop:
return
yield total
async for item in itr:
total = await maybe_await(func(total, item))
yield total
class Chain:
def __call__(self, *itrs: AnyIterable[T]) -> AsyncIterator[T]:
"""
Yield values from one or more iterables in series.
Consumes the first iterable lazily, in entirety, then the second, and so on.
Example::
async for value in chain([1, 2, 3], [7, 8, 9]):
... # 1, 2, 3, 7, 8, 9
"""
return self.from_iterable(itrs)
async def from_iterable(self, itrs: AnyIterableIterable[T]) -> AsyncIterator[T]:
"""
Like chain, but takes an iterable of iterables.
Alias for chain(*itrs)
"""
async for itr in iter(itrs):
async for item in iter(itr):
yield item
chain = Chain()
async def combinations(itr: AnyIterable[T], r: int) -> AsyncIterator[Tuple[T, ...]]:
"""
Yield r length subsequences from the given iterable.
Simple wrapper around itertools.combinations for asyncio.
This will consume the entire iterable before yielding values.
Example::
async for value in combinations(range(4), 3):
... # (0, 1, 2), (0, 1, 3), (0, 2, 3), (1, 2, 3)
"""
pool: List[T] = await list(itr)
for value in itertools.combinations(pool, r):
yield value
async def combinations_with_replacement(
itr: AnyIterable[T], r: int
) -> AsyncIterator[Tuple[T, ...]]:
"""
Yield r length subsequences from the given iterable with replacement.
Simple wrapper around itertools.combinations_with_replacement.
This will consume the entire iterable before yielding values.
Example::
async for value in combinations_with_replacement("ABC", 2):
... # ("A", "A"), ("A", "B"), ("A", "C"), ("B", "B"), ...
"""
pool: List[T] = await list(itr)
for value in itertools.combinations_with_replacement(pool, r):
yield value
async def compress(
itr: AnyIterable[T], selectors: AnyIterable[Any]
) -> AsyncIterator[T]:
"""
Yield elements only when the corresponding selector evaluates to True.
Stops when either the iterable or the selectors have been exhausted.
Example::
async for value in compress(range(5), [1, 0, 0, 1, 1]):
... # 0, 3, 4
"""
async for value, selector in zip(itr, selectors):
if selector:
yield value
async def count(start: N = 0, step: N = 1) -> AsyncIterator[N]:
"""
Yield an infinite series, starting at the given value and increasing by step.
Example::
async for value in counter(10, -1):
... # 10, 9, 8, 7, ...
"""
value = start
while True:
yield value
value += step
async def cycle(itr: AnyIterable[T]) -> AsyncIterator[T]:
"""
Yield a repeating series from the given iterable.
Lazily consumes the iterable when the next value is needed, and caching
the values in memory for future iterations of the series.
Example::
async for value in cycle([1, 2]):
... # 1, 2, 1, 2, 1, 2, ...
"""
items = []
async for item in iter(itr):
yield item
items.append(item)
while True:
for item in items:
yield item
async def dropwhile(
predicate: Predicate[T], iterable: AnyIterable[T]
) -> AsyncIterator[T]:
"""
Drops all items until the predicate evaluates False; yields all items afterwards.
Accepts both standard functions and coroutines for the predicate.
Example::
def pred(x):
return x < 4
async for item in dropwhile(pred, range(6)):
... # 4, 5, 6
"""
itr = iter(iterable)
async for item in itr:
if not await maybe_await(predicate(item)):
yield item
break
async for item in itr:
yield item
async def filterfalse(
predicate: Predicate[T], iterable: AnyIterable[T]
) -> AsyncIterator[T]:
"""
Yield items from the iterable only when the predicate evaluates to False.
Accepts both standard functions and coroutines for the predicate.
Example::
def pred(x):
return x < 4
async for item in filterfalse(pred, range(6)):
... # 4, 5
"""
async for item in iter(iterable):
if not await maybe_await(predicate(item)):
yield item
@overload
def groupby(itr: AnyIterable[T]) -> AsyncIterator[Tuple[T, List[T]]]: # pragma: nocover
pass
@overload
def groupby(
itr: AnyIterable[T], key: KeyFunction[T, R]
) -> AsyncIterator[Tuple[R, List[T]]]: # pragma: nocover
pass
async def groupby(
itr: AnyIterable[T], key: Optional[KeyFunction[T, R]] = None
) -> AsyncIterator[Tuple[Any, List[T]]]:
"""
Yield consecutive keys and groupings from the given iterable.
Items will be grouped based on the key function, which defaults to
the identity of each item. Accepts both standard functions and
coroutines for the key function. Suggest sorting by the key
function before using groupby.
Example::
data = ["A", "a", "b", "c", "C", "c"]
async for key, group in groupby(data, key=str.lower):
key # "a", "b", "c"
group # ["A", "a"], ["b"], ["c", "C", "c"]
"""
if key is None:
key = lambda x: x # noqa: E731
grouping: List[T] = []
it = iter(itr)
try:
item = await next(it)
except StopAsyncIteration:
return
grouping = [item]
j = await maybe_await(key(item))
async for item in it:
k = await maybe_await(key(item))
if k != j:
yield j, grouping
grouping = [item]
else:
grouping.append(item)
j = k
yield j, grouping
@overload
def islice(
itr: AnyIterable[T], __stop: Optional[int]
) -> AsyncIterator[T]: # pragma: nocover
pass
@overload
def islice(
itr: AnyIterable[T], __start: int, __stop: Optional[int], __step: int = 1
) -> AsyncIterator[T]: # pragma: nocover
pass
async def islice(itr: AnyIterable[T], *args: Optional[int]) -> AsyncIterator[T]:
"""
Yield selected items from the given iterable.
islice(iterable, stop)
islice(iterable, start, stop[, step])
Starting from the start index (or zero), stopping at the stop
index (or until exhausted), skipping items if step > 0.
Example::
data = range(10)
async for item in islice(data, 5):
... # 0, 1, 2, 3, 4
async for item in islice(data, 2, 5):
... # 2, 3, 4
async for item in islice(data, 1, 7, 2):
... # 1, 3, 5
"""
start = 0
step = 1
if not args:
raise ValueError("must pass stop index")
if len(args) == 1:
(stop,) = args
elif len(args) == 2:
start, stop = args # type: ignore
elif len(args) == 3:
start, stop, step = args # type: ignore
else:
raise ValueError("too many arguments given")
assert start >= 0 and (stop is None or stop >= 0) and step >= 0
step = max(1, step)
if stop == 0:
return
async for index, item in enumerate(itr):
if index >= start and (index - start) % step == 0:
yield item
if stop is not None and index + 1 >= stop:
break
async def permutations(
itr: AnyIterable[T], r: Optional[int] = None
) -> AsyncIterator[Tuple[T, ...]]:
"""
Yield r length permutations of elements in the iterable.
Simple wrapper around itertools.combinations for asyncio.
This will consume the entire iterable before yielding values.
Example::
async for value in permutations(range(3)):
... # (0, 1, 2), (0, 2, 1), (1, 0, 2), ...
"""
pool: List[T] = await list(itr)
for value in itertools.permutations(pool, r):
yield value
async def product(
*itrs: AnyIterable[T], repeat: int = 1
) -> AsyncIterator[Tuple[T, ...]]:
"""
Yield cartesian products of all iterables.
Simple wrapper around itertools.combinations for asyncio.
This will consume all iterables before yielding any values.
Example::
async for value in product("abc", "xy"):
... # ("a", "x"), ("a", "y"), ("b", "x"), ...
async for value in product(range(3), repeat=3):
... # (0, 0, 0), (0, 0, 1), (0, 0, 2), ...
"""
pools = await asyncio.gather(*[list(itr) for itr in itrs])
for value in itertools.product(*pools, repeat=repeat):
yield value
async def repeat(elem: T, n: int = -1) -> AsyncIterator[T]:
"""
Yield the given value repeatedly, forever or up to n times.
Example::
async for value in repeat(7):
... # 7, 7, 7, 7, 7, 7, ...
"""
while True:
if n == 0:
break
yield elem
n -= 1
async def starmap(
fn: AnyFunction[R], iterable: AnyIterableIterable[Any]
) -> AsyncIterator[R]:
"""
Yield values from a function using an iterable of iterables for arguments.
Each iterable contained within will be unpacked and consumed before
executing the function or coroutine.
Example::
data = [(1, 1), (1, 1, 1), (2, 2)]
async for value in starmap(operator.add, data):
... # 2, 3, 4
"""
async for itr in iter(iterable):
args = await list(itr)
yield await maybe_await(fn(*args))
async def takewhile(
predicate: Predicate[T], iterable: AnyIterable[T]
) -> AsyncIterator[T]:
"""
Yield values from the iterable until the predicate evaluates False.
Accepts both standard functions and coroutines for the predicate.
Example::
def pred(x):
return x < 4
async for value in takewhile(pred, range(8)):
... # 0, 1, 2, 3
"""
async for item in iter(iterable):
if await maybe_await(predicate(item)):
yield item
else:
break
def tee(itr: AnyIterable[T], n: int = 2) -> Tuple[AsyncIterator[T], ...]:
"""
Return n iterators that each yield items from the given iterable.
The first iterator lazily fetches from the original iterable, and then
queues the values for the other iterators to yield when needed.
Caveat: all iterators are dependent on the first iterator – if it is
consumed more slowly than the rest, the other consumers will be blocked
until the first iterator continues forward. Similarly, if the first
iterator is consumed more quickly than the rest, more memory will be
used in keeping values in the queues until the other iterators finish
consuming them.
Example::
it1, it2 = tee(range(5), n=2)
async for value in it1:
... # 0, 1, 2, 3, 4
async for value in it2:
... # 0, 1, 2, 3, 4
"""
assert n > 0
sentinel = object()
queues: List[asyncio.Queue] = [asyncio.Queue() for k in range(n)]
async def gen(k: int, q: asyncio.Queue) -> AsyncIterator[T]:
if k == 0:
try:
async for value in iter(itr):
await asyncio.gather(
*[queue.put((None, value)) for queue in queues[1:]]
)
yield value
except Exception as e:
await asyncio.gather(*[queue.put((e, None)) for queue in queues[1:]])
raise
await asyncio.gather(*[queue.put((None, sentinel)) for queue in queues[1:]])
else:
while True:
error, value = await q.get()
if error is not None:
raise error
if value is sentinel:
break
yield value
return tuple(gen(k, q) for k, q in builtins.enumerate(queues))
async def zip_longest(
*itrs: AnyIterable[Any], fillvalue: Any = None
) -> AsyncIterator[Tuple[Any, ...]]:
"""
Yield a tuple of items from mixed iterables until all are consumed.
If shorter iterables are exhausted, the default value will be used
until all iterables are exhausted.
Example::
a = range(3)
b = range(5)
async for a, b in zip_longest(a, b, fillvalue=-1):
a # 0, 1, 2, -1, -1
b # 0, 1, 2, 3, 4
"""
its: List[AsyncIterator[Any]] = [iter(itr) for itr in itrs]
itr_count = len(its)
finished = 0
while True:
values = await asyncio.gather(
*[it.__anext__() for it in its], return_exceptions=True
)
for idx, value in builtins.enumerate(values):
if isinstance(value, AnyStop):
finished += 1
values[idx] = fillvalue
its[idx] = repeat(fillvalue)
elif isinstance(value, BaseException):
raise value
if finished >= itr_count:
break
yield tuple(values)