Apply some ruff/Perflint rules (PERF)

ome_zarr/csv.py

@@ -114,16 +114,15 @@ def dict_to_zarr(
     if plate_attrs is None and not multiscales:
         raise Exception("zarr_path must be to plate.zarr or image.zarr")
 
-    labels_paths = []
     if plate_attrs is not None:
         # look for 'label/0' under the first field of each Well
         field = "0"
-        for w in plate_attrs.get("wells", []):
-            labels_paths.append(
-                os.path.join(zarr_path, w["path"], field, "labels", "0")
-            )
+        labels_paths = [
+            os.path.join(zarr_path, w["path"], field, "labels", "0")
+            for w in plate_attrs.get("wells", [])
+        ]
     else:
-        labels_paths.append(os.path.join(zarr_path, "labels", "0"))
+        labels_paths = [os.path.join(zarr_path, "labels", "0")]
 
     for path_to_labels in labels_paths:
         label_group = zarr_open(path_to_labels)

ome_zarr/reader.py

@@ -555,9 +555,9 @@ def get_tile(row: int, col: int) -> da.core.Array:
         lazy_rows = []
         # For level 0, return whole image for each tile
         for row in range(self.row_count):
-            lazy_row: list[da.Array] = []
-            for col in range(self.column_count):
-                lazy_row.append(get_tile(row, col))
+            lazy_row: list[da.Array] = [
+                get_tile(row, col) for col in range(self.column_count)
+            ]
             lazy_rows.append(da.concatenate(lazy_row, axis=len(self.axes) - 1))
         return da.concatenate(lazy_rows, axis=len(self.axes) - 2)
 

tests/test_starting_points.py

@@ -15,9 +15,7 @@ def initdir(self, tmpdir):
         create_zarr(str(self.path))
 
     def matches(self, node: Node, expected: list[type[Spec]]):
-        found: list[type[Spec]] = list()
-        for spec in node.specs:
-            found.append(type(spec))
+        found: list[type[Spec]] = [type(spec) for spec in node.specs]
 
         expected_names = sorted(x.__name__ for x in expected)
         found_names = sorted(x.__name__ for x in found)