Import (Async)Iterator directly

`pydoclint` doesn't resolve basic types, so for the type-checking to be
able to match the yield statement we need to use the plain name.

More info at: https://jsh9.github.io/pydoclint/notes_for_users.html#2-cases-that-pydoclint-is-not-designed-to-handle

Signed-off-by: Leandro Lucarella <[email protected]>

Author: llucax

tests/conftest.py

@@ -2,8 +2,8 @@
 # Copyright © 2022 Frequenz Energy-as-a-Service GmbH
 
 """Setup for all the tests."""
-import collections.abc
 import contextlib
+from collections.abc import Iterator
 from datetime import timedelta
 
 import pytest
@@ -16,7 +16,7 @@
 
 
 @contextlib.contextmanager
-def actor_restart_limit(limit: int) -> collections.abc.Iterator[None]:
+def actor_restart_limit(limit: int) -> Iterator[None]:
     """Temporarily set the actor restart limit to a given value.
 
     Example:
@@ -41,14 +41,14 @@ def actor_restart_limit(limit: int) -> collections.abc.Iterator[None]:
 
 
 @pytest.fixture(scope="session", autouse=True)
-def disable_actor_auto_restart() -> collections.abc.Iterator[None]:
+def disable_actor_auto_restart() -> Iterator[None]:
     """Disable auto-restart of actors while running tests."""
     with actor_restart_limit(0):
         yield
 
 
 @pytest.fixture
-def actor_auto_restart_once() -> collections.abc.Iterator[None]:
+def actor_auto_restart_once() -> Iterator[None]:
     """Make actors restart only once."""
     with actor_restart_limit(1):
         yield

tests/timeseries/test_periodic_feature_extractor.py

@@ -3,8 +3,8 @@
 
 """Tests for the timeseries averager."""
 
-import collections.abc
 import contextlib
+from collections.abc import AsyncIterator
 from datetime import datetime, timedelta, timezone
 from typing import List
 
@@ -28,15 +28,15 @@
 @contextlib.asynccontextmanager
 async def init_feature_extractor(
     data: List[float], period: timedelta
-) -> collections.abc.AsyncIterator[PeriodicFeatureExtractor]:
+) -> AsyncIterator[PeriodicFeatureExtractor]:
     """
     Initialize a PeriodicFeatureExtractor with a `MovingWindow` that contains the data.
 
     Args:
         data: The data that is pushed into the moving window.
         period: The distance between two successive windows.
 
-    Returns:
+    Yields:
         PeriodicFeatureExtractor
     """
     window, sender = init_moving_window(timedelta(seconds=len(data)))
@@ -48,14 +48,14 @@ async def init_feature_extractor(
 @contextlib.asynccontextmanager
 async def init_feature_extractor_no_data(
     period: int,
-) -> collections.abc.AsyncIterator[PeriodicFeatureExtractor]:
+) -> AsyncIterator[PeriodicFeatureExtractor]:
     """
     Initialize a PeriodicFeatureExtractor with a `MovingWindow` that contains no data.
 
     Args:
         period: The distance between two successive windows.
 
-    Returns:
+    Yields:
         PeriodicFeatureExtractor
     """
     # We only need the moving window to initialize the PeriodicFeatureExtractor class.