Merge pull request numpy#26882 from DimitriPapadopoulos/UP

MAINT: start applying ruff/pyupgrade rules (UP)

Author: charris

benchmarks/benchmarks/bench_ufunc.py

@@ -31,7 +31,7 @@
 
 all_ufuncs = (getattr(np, name, None) for name in dir(np))
 all_ufuncs = set(filter(lambda f: isinstance(f, np.ufunc), all_ufuncs))
-bench_ufuncs = set((getattr(np, name, None) for name in ufuncs))
+bench_ufuncs = set(getattr(np, name, None) for name in ufuncs)
 
 missing_ufuncs = all_ufuncs - bench_ufuncs
 if len(missing_ufuncs) > 0:
@@ -497,7 +497,7 @@ def time_floor_divide_int(self, dtype, size):
 class Scalar(Benchmark):
     def setup(self):
         self.x = np.asarray(1.0)
-        self.y = np.asarray((1.0 + 1j))
+        self.y = np.asarray(1.0 + 1j)
         self.z = complex(1.0, 1.0)
 
     def time_add_scalar(self):

numpy/_core/tests/test_array_coercion.py

@@ -38,7 +38,7 @@ def subclass(a):
 
     yield subclass
 
-    class _SequenceLike():
+    class _SequenceLike:
         # Older NumPy versions, sometimes cared whether a protocol array was
         # also _SequenceLike.  This shouldn't matter, but keep it for now
         # for __array__ and not the others.

numpy/_core/tests/test_indexing.py

@@ -983,7 +983,7 @@ def _get_multi_index(self, arr, indices):
             elif indx is None:
                 # this is like taking a slice with one element from a new axis:
                 indices.append(['n', np.array([0], dtype=np.intp)])
-                arr = arr.reshape((arr.shape[:ax] + (1,) + arr.shape[ax:]))
+                arr = arr.reshape(arr.shape[:ax] + (1,) + arr.shape[ax:])
                 continue
             if isinstance(indx, np.ndarray) and indx.dtype == bool:
                 if indx.shape != arr.shape[ax:ax+indx.ndim]:
@@ -998,9 +998,9 @@ def _get_multi_index(self, arr, indices):
                     flat_indx = np.array([0]*indx.sum(), dtype=np.intp)
                 # concatenate axis into a single one:
                 if indx.ndim != 0:
-                    arr = arr.reshape((arr.shape[:ax]
+                    arr = arr.reshape(arr.shape[:ax]
                                   + (np.prod(arr.shape[ax:ax+indx.ndim]),)
-                                  + arr.shape[ax+indx.ndim:]))
+                                  + arr.shape[ax+indx.ndim:])
                     indx = flat_indx
                 else:
                     # This could be changed, a 0-d boolean index can
@@ -1067,9 +1067,9 @@ def _get_multi_index(self, arr, indices):
                 # First of all, reshape arr to combine fancy axes into one:
                 orig_shape = arr.shape
                 orig_slice = orig_shape[ax:ax + len(indx[1:])]
-                arr = arr.reshape((arr.shape[:ax]
+                arr = arr.reshape(arr.shape[:ax]
                                     + (np.prod(orig_slice).astype(int),)
-                                    + arr.shape[ax + len(indx[1:]):]))
+                                    + arr.shape[ax + len(indx[1:]):])
 
                 # Check if broadcasting works
                 res = np.broadcast(*indx[1:])
@@ -1103,9 +1103,9 @@ def _get_multi_index(self, arr, indices):
                     raise ValueError
                 arr = arr.take(mi.ravel(), axis=ax)
                 try:
-                    arr = arr.reshape((arr.shape[:ax]
+                    arr = arr.reshape(arr.shape[:ax]
                                         + mi.shape
-                                        + arr.shape[ax+1:]))
+                                        + arr.shape[ax+1:])
                 except ValueError:
                     # too many dimensions, probably
                     raise IndexError

numpy/_core/tests/test_multiarray.py

@@ -234,7 +234,7 @@ def test_readonly_flag_protocols(self, flag, flag_value, writeable):
         a = np.arange(10)
         setattr(a.flags, flag, flag_value)
 
-        class MyArr():
+        class MyArr:
             __array_struct__ = a.__array_struct__
 
         assert memoryview(a).readonly is not writeable
@@ -6480,11 +6480,11 @@ def test_std_where(self):
                         [True],
                         [False]])
         _cases = [
-            (0, True, 7.07106781*np.ones((5))),
-            (1, True, 1.41421356*np.ones((5))),
+            (0, True, 7.07106781*np.ones(5)),
+            (1, True, 1.41421356*np.ones(5)),
             (0, whf,
              np.array([4.0824829 , 8.16496581, 5., 7.39509973, 8.49836586])),
-            (0, whp, 2.5*np.ones((5)))
+            (0, whp, 2.5*np.ones(5))
         ]
         for _ax, _wh, _res in _cases:
             assert_allclose(a.std(axis=_ax, where=_wh), _res)
@@ -6886,7 +6886,7 @@ def test_huge_vectordot(self, dtype):
 
     def test_dtype_discovery_fails(self):
         # See gh-14247, error checking was missing for failed dtype discovery
-        class BadObject(object):
+        class BadObject:
             def __array__(self, dtype=None, copy=None):
                 raise TypeError("just this tiny mint leaf")
 
@@ -7247,7 +7247,7 @@ def test_matmul_empty(self):
 
     def test_matmul_exception_multiply(self):
         # test that matmul fails if `__mul__` is missing
-        class add_not_multiply():
+        class add_not_multiply:
             def __add__(self, other):
                 return self
         a = np.full((3,3), add_not_multiply())
@@ -7256,7 +7256,7 @@ def __add__(self, other):
 
     def test_matmul_exception_add(self):
         # test that matmul fails if `__add__` is missing
-        class multiply_not_add():
+        class multiply_not_add:
             def __mul__(self, other):
                 return self
         a = np.full((3,3), multiply_not_add())
@@ -8356,7 +8356,7 @@ def test_no_suboffsets(self):
                 np.frombuffer(buffer)
 
 
-class TestArrayCreationCopyArgument(object):
+class TestArrayCreationCopyArgument:
 
     class RaiseOnBool:
 
@@ -8677,7 +8677,7 @@ def test_multiarray_flags_not_writable_attribute_deletion(self):
             assert_raises(AttributeError, delattr, a, s)
 
 
-class TestArrayInterface():
+class TestArrayInterface:
     class Foo:
         def __init__(self, value):
             self.value = value

numpy/_core/tests/test_overrides.py

@@ -540,7 +540,7 @@ def __array_function__(self, func, types, args, kwargs):
 
 class TestArrayLike:
     def setup_method(self):
-        class MyArray():
+        class MyArray:
             def __init__(self, function=None):
                 self.function = function
 
@@ -554,7 +554,7 @@ def __array_function__(self, func, types, args, kwargs):
 
         self.MyArray = MyArray
 
-        class MyNoArrayFunctionArray():
+        class MyNoArrayFunctionArray:
             def __init__(self, function=None):
                 self.function = function
 

numpy/_core/tests/test_records.py

@@ -114,9 +114,9 @@ def test_recarray_from_obj(self):
 
         mine = np.rec.fromarrays([a, b, c], names='date,data1,data2')
         for i in range(len(a)):
-            assert_((mine.date[i] == list(range(1, 10))))
-            assert_((mine.data1[i] == 0.0))
-            assert_((mine.data2[i] == 0.0))
+            assert_(mine.date[i] == list(range(1, 10)))
+            assert_(mine.data1[i] == 0.0)
+            assert_(mine.data2[i] == 0.0)
 
     def test_recarray_repr(self):
         a = np.array([(1, 0.1), (2, 0.2)],

numpy/_core/tests/test_regression.py

@@ -1071,8 +1071,8 @@ def test_astype_copy(self):
         with open(filename, 'rb') as f:
             xp = pickle.load(f, encoding='latin1')
         xpd = xp.astype(np.float64)
-        assert_((xp.__array_interface__['data'][0] !=
-                xpd.__array_interface__['data'][0]))
+        assert_(xp.__array_interface__['data'][0] !=
+                xpd.__array_interface__['data'][0])
 
     def test_compress_small_type(self):
         # Ticket #789, changeset 5217.

numpy/_core/tests/test_shape_base.py

@@ -154,7 +154,7 @@ def test_2D_array(self):
 
     def test_generator(self):
         with pytest.raises(TypeError, match="arrays to stack must be"):
-            hstack((np.arange(3) for _ in range(2)))
+            hstack(np.arange(3) for _ in range(2))
         with pytest.raises(TypeError, match="arrays to stack must be"):
             hstack(map(lambda x: x, np.ones((3, 2))))
 
@@ -209,7 +209,7 @@ def test_2D_array2(self):
 
     def test_generator(self):
         with pytest.raises(TypeError, match="arrays to stack must be"):
-            vstack((np.arange(3) for _ in range(2)))
+            vstack(np.arange(3) for _ in range(2))
 
     def test_casting_and_dtype(self):
         a = np.array([1, 2, 3])
@@ -477,7 +477,7 @@ def test_stack():
 
     # do not accept generators
     with pytest.raises(TypeError, match="arrays to stack must be"):
-        stack((x for x in range(3)))
+        stack(x for x in range(3))
 
     #casting and dtype test
     a = np.array([1, 2, 3])

numpy/_core/tests/test_stringdtype.py

@@ -232,12 +232,12 @@ def test_self_casts(dtype, dtype2, strings):
     if hasattr(dtype, "na_object") and hasattr(dtype2, "na_object"):
         na1 = dtype.na_object
         na2 = dtype2.na_object
-        if ((na1 is not na2 and
+        if (na1 is not na2 and
              # check for pd_NA first because bool(pd_NA) is an error
              ((na1 is pd_NA or na2 is pd_NA) or
               # the second check is a NaN check, spelled this way
               # to avoid errors from math.isnan and np.isnan
-              (na1 != na2 and not (na1 != na1 and na2 != na2))))):
+              (na1 != na2 and not (na1 != na1 and na2 != na2)))):
             with pytest.raises(TypeError):
                 arr[:-1] == newarr[:-1]
             return

numpy/f2py/auxfuncs.py

@@ -701,9 +701,9 @@ def getcallprotoargument(rout, cb_map={}):
             else:
                 if not isattr_value(var):
                     ctype = ctype + '*'
-            if ((isstring(var)
+            if (isstring(var)
                  or isarrayofstrings(var)  # obsolete?
-                 or isstringarray(var))):
+                 or isstringarray(var)):
                 arg_types2.append('size_t')
         arg_types.append(ctype)