Apply ruff preview rule

src/zarr/core/metadata/v2.py

@@ -267,11 +267,10 @@ def parse_filters(data: object) -> tuple[numcodecs.abc.Codec, ...] | None:
     """
     Parse a potential tuple of filters
     """
-    out: list[numcodecs.abc.Codec] = []
-
     if data is None:
         return data
     if isinstance(data, Iterable):
+        out: list[numcodecs.abc.Codec] = []
         for idx, val in enumerate(data):
             if isinstance(val, numcodecs.abc.Codec):
                 out.append(val)

tests/conftest.py

@@ -109,7 +109,7 @@ async def store2(request: pytest.FixtureRequest, tmpdir: LEGACY_PATH) -> Store:
 def sync_store(request: pytest.FixtureRequest, tmp_path: LEGACY_PATH) -> Store:
     result = sync(parse_store(request.param, str(tmp_path)))
     if not isinstance(result, Store):
-        raise TypeError("Wrong store class returned by test fixture! got " + result + " instead")
+        raise TypeError(f"Wrong store class returned by test fixture! got {result} instead")
     return result
 
 

tests/test_codec_entrypoints.py

@@ -25,7 +25,7 @@ def set_path() -> Generator[None, None, None]:
 @pytest.mark.usefixtures("set_path")
 @pytest.mark.parametrize("codec_name", ["TestEntrypointCodec", "TestEntrypointGroup.Codec"])
 def test_entrypoint_codec(codec_name: str) -> None:
-    config.set({"codecs.test": "package_with_entrypoint." + codec_name})
+    config.set({"codecs.test": f"package_with_entrypoint.{codec_name}"})
     cls_test = zarr.registry.get_codec_class("test")
     assert cls_test.__qualname__ == codec_name
 
@@ -42,7 +42,7 @@ def test_entrypoint_pipeline() -> None:
 def test_entrypoint_buffer(buffer_name: str) -> None:
     config.set(
         {
-            "buffer": "package_with_entrypoint." + buffer_name,
+            "buffer": f"package_with_entrypoint.{buffer_name}",
             "ndbuffer": "package_with_entrypoint.TestEntrypointNDBuffer",
         }
     )

tests/test_properties.py

@@ -10,6 +10,8 @@
 
 pytest.importorskip("hypothesis")
 
+from itertools import starmap
+
 import hypothesis.extra.numpy as npst
 import hypothesis.strategies as st
 from hypothesis import assume, given, settings
@@ -60,7 +62,7 @@ def deep_equal(a: Any, b: Any) -> bool:
     if isinstance(a, np.ndarray) and isinstance(b, np.ndarray):
         if a.shape != b.shape:
             return False
-        return all(deep_equal(x, y) for x, y in zip(a.flat, b.flat, strict=False))
+        return all(starmap(deep_equal, zip(a.flat, b.flat, strict=False)))
 
     if isinstance(a, dict) and isinstance(b, dict):
         if set(a.keys()) != set(b.keys()):
@@ -70,7 +72,7 @@ def deep_equal(a: Any, b: Any) -> bool:
     if isinstance(a, (list, tuple)) and isinstance(b, (list, tuple)):
         if len(a) != len(b):
             return False
-        return all(deep_equal(x, y) for x, y in zip(a, b, strict=False))
+        return all(starmap(deep_equal, zip(a, b, strict=False)))
 
     return a == b