Feature parity with Python 3.13

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2019 - 2024 Max Fischer
+Copyright (c) 2019 - 2024 Max Kühn
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

asyncstdlib/__init__.py

@@ -45,7 +45,7 @@
 from .asynctools import borrow, scoped_iter, await_each, any_iter, apply, sync
 from .heapq import merge, nlargest, nsmallest
 
-__version__ = "3.12.5"
+__version__ = "3.13.0"
 
 __all__ = [
     "anext",

asyncstdlib/functools.py

@@ -7,7 +7,6 @@
     Generic,
     Generator,
     Optional,
-    Coroutine,
     AsyncContextManager,
     Type,
     cast,
@@ -66,25 +65,25 @@ def __repr__(self) -> str:
         return f"{self.__class__.__name__}({self.value!r})"
 
 
-class _FutureCachedValue(Generic[R, T]):
-    """A placeholder object to control concurrent access to a cached awaitable value.
+class _FutureCachedPropertyValue(Generic[R, T]):
+    """
+    A placeholder object to control concurrent access to a cached awaitable value
 
     When given a lock to coordinate access, only the first task to await on a
     cached property triggers the underlying coroutine. Once a value has been
     produced, all tasks are unblocked and given the same, single value.
-
     """
 
-    __slots__ = ("_get_attribute", "_instance", "_name", "_lock")
+    __slots__ = ("_func", "_instance", "_name", "_lock")
 
     def __init__(
         self,
-        get_attribute: Callable[[T], Coroutine[Any, Any, R]],
+        func: Callable[[T], Awaitable[R]],
         instance: T,
         name: str,
         lock: AsyncContextManager[Any],
     ):
-        self._get_attribute = get_attribute
+        self._func = func
         self._instance = instance
         self._name = name
         self._lock = lock
@@ -98,7 +97,6 @@ def _instance_value(self) -> Awaitable[R]:
 
         If the instance (no longer) has this attribute, it was deleted and the
         process is restarted by delegating to the descriptor.
-
         """
         try:
             return self._instance.__dict__[self._name]
@@ -116,12 +114,17 @@ async def _await_impl(self) -> R:
                     # the instance attribute is still this placeholder, and we
                     # hold the lock. Start the getter to store the value on the
                     # instance and return the value.
-                    return await self._get_attribute(self._instance)
+                    return await self._get_attribute()
 
         # another task produced a value, or the instance.__dict__ object was
         # deleted in the interim.
         return await stored
 
+    async def _get_attribute(self) -> R:
+        value = await self._func(self._instance)
+        self._instance.__dict__[self._name] = AwaitableValue(value)
+        return value
+
     def __repr__(self) -> str:
         return (
             f"<{type(self).__name__} for '{type(self._instance).__name__}."
@@ -135,9 +138,10 @@ def __init__(
         getter: Callable[[T], Awaitable[R]],
         asynccontextmanager_type: Type[AsyncContextManager[Any]] = nullcontext,
     ):
-        self.func = getter
+        self.func = self.__wrapped__ = getter
         self.attrname = None
         self.__doc__ = getter.__doc__
+        self.__module__ = getter.__module__
         self._asynccontextmanager_type = asynccontextmanager_type
 
     def __set_name__(self, owner: Any, name: str) -> None:
@@ -175,19 +179,12 @@ def __get__(
         # on this instance. It takes care of coordinating between different
         # tasks awaiting on the placeholder until the cached value has been
         # produced.
-        wrapper = _FutureCachedValue(
-            self._get_attribute, instance, name, self._asynccontextmanager_type()
+        wrapper = _FutureCachedPropertyValue(
+            self.func, instance, name, self._asynccontextmanager_type()
         )
         cache[name] = wrapper
         return wrapper
 
-    async def _get_attribute(self, instance: T) -> R:
-        value = await self.func(instance)
-        name = self.attrname
-        assert name is not None  # enforced in __get__
-        instance.__dict__[name] = AwaitableValue(value)
-        return value
-
 
 def cached_property(
     type_or_getter: Union[Type[AsyncContextManager[Any]], Callable[[T], Awaitable[R]]],

asyncstdlib/itertools.py

@@ -32,7 +32,6 @@
     zip,
     enumerate as aenumerate,
     iter as aiter,
-    tuple as atuple,
 )
 
 S = TypeVar("S")
@@ -122,17 +121,31 @@ async def accumulate(iterable, function, *, initial):
             yield value
 
 
-async def batched(iterable: AnyIterable[T], n: int) -> AsyncIterator[Tuple[T, ...]]:
+async def batched(
+    iterable: AnyIterable[T], n: int, strict: bool = False
+) -> AsyncIterator[Tuple[T, ...]]:
     """
     Batch the ``iterable`` to tuples of the length ``n``.
 
-    This lazily exhausts ``iterable`` and returns each batch as soon as it's ready.
+    This lazily exhausts ``iterable`` and returns each batch as soon as it is ready.
+    If ``strict`` is :py:data:`True` and the last batch is smaller than ``n``,
+    :py:exc:`ValueError` is raised.
     """
     if n < 1:
         raise ValueError("n must be at least one")
     async with ScopedIter(iterable) as item_iter:
-        while batch := await atuple(islice(_borrow(item_iter), n)):
-            yield batch
+        batch: list[T] = []
+        try:
+            while True:
+                batch.clear()
+                for _ in range(n):
+                    batch.append(await anext(item_iter))
+                yield tuple(batch)
+        except StopAsyncIteration:
+            if batch:
+                if strict and len(batch) < n:
+                    raise ValueError("batched(): incomplete batch") from None
+                yield tuple(batch)
 
 
 class chain(AsyncIterator[T]):

asyncstdlib/itertools.pyi

@@ -32,27 +32,33 @@ def accumulate(
     initial: T1,
 ) -> AsyncIterator[T1]: ...
 @overload
-def batched(iterable: AnyIterable[T], n: Literal[1]) -> AsyncIterator[tuple[T]]: ...
+def batched(
+    iterable: AnyIterable[T], n: Literal[1], strict: bool = ...
+) -> AsyncIterator[tuple[T]]: ...
 @overload
-def batched(iterable: AnyIterable[T], n: Literal[2]) -> AsyncIterator[tuple[T, T]]: ...
+def batched(
+    iterable: AnyIterable[T], n: Literal[2], strict: bool = ...
+) -> AsyncIterator[tuple[T, T]]: ...
 @overload
 def batched(
-    iterable: AnyIterable[T], n: Literal[3]
+    iterable: AnyIterable[T], n: Literal[3], strict: bool = ...
 ) -> AsyncIterator[tuple[T, T, T]]: ...
 @overload
 def batched(
-    iterable: AnyIterable[T], n: Literal[4]
+    iterable: AnyIterable[T], n: Literal[4], strict: bool = ...
 ) -> AsyncIterator[tuple[T, T, T, T]]: ...
 @overload
 def batched(
-    iterable: AnyIterable[T], n: Literal[5]
+    iterable: AnyIterable[T], n: Literal[5], strict: bool = ...
 ) -> AsyncIterator[tuple[T, T, T, T, T]]: ...
 @overload
 def batched(
-    iterable: AnyIterable[T], n: Literal[6]
+    iterable: AnyIterable[T], n: Literal[6], strict: bool = ...
 ) -> AsyncIterator[tuple[T, T, T, T, T, T]]: ...
 @overload
-def batched(iterable: AnyIterable[T], n: int) -> AsyncIterator[tuple[T, ...]]: ...
+def batched(
+    iterable: AnyIterable[T], n: int, strict: bool = ...
+) -> AsyncIterator[tuple[T, ...]]: ...
 
 class chain(AsyncIterator[T]):
     __slots__: tuple[str, ...]

docs/conf.py

@@ -25,7 +25,7 @@
 # -- Project information -----------------------------------------------------
 
 project = "asyncstdlib"
-author = "Max Fischer"
+author = "Max Kühn"
 copyright = f"2019-2024 {author}"
 
 # The short X.Y version

docs/source/api/itertools.rst

@@ -86,11 +86,15 @@ Iterator splitting
 
     .. versionadded:: 3.10.0
 
-.. autofunction:: batched(iterable: (async) iter T, n: int)
+.. autofunction:: batched(iterable: (async) iter T, n: int, strict: bool = False)
     :async-for: :T
 
     .. versionadded:: 3.11.0
 
+    .. versionadded:: 3.13.0
+
+        The ``strict`` parameter.
+
 .. py:function:: groupby(iterable: (async) iter T)
     :async-for: :(T, async iter T)
     :noindex:

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "flit_core.buildapi"
 dynamic = ["version", "description"]
 name = "asyncstdlib"
 authors = [
-    {name = "Max Fischer", email = "[email protected]"},
+    {name = "Max Kühn", email = "[email protected]"},
 ]
 readme = "README.rst"
 classifiers = [

unittests/test_itertools.py

@@ -79,6 +79,19 @@ async def test_batched_invalid(length):
         await a.list(a.batched(range(10), length))
 
 
+@sync
+@pytest.mark.parametrize("values", ([1, 2, 3, 4], [1, 2, 3, 4, 5], [1]))
+async def test_batched_strict(values: "list[int]"):
+    for n in range(1, len(values) + 1):
+        batches = a.batched(values, n, strict=True)
+        if len(values) % n == 0:
+            assert values == list(await a.reduce(lambda a, b: a + b, batches))
+        else:
+            assert await a.anext(batches)
+            with pytest.raises(ValueError):
+                await a.list(batches)
+
+
 @sync
 async def test_cycle():
     async for _ in a.cycle([]):