Source code for langchain_core.utils.iter

from collections import deque
from itertools import islice
from typing import (

from typing_extensions import Literal

T = TypeVar("T")

[docs]class NoLock: """Dummy lock that provides the proper interface but no protection""" def __enter__(self) -> None: pass def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> Literal[False]: return False
[docs]def tee_peer( iterator: Iterator[T], # the buffer specific to this peer buffer: Deque[T], # the buffers of all peers, including our own peers: List[Deque[T]], lock: ContextManager[Any], ) -> Generator[T, None, None]: """An individual iterator of a :py:func:`~.tee`""" try: while True: if not buffer: with lock: # Another peer produced an item while we were waiting for the lock. # Proceed with the next loop iteration to yield the item. if buffer: continue try: item = next(iterator) except StopIteration: break else: # Append to all buffers, including our own. We'll fetch our # item from the buffer again, instead of yielding it directly. # This ensures the proper item ordering if any of our peers # are fetching items concurrently. They may have buffered their # item already. for peer_buffer in peers: peer_buffer.append(item) yield buffer.popleft() finally: with lock: # this peer is done – remove its buffer for idx, peer_buffer in enumerate(peers): # pragma: no branch if peer_buffer is buffer: peers.pop(idx) break # if we are the last peer, try and close the iterator if not peers and hasattr(iterator, "close"): iterator.close()
[docs]class Tee(Generic[T]): """ Create ``n`` separate asynchronous iterators over ``iterable`` This splits a single ``iterable`` into multiple iterators, each providing the same items in the same order. All child iterators may advance separately but share the same items from ``iterable`` -- when the most advanced iterator retrieves an item, it is buffered until the least advanced iterator has yielded it as well. A ``tee`` works lazily and can handle an infinite ``iterable``, provided that all iterators advance. .. code-block:: python3 async def derivative(sensor_data): previous, current = a.tee(sensor_data, n=2) await a.anext(previous) # advance one iterator return, previous, current) Unlike :py:func:`itertools.tee`, :py:func:`~.tee` returns a custom type instead of a :py:class:`tuple`. Like a tuple, it can be indexed, iterated and unpacked to get the child iterators. In addition, its :py:meth:`~.tee.aclose` method immediately closes all children, and it can be used in an ``async with`` context for the same effect. If ``iterable`` is an iterator and read elsewhere, ``tee`` will *not* provide these items. Also, ``tee`` must internally buffer each item until the last iterator has yielded it; if the most and least advanced iterator differ by most data, using a :py:class:`list` is more efficient (but not lazy). If the underlying iterable is concurrency safe (``anext`` may be awaited concurrently) the resulting iterators are concurrency safe as well. Otherwise, the iterators are safe if there is only ever one single "most advanced" iterator. To enforce sequential use of ``anext``, provide a ``lock`` - e.g. an :py:class:`asyncio.Lock` instance in an :py:mod:`asyncio` application - and access is automatically synchronised. """
[docs] def __init__( self, iterable: Iterator[T], n: int = 2, *, lock: Optional[ContextManager[Any]] = None, ): self._iterator = iter(iterable) self._buffers: List[Deque[T]] = [deque() for _ in range(n)] self._children = tuple( tee_peer( iterator=self._iterator, buffer=buffer, peers=self._buffers, lock=lock if lock is not None else NoLock(), ) for buffer in self._buffers )
def __len__(self) -> int: return len(self._children) @overload def __getitem__(self, item: int) -> Iterator[T]: ... @overload def __getitem__(self, item: slice) -> Tuple[Iterator[T], ...]: ... def __getitem__( self, item: Union[int, slice] ) -> Union[Iterator[T], Tuple[Iterator[T], ...]]: return self._children[item] def __iter__(self) -> Iterator[Iterator[T]]: yield from self._children def __enter__(self) -> "Tee[T]": return self def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> Literal[False]: self.close() return False
[docs] def close(self) -> None: for child in self._children: child.close()
# Why this is needed safetee = Tee
[docs]def batch_iterate(size: Optional[int], iterable: Iterable[T]) -> Iterator[List[T]]: """Utility batching function. Args: size: The size of the batch. If None, returns a single batch. iterable: The iterable to batch. Returns: An iterator over the batches. """ it = iter(iterable) while True: chunk = list(islice(it, size)) if not chunk: return yield chunk