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"""
This module provides generator utilities for batching items from
iterables and async iterables.
Functions:
abatcher(generator, batch_size=None, interval=None):
Asyncio generator wrapper that returns items with a given batch
size or interval (whichever is reached first).
batcher(iterable, batch_size=10):
Generator wrapper that returns items with a given batch size.
"""
import asyncio
import time
import python_utils
from python_utils import types
_T = types.TypeVar('_T')
async def abatcher(
generator: types.Union[
types.AsyncGenerator[_T, None],
types.AsyncIterator[_T],
],
batch_size: types.Optional[int] = None,
interval: types.Optional[types.delta_type] = None,
) -> types.AsyncGenerator[types.List[_T], None]:
"""
Asyncio generator wrapper that returns items with a given batch size or
interval (whichever is reached first).
Args:
generator: The async generator or iterator to batch.
batch_size (types.Optional[int], optional): The number of items per
batch. Defaults to None.
interval (types.Optional[types.delta_type], optional): The time
interval to wait before yielding a batch. Defaults to None.
Yields:
types.AsyncGenerator[types.List[_T], None]: A generator that yields
batches of items.
"""
batch: types.List[_T] = []
assert batch_size or interval, 'Must specify either batch_size or interval'
# If interval is specified, use it to determine when to yield the batch
# Alternatively set a really long timeout to keep the code simpler
if interval:
interval_s = python_utils.delta_to_seconds(interval)
else:
# Set the timeout to 10 years
interval_s = 60 * 60 * 24 * 365 * 10.0
next_yield: float = time.perf_counter() + interval_s
done: types.Set[asyncio.Task[_T]]
pending: types.Set[asyncio.Task[_T]] = set()
while True:
try:
done, pending = await asyncio.wait(
pending
or [
asyncio.create_task(
types.cast(
types.Coroutine[None, None, _T],
generator.__anext__(),
)
),
],
timeout=interval_s,
return_when=asyncio.FIRST_COMPLETED,
)
if done:
for result in done:
batch.append(result.result())
except StopAsyncIteration:
if batch:
yield batch
break
if batch_size is not None and len(batch) == batch_size:
yield batch
batch = []
if interval and batch and time.perf_counter() > next_yield:
yield batch
batch = []
# Always set the next yield time to the current time. If the
# loop is running slow due to blocking functions we do not
# want to burst too much
next_yield = time.perf_counter() + interval_s
def batcher(
iterable: types.Iterable[_T],
batch_size: int = 10,
) -> types.Generator[types.List[_T], None, None]:
"""
Generator wrapper that returns items with a given batch size.
Args:
iterable (types.Iterable[_T]): The iterable to batch.
batch_size (int, optional): The number of items per batch. Defaults
to 10.
Yields:
types.Generator[types.List[_T], None, None]: A generator that yields
batches of items.
"""
batch: types.List[_T] = []
for item in iterable:
batch.append(item)
if len(batch) == batch_size:
yield batch
batch = []
if batch:
yield batch
|
