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linedance-app/venv/lib/python3.12/site-packages/numba/tests/test_alignment.py

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+# See also numba.cuda.tests.test_alignment
+
+import numpy as np
+from numba import from_dtype, njit, void
+from numba.tests.support import TestCase
+
+
+class TestAlignment(TestCase):
+
+    def test_record_alignment(self):
+        rec_dtype = np.dtype([('a', 'int32'), ('b', 'float64')], align=True)
+        rec = from_dtype(rec_dtype)
+
+        @njit((rec[:],))
+        def foo(a):
+            for i in range(a.size):
+                a[i].a = a[i].b
+
+        a_recarray = np.recarray(3, dtype=rec_dtype)
+        for i in range(a_recarray.size):
+            a_rec = a_recarray[i]
+            a_rec.a = 0
+            a_rec.b = (i + 1) * 123
+
+        foo(a_recarray)
+        np.testing.assert_equal(a_recarray.a, a_recarray.b)
+
+    def test_record_misaligned(self):
+        rec_dtype = np.dtype([('a', 'int32'), ('b', 'float64')])
+        rec = from_dtype(rec_dtype)
+
+        # Unlike the CUDA target, this will not generate an error
+        @njit((rec[:],))
+        def foo(a):
+            for i in range(a.size):
+                a[i].a = a[i].b
+
+
+if __name__ == '__main__':
+    unittest.main()