Apply ruff/Pylint rule PLW0127

PLW0127 Self-assignment of variable

The intent of the "flake8 workaround" might have been to avoid F811 errors.
These F811 errors exist only because of the ignored F401 errors. So ignore
F401 errors more precisely to clarify the situation.

Author: DimitriPapadopoulos

xarray/core/dataset.py

@@ -7966,8 +7966,6 @@ def sortby(
             variables = variables(self)
         if not isinstance(variables, list):
             variables = [variables]
-        else:
-            variables = variables
         arrays = [v if isinstance(v, DataArray) else self[v] for v in variables]
         aligned_vars = align(self, *arrays, join="left")
         aligned_self = cast("Self", aligned_vars[0])

xarray/tests/test_distributed.py

@@ -21,14 +21,14 @@
 
 from dask.distributed import Client, Lock
 from distributed.client import futures_of
-from distributed.utils_test import (  # noqa: F401
-    cleanup,
-    client,
+from distributed.utils_test import (
+    cleanup,  # noqa: F401
+    client,  # noqa: F401
     cluster,
-    cluster_fixture,
+    cluster_fixture,  # noqa: F401
     gen_cluster,
-    loop,
-    loop_in_thread,
+    loop,  # noqa: F401
+    loop_in_thread,  # noqa: F401
 )
 
 import xarray as xr
@@ -49,9 +49,6 @@
 )
 from xarray.tests.test_dataset import create_test_data
 
-loop = loop  # loop is an imported fixture, which flake8 has issues ack-ing
-client = client  # client is an imported fixture, which flake8 has issues ack-ing
-
 
 @pytest.fixture
 def tmp_netcdf_filename(tmpdir):
@@ -89,7 +86,10 @@ def tmp_netcdf_filename(tmpdir):
 
 @pytest.mark.parametrize("engine,nc_format", ENGINES_AND_FORMATS)
 def test_dask_distributed_netcdf_roundtrip(
-    loop, tmp_netcdf_filename, engine, nc_format
+    loop,  # noqa: F811
+    tmp_netcdf_filename,
+    engine,
+    nc_format,
 ):
     if engine not in ENGINES:
         pytest.skip("engine not available")
@@ -119,7 +119,8 @@ def test_dask_distributed_netcdf_roundtrip(
 
 @requires_netCDF4
 def test_dask_distributed_write_netcdf_with_dimensionless_variables(
-    loop, tmp_netcdf_filename
+    loop,  # noqa: F811
+    tmp_netcdf_filename,
 ):
     with cluster() as (s, [a, b]):
         with Client(s["address"], loop=loop):
@@ -199,7 +200,10 @@ def test_open_mfdataset_multiple_files_parallel(parallel, tmp_path):
 
 @pytest.mark.parametrize("engine,nc_format", ENGINES_AND_FORMATS)
 def test_dask_distributed_read_netcdf_integration_test(
-    loop, tmp_netcdf_filename, engine, nc_format
+    loop,  # noqa: F811
+    tmp_netcdf_filename,
+    engine,
+    nc_format,
 ):
     if engine not in ENGINES:
         pytest.skip("engine not available")
@@ -223,7 +227,7 @@ def test_dask_distributed_read_netcdf_integration_test(
 # heads-up, this is using quite private zarr API
 # https://github.com/dask/dask/blob/e04734b4d8959ba259801f2e2a490cb4ee8d891f/dask/tests/test_distributed.py#L338-L358
 @pytest.fixture
-def zarr(client):
+def zarr(client):  # noqa: F811
     zarr_lib = pytest.importorskip("zarr")
     # Zarr-Python 3 lazily allocates a dedicated thread/IO loop
     # for to execute async tasks. To avoid having this thread
@@ -248,7 +252,7 @@ def zarr(client):
 @pytest.mark.parametrize("consolidated", [True, False])
 @pytest.mark.parametrize("compute", [True, False])
 def test_dask_distributed_zarr_integration_test(
-    client,
+    client,  # noqa: F811
     zarr,
     consolidated: bool,
     compute: bool,