♻️ Refactor code to use empty tuple instead of

empty list

zcollection/collection/__init__.py

@@ -86,7 +86,7 @@ def _infer_callable(
     try:
         one_partition: str = next(collection.partitions(filters=filters))
     except StopIteration:
-        return tuple()
+        return ()
 
     with collection.synchronizer:
         zds: dataset.Dataset = storage.open_zarr_group(

zcollection/collection/detail.py

@@ -472,5 +472,4 @@ def _load_and_apply_indexer(
         partition_handler.join(partition_scheme, fs.sep))
     zds: dataset.Dataset = open_zarr_group(
         partition, fs, delayed=delayed, selected_variables=selected_variables)
-    return list(
-        zds.isel({partition_properties.dim: indexer}) for indexer in items)
+    return [zds.isel({partition_properties.dim: indexer}) for indexer in items]

zcollection/collection/tests/test_collection.py

@@ -561,7 +561,7 @@ def test_insert_with_missing_variable(
     created by an algorithm.
     """
     tested_fs = request.getfixturevalue(arg)
-    zds = next(create_test_dataset_with_fillvalue()).to_xarray()
+    zds = next(create_test_dataset_with_fillvalue())
     zcollection = convenience.create_collection(
         axis='time',
         ds=zds,

zcollection/indexing/abc.py

@@ -396,13 +396,10 @@ def _table_2_indexer(self, table: pyarrow.Table,
         # Finally, we build the list of indexes of the different chunks found.
         chunks = numpy.unique(numpy.concatenate(chunks))
 
-        return (
-            tuple(  # type:ignore
-                (tuple(
-                    (name, data[name][ix0])
-                    for name in column_names), slice(start[ix0],
-                                                     stop[ix1 - 1])), )
-            for ix0, ix1 in tuple(zip(chunks[:-1], chunks[1:])))
+        return (  # force yapf to respect the line break for flake8
+            (tuple((name, data[name][ix0])
+                   for name in column_names), slice(start[ix0], stop[ix1 - 1]))
+            for ix0, ix1 in zip(chunks[:-1], chunks[1:]))
 
     def query(
         self,
@@ -425,7 +422,7 @@ def query(
             Indexer.
         """
         if len(self._partition_keys) == 0:
-            return tuple()
+            return ()
 
         logical_op = logical_op or 'and'
         if logical_op not in ('and', 'and_not', 'invert', 'or', 'xor'):

zcollection/indexing/tests/test_abc.py

@@ -241,4 +241,4 @@ def test_indexer(
     )
 
     indexer = HalfOrbitIndexer('', filesystem=fsspec.filesystem('memory'))
-    assert indexer.query({'cycle_number': [2, 4]}) == tuple()
+    assert indexer.query({'cycle_number': [2, 4]}) == ()

zcollection/meta.py

@@ -137,7 +137,7 @@ def __init__(self,
                  compressor: numcodecs.abc.Codec | None = None,
                  fill_value: Any | None = None,
                  filters: Sequence[numcodecs.abc.Codec] | None = None) -> None:
-        attrs = attrs or tuple()
+        attrs = attrs or ()
 
         #: Attributes of the variable.
         self.attrs = tuple(attrs)

zcollection/partitioning/date.py

@@ -193,7 +193,7 @@ def encode(
             >>> partitioning.encode(fields)
             (numpy.datetime64('2020-01-01'),)
         """
-        return tuple((numpy.datetime64(self._stringify(partition)), ))
+        return (numpy.datetime64(self._stringify(partition)), )
 
     def decode(
         self,

zcollection/tests/test_compressed_array.py

@@ -25,7 +25,7 @@
 #: Functions to test
 functions = [
     lambda x: x,
-    lambda x: dask.array.ufunc.expm1(x),
+    dask.array.ufunc.expm1,
     lambda x: 2 * x,
     lambda x: x / 2,
     lambda x: x**2,
@@ -36,17 +36,17 @@
     lambda x: x[:1, :, 1:3],
     lambda x: x.T,
     lambda x: dask.array.routines.transpose(x, (1, 2, 0)),
-    lambda x: dask.array.reductions.nanmean(x),
+    dask.array.reductions.nanmean,
     lambda x: dask.array.reductions.nanmean(x, axis=1),
-    lambda x: dask.array.reductions.nanmax(x),
-    lambda x: dask.array.reductions.nanmin(x),
-    lambda x: dask.array.reductions.nanprod(x),
-    lambda x: dask.array.reductions.nanstd(x),
-    lambda x: dask.array.reductions.nanvar(x),
-    lambda x: dask.array.reductions.nansum(x),
+    dask.array.reductions.nanmax,
+    dask.array.reductions.nanmin,
+    dask.array.reductions.nanprod,
+    dask.array.reductions.nanstd,
+    dask.array.reductions.nanvar,
+    dask.array.reductions.nansum,
     lambda x: dask.array.reductions.median(x, axis=0),
-    lambda x: dask.array.reductions.nanargmax(x),
-    lambda x: dask.array.reductions.nanargmin(x),
+    dask.array.reductions.nanargmax,
+    dask.array.reductions.nanargmin,
     lambda x: dask.array.reductions.nancumprod(x, axis=0),
     lambda x: dask.array.reductions.nancumsum(x, axis=0),
     lambda x: x.sum(),
@@ -74,12 +74,12 @@
         lambda x: x * 2, depth=0, trim=False, boundary='none'),
     lambda x: x.round(1),
     lambda x: x.reshape((x.shape[0] * x.shape[1], x.shape[2])),
-    lambda x: abs(x),
+    abs,
     lambda x: x > 0.5,
     lambda x: x.rechunk((4, 4, 4)),
     lambda x: x.rechunk((2, 2, 1)),
-    lambda x: numpy.isneginf(x),
-    lambda x: numpy.isposinf(x),
+    numpy.isneginf,
+    numpy.isposinf,
 ]
 # pylint: enable=unnecessary-lambda
 

zcollection/tests/test_dataset.py

@@ -482,11 +482,11 @@ def test_dataset_select_variables_by_dims(
     assert list(selected.variables) == ['var1', 'var3', 'var4', 'var6']
     assert selected.dimensions == {'x': 10, 'y': 10, 'a': 20, 'b': 20}
 
-    selected = zds.select_variables_by_dims(tuple())
+    selected = zds.select_variables_by_dims(())
     assert list(selected.variables) == ['var7']
     assert selected.dimensions == {}
 
-    selected = zds.select_variables_by_dims(tuple(), predicate=False)
+    selected = zds.select_variables_by_dims((), predicate=False)
     assert list(selected.variables) == [
         'var1', 'var2', 'var3', 'var4', 'var5', 'var6'
     ]

zcollection/variable/abc.py

@@ -420,7 +420,7 @@ def set_for_insertion(self: T) -> T:
                             name=self.name,
                             array=self.array,
                             dimensions=self.dimensions,
-                            attrs=tuple(),
+                            attrs=(),
                             compressor=self.compressor,
                             fill_value=self.fill_value,
                             filters=self.filters)