fix: fix ruff c408 in astropy/units

.ruff.toml

@@ -277,7 +277,6 @@ lint.unfixable = [
 ]
 "astropy/timeseries/*" = ["C408"]
 "astropy/units/*" = [
-    "C408",  # unnecessary-collection-call
     "F821",  # undefined-name
     "N812",  # lowercase-imported-as-non-lowercase
 ]

astropy/units/equivalencies.py

@@ -52,7 +52,7 @@ class Equivalency(UserList):
     def __init__(self, equiv_list, name="", kwargs=None):
         self.data = equiv_list
         self.name = [name]
-        self.kwargs = [kwargs] if kwargs is not None else [dict()]
+        self.kwargs = [kwargs] if kwargs is not None else [{}]
 
     def __add__(self, other):
         if isinstance(other, Equivalency):

astropy/units/quantity.py

@@ -675,7 +675,7 @@ def __array_ufunc__(self, function, method, *inputs, **kwargs):
             return self._result_as_quantity(result, unit, out)
 
         except (TypeError, ValueError, AttributeError) as e:
-            out_normalized = kwargs.get("out", tuple())
+            out_normalized = kwargs.get("out", ())
             inputs_and_outputs = inputs + out_normalized
             ignored_ufunc = (
                 None,

astropy/units/quantity_helper/function_helpers.py

@@ -313,7 +313,7 @@ def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None):
         neginf = x._to_own_unit(neginf)
     return (
         (x.view(np.ndarray),),
-        dict(copy=True, nan=nan, posinf=posinf, neginf=neginf),
+        {"copy": True, "nan": nan, "posinf": posinf, "neginf": neginf},
         x.unit,
         None,
     )
@@ -1264,12 +1264,12 @@ def merge_arrays(
 
     return (
         (arrays,),
-        dict(
-            fill_value=fill_value,
-            flatten=flatten,
-            usemask=usemask,
-            asrecarray=asrecarray,
-        ),
+        {
+            "fill_value": fill_value,
+            "flatten": flatten,
+            "usemask": usemask,
+            "asrecarray": asrecarray,
+        },
         unit,
         None,
     )

astropy/units/tests/test_equivalencies.py

@@ -963,7 +963,7 @@ def test_add_equivelencies():
     assert isinstance(e1, Equivalency)
     assert e1.name == ["pixel_scale", "temperature_energy"]
     assert isinstance(e1.kwargs, list)
-    assert e1.kwargs == [{"pixscale": 10 * u.arcsec / u.pix}, dict()]
+    assert e1.kwargs == [{"pixscale": 10 * u.arcsec / u.pix}, {}]
 
     e2 = u.pixel_scale(10 * u.arcsec / u.pixel) + [1, 2, 3]
     assert isinstance(e2, list)

astropy/units/tests/test_physical.py

@@ -267,7 +267,7 @@ def test_physical_type_as_set(unit, expected_set):
 
 def test_physical_type_iteration():
     """Test iterating through different physical type names."""
-    physical_type_names = list(pressure)
+    physical_type_names = [pressure]
     assert physical_type_names == ["energy density", "pressure", "stress"]
 
 
@@ -377,7 +377,7 @@ def test_physical_type_hash():
     assert dictionary[length] == 42
 
 
-@pytest.mark.parametrize("multiplicand", [list(), 42, 0, -1])
+@pytest.mark.parametrize("multiplicand", [[], 42, 0, -1])
 def test_physical_type_multiplication(multiplicand):
     """
     Test that multiplication of a physical type returns `NotImplemented`

astropy/units/tests/test_quantity.py

@@ -1709,8 +1709,8 @@ def __array_finalize__(self, obj):
                     self.my_attr = obj.my_attr
 
         self.MyArray = MyArray
-        self.MyQuantity1 = type("MyQuantity1", (u.Quantity, MyArray), dict(my_attr="1"))
-        self.MyQuantity2 = type("MyQuantity2", (MyArray, u.Quantity), dict(my_attr="2"))
+        self.MyQuantity1 = type("MyQuantity1", (u.Quantity, MyArray), {"my_attr": "1"})
+        self.MyQuantity2 = type("MyQuantity2", (MyArray, u.Quantity), {"my_attr": "2"})
 
     def test_setup(self):
         mq1 = self.MyQuantity1(10, u.m)

astropy/units/tests/test_quantity_non_ufuncs.py

@@ -1425,7 +1425,7 @@ def test_histogram(self):
             [125, 200] * u.cm,
             weights=weights,
             value_args=(x.value, [1.25, 2.0]),
-            value_kwargs=dict(weights=weights.value),
+            value_kwargs={"weights": weights.value},
             expected_units=(weights.unit, x.unit),
         )
         # With weights and density.
@@ -1436,7 +1436,7 @@ def test_histogram(self):
             weights=weights,
             density=True,
             value_args=(x.value, [1.25, 2.0]),
-            value_kwargs=dict(weights=weights.value),
+            value_kwargs={"weights": weights.value},
             expected_units=(weights.unit / x.unit, x.unit),
         )
 
@@ -1464,7 +1464,7 @@ def test_histogram_range(self, range):
             self.x,
             range=range,
             value_args=[self.x.value],
-            value_kwargs=dict(range=self._range_value(range, self.x.unit)),
+            value_kwargs={"range": self._range_value(range, self.x.unit)},
             expected_units=(None, self.x.unit),
         )
 
@@ -1524,7 +1524,7 @@ def test_histogram2d(self):
             y,
             weights=weights,
             value_args=(x.value, y.value),
-            value_kwargs=dict(weights=weights.value),
+            value_kwargs={"weights": weights.value},
             expected_units=(weights.unit, x.unit, y.unit),
         )
         # Check quantity bin sizes.
@@ -1545,7 +1545,7 @@ def test_histogram2d(self):
             y.value,
             bins=[5, inb2_y],
             value_args=(x.value, y.value),
-            value_kwargs=dict(bins=[5, np.array([0, 2.5, 100.0])]),
+            value_kwargs={"bins": [5, np.array([0, 2.5, 100.0])]},
             expected_units=(None, u.one, u.one),
         )
 
@@ -1582,12 +1582,12 @@ def test_histogram2d_range(self, range):
             self.y,
             range=range,
             value_args=[self.x.value, self.y.value],
-            value_kwargs=dict(
-                range=[
+            value_kwargs={
+                "range": [
                     self._range_value(r, un)
                     for (r, un) in zip(range, (self.x.unit, self.y.unit))
                 ]
-            ),
+            },
             expected_units=(None, self.x.unit, self.y.unit),
         )
 
@@ -1622,7 +1622,7 @@ def test_histogramdd(self):
             sample,
             weights=weights,
             value_args=(sample_values,),
-            value_kwargs=dict(weights=weights.value),
+            value_kwargs={"weights": weights.value},
             expected_units=(weights.unit, sample_units),
         )
         # Check quantity bin sizes.
@@ -1641,7 +1641,7 @@ def test_histogramdd(self):
             sample_values,
             bins=[5, inb2_y],
             value_args=(sample_values,),
-            value_kwargs=dict(bins=[5, np.array([0, 2.5, 100.0])]),
+            value_kwargs={"bins": [5, np.array([0, 2.5, 100.0])]},
             expected_units=(None, (u.one, u.one)),
         )
         # For quantities, it is probably not that likely one would pass
@@ -1696,12 +1696,12 @@ def test_histogramdd_range(self, range):
             (self.x, self.y),
             range=range,
             value_args=[(self.x.value, self.y.value)],
-            value_kwargs=dict(
-                range=[
+            value_kwargs={
+                "range": [
                     self._range_value(r, un)
                     for (r, un) in zip(range, (self.x.unit, self.y.unit))
                 ]
-            ),
+            },
             expected_units=(None, (self.x.unit, self.y.unit)),
         )
 
@@ -1914,9 +1914,9 @@ def check2(self, function, *args, **kwargs):
     @pytest.mark.parametrize(
         "kwargs",
         (
-            dict(return_index=True, return_inverse=True),
-            dict(return_counts=True),
-            dict(return_index=True, return_inverse=True, return_counts=True),
+            {"return_index": True, "return_inverse": True},
+            {"return_count": True},
+            {"return_index": True, "return_inverse": True, "return_counts": True},
         ),
     )
     def test_unique(self, kwargs):
@@ -1926,16 +1926,16 @@ def test_unique(self, kwargs):
     @pytest.mark.parametrize(
         "kwargs",
         (
-            dict(axis=0),
-            dict(axis=1),
-            dict(return_counts=True, return_inverse=False, axis=1),
+            {"axis": 0},
+            {"axis": 1},
+            {"return_counts": True, "return_inverse": False, "axis": 1},
         ),
     )
     def test_unique_more_complex(self, kwargs):
         self.check1(np.unique, **kwargs)
 
     @needs_array_function
-    @pytest.mark.parametrize("kwargs", (dict(), dict(return_indices=True)))
+    @pytest.mark.parametrize("kwargs", ({}, {"return_indices": True}))
     def test_intersect1d(self, kwargs):
         self.check2(np.intersect1d, **kwargs)