diff --git a/pkgs/development/python-modules/numba/numpy-1.24.patch b/pkgs/development/python-modules/numba/numpy-1.24.patch
deleted file mode 100644
index 8a0214b79f7f..000000000000
--- a/pkgs/development/python-modules/numba/numpy-1.24.patch
+++ /dev/null
@@ -1,644 +0,0 @@
-From c3e6994e07fb6ac57be5d9d33d9046c5453b2256 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 24 Nov 2022 15:41:24 +0000
-Subject: [PATCH 01/13] CUDA intrinsics tests: correct np.float -> np.float16
-
-I believe this was written in error and should always have been float16.
----
- numba/cuda/tests/cudapy/test_intrinsics.py | 4 ++--
- 1 file changed, 2 insertions(+), 2 deletions(-)
-
-diff --git a/numba/cuda/tests/cudapy/test_intrinsics.py b/numba/cuda/tests/cudapy/test_intrinsics.py
-index 6e5fc0a0e..46fe8c607 100644
---- a/numba/cuda/tests/cudapy/test_intrinsics.py
-+++ b/numba/cuda/tests/cudapy/test_intrinsics.py
-@@ -619,7 +619,7 @@ class TestCudaIntrinsic(CUDATestCase):
-         arg2 = np.float16(4.)
-         compiled[1, 1](ary, arg1, arg2)
-         np.testing.assert_allclose(ary[0], arg2)
--        arg1 = np.float(5.)
-+        arg1 = np.float16(5.)
-         compiled[1, 1](ary, arg1, arg2)
-         np.testing.assert_allclose(ary[0], arg1)
- 
-@@ -631,7 +631,7 @@ class TestCudaIntrinsic(CUDATestCase):
-         arg2 = np.float16(4.)
-         compiled[1, 1](ary, arg1, arg2)
-         np.testing.assert_allclose(ary[0], arg1)
--        arg1 = np.float(5.)
-+        arg1 = np.float16(5.)
-         compiled[1, 1](ary, arg1, arg2)
-         np.testing.assert_allclose(ary[0], arg2)
- 
--- 
-2.39.1
-
-From 550fc6a25a82f76bc1f06bdea39177df635038c2 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 22 Dec 2022 13:02:22 +0000
-Subject: [PATCH 02/13] TestLinalgSvd.test_no_input_mutation: use
- reconstruction if necessary
-
-This test only checked for a plain match when comparing outputs.
-However, in some cases a reconstruction check can be necessary, as in
-`test_linalg_svd`.
----
- numba/tests/test_linalg.py | 61 ++++++++++++++++++++------------------
- 1 file changed, 32 insertions(+), 29 deletions(-)
-
-diff --git a/numba/tests/test_linalg.py b/numba/tests/test_linalg.py
-index db183059d..b1d4f0a83 100644
---- a/numba/tests/test_linalg.py
-+++ b/numba/tests/test_linalg.py
-@@ -1122,6 +1122,32 @@ class TestLinalgSvd(TestLinalgBase):
-     Tests for np.linalg.svd.
-     """
- 
-+    # This checks that A ~= U*S*V**H, i.e. SV decomposition ties out.  This is
-+    # required as NumPy uses only double precision LAPACK routines and
-+    # computation of SVD is numerically sensitive. Numba uses type-specific
-+    # routines and therefore sometimes comes out with a different answer to
-+    # NumPy (orthonormal bases are not unique, etc.).
-+
-+    def check_reconstruction(self, a, got, expected):
-+        u, sv, vt = got
-+
-+        # Check they are dimensionally correct
-+        for k in range(len(expected)):
-+            self.assertEqual(got[k].shape, expected[k].shape)
-+
-+        # Columns in u and rows in vt dictates the working size of s
-+        s = np.zeros((u.shape[1], vt.shape[0]))
-+        np.fill_diagonal(s, sv)
-+
-+        rec = np.dot(np.dot(u, s), vt)
-+        resolution = np.finfo(a.dtype).resolution
-+        np.testing.assert_allclose(
-+            a,
-+            rec,
-+            rtol=10 * resolution,
-+            atol=100 * resolution  # zeros tend to be fuzzy
-+        )
-+
-     @needs_lapack
-     def test_linalg_svd(self):
-         """
-@@ -1150,34 +1176,8 @@ class TestLinalgSvd(TestLinalgBase):
-                     # plain match failed, test by reconstruction
-                     use_reconstruction = True
- 
--            # if plain match fails then reconstruction is used.
--            # this checks that A ~= U*S*V**H
--            # i.e. SV decomposition ties out
--            # this is required as numpy uses only double precision lapack
--            # routines and computation of svd is numerically
--            # sensitive, numba using the type specific routines therefore
--            # sometimes comes out with a different answer (orthonormal bases
--            # are not unique etc.).
-             if use_reconstruction:
--                u, sv, vt = got
--
--                # check they are dimensionally correct
--                for k in range(len(expected)):
--                    self.assertEqual(got[k].shape, expected[k].shape)
--
--                # regardless of full_matrices cols in u and rows in vt
--                # dictates the working size of s
--                s = np.zeros((u.shape[1], vt.shape[0]))
--                np.fill_diagonal(s, sv)
--
--                rec = np.dot(np.dot(u, s), vt)
--                resolution = np.finfo(a.dtype).resolution
--                np.testing.assert_allclose(
--                    a,
--                    rec,
--                    rtol=10 * resolution,
--                    atol=100 * resolution  # zeros tend to be fuzzy
--                )
-+                self.check_reconstruction(a, got, expected)
- 
-             # Ensure proper resource management
-             with self.assertNoNRTLeak():
-@@ -1238,8 +1238,11 @@ class TestLinalgSvd(TestLinalgBase):
-         got = func(X, False)
-         np.testing.assert_allclose(X, X_orig)
- 
--        for e_a, g_a in zip(expected, got):
--            np.testing.assert_allclose(e_a, g_a)
-+        try:
-+            for e_a, g_a in zip(expected, got):
-+                np.testing.assert_allclose(e_a, g_a)
-+        except AssertionError:
-+            self.check_reconstruction(X, got, expected)
- 
- 
- class TestLinalgQr(TestLinalgBase):
--- 
-2.39.1
-
-From c9ca2d1ae5e09ace729cddf6fba08effcd69a0b7 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 24 Nov 2022 21:39:27 +0000
-Subject: [PATCH 03/13] test_comp_nest_with_dependency: skip on NumPy 1.24
-
-Setting an array element with a sequence is removed in NumPy 1.24.
----
- numba/tests/test_comprehension.py | 2 ++
- 1 file changed, 2 insertions(+)
-
-diff --git a/numba/tests/test_comprehension.py b/numba/tests/test_comprehension.py
-index 2cdd3dc25..092ed51da 100644
---- a/numba/tests/test_comprehension.py
-+++ b/numba/tests/test_comprehension.py
-@@ -11,6 +11,7 @@ from numba import jit, typed
- from numba.core import types, utils
- from numba.core.errors import TypingError, LoweringError
- from numba.core.types.functions import _header_lead
-+from numba.np.numpy_support import numpy_version
- from numba.tests.support import tag, _32bit, captured_stdout
- 
- 
-@@ -360,6 +361,7 @@ class TestArrayComprehension(unittest.TestCase):
-         self.check(comp_nest_with_array_conditional, 5,
-                    assert_allocate_list=True)
- 
-+    @unittest.skipUnless(numpy_version < (1, 24), 'Removed in NumPy 1.24')
-     def test_comp_nest_with_dependency(self):
-         def comp_nest_with_dependency(n):
-             l = np.array([[i * j for j in range(i+1)] for i in range(n)])
--- 
-2.39.1
-
-From e69ad519352ac5a1f7714083968fcbac3ba92f95 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 24 Nov 2022 16:48:37 +0000
-Subject: [PATCH 04/13] Avoid use of np.bool in stencilparfor.py
-
----
- numba/stencils/stencilparfor.py | 7 ++++++-
- 1 file changed, 6 insertions(+), 1 deletion(-)
-
-diff --git a/numba/stencils/stencilparfor.py b/numba/stencils/stencilparfor.py
-index 5f30893b3..4f23ed903 100644
---- a/numba/stencils/stencilparfor.py
-+++ b/numba/stencils/stencilparfor.py
-@@ -21,6 +21,7 @@ from numba.core.ir_utils import (get_call_table, mk_unique_var,
-                             find_callname, require, find_const, GuardException)
- from numba.core.errors import NumbaValueError
- from numba.core.utils import OPERATORS_TO_BUILTINS
-+from numba.np import numpy_support
- 
- 
- def _compute_last_ind(dim_size, index_const):
-@@ -264,7 +265,11 @@ class StencilPass(object):
-             dtype_g_np_assign = ir.Assign(dtype_g_np, dtype_g_np_var, loc)
-             init_block.body.append(dtype_g_np_assign)
- 
--            dtype_np_attr_call = ir.Expr.getattr(dtype_g_np_var, return_type.dtype.name, loc)
-+            return_type_name = numpy_support.as_dtype(
-+                               return_type.dtype).type.__name__
-+            if return_type_name == 'bool':
-+                return_type_name = 'bool_'
-+            dtype_np_attr_call = ir.Expr.getattr(dtype_g_np_var, return_type_name, loc)
-             dtype_attr_var = ir.Var(scope, mk_unique_var("$np_attr_attr"), loc)
-             self.typemap[dtype_attr_var.name] = types.functions.NumberClass(return_type.dtype)
-             dtype_attr_assign = ir.Assign(dtype_np_attr_call, dtype_attr_var, loc)
--- 
-2.39.1
-
-From dd96d5996abd8646443501f2bbd7d4e1a9c0eec4 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 24 Nov 2022 15:46:52 +0000
-Subject: [PATCH 05/13] test_hypot: Tweak regex so it matches NumPy 1.24
-
-The modified regex matches the existing message produced by NumPy <
-1.24, and the new improved message in 1.24.
----
- numba/tests/test_mathlib.py | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/numba/tests/test_mathlib.py b/numba/tests/test_mathlib.py
-index a3f535316..05e3d68f5 100644
---- a/numba/tests/test_mathlib.py
-+++ b/numba/tests/test_mathlib.py
-@@ -516,7 +516,7 @@ class TestMathLib(TestCase):
-             with warnings.catch_warnings():
-                 warnings.simplefilter("error", RuntimeWarning)
-                 self.assertRaisesRegexp(RuntimeWarning,
--                                        'overflow encountered in .*_scalars',
-+                                        'overflow encountered in .*scalar',
-                                         naive_hypot, val, val)
- 
-     def test_hypot_npm(self):
--- 
-2.39.1
-
-From b755c22caeec9e6b0e0606f0cee245648914d592 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 24 Nov 2022 11:29:53 +0000
-Subject: [PATCH 06/13] Don't test summing with timedelta dtype
-
-This always produced invalid results (though they were consistent
-between Numba and NumPy) but now this fails in NumPy 1.24 with an
-exception:
-
-```
-TypeError: The `dtype` and `signature` arguments to ufuncs only select
-the general DType and not details such as the byte order or time unit.
-You can avoid this error by using the scalar types `np.float64` or the
-dtype string notation.
-```
-
-Note that the exception message is misleading, and using the dtype
-string notation does not provide a workaround.
----
- numba/tests/test_array_methods.py | 15 ++++++---------
- 1 file changed, 6 insertions(+), 9 deletions(-)
-
-diff --git a/numba/tests/test_array_methods.py b/numba/tests/test_array_methods.py
-index eee5cfeff..a2312adba 100644
---- a/numba/tests/test_array_methods.py
-+++ b/numba/tests/test_array_methods.py
-@@ -1193,7 +1193,7 @@ class TestArrayMethods(MemoryLeakMixin, TestCase):
-         pyfunc = array_sum_dtype_kws
-         cfunc = jit(nopython=True)(pyfunc)
-         all_dtypes = [np.float64, np.float32, np.int64, np.int32, np.uint32,
--                      np.uint64, np.complex64, np.complex128, TIMEDELTA_M]
-+                      np.uint64, np.complex64, np.complex128]
-         all_test_arrays = [
-             [np.ones((7, 6, 5, 4, 3), arr_dtype),
-              np.ones(1, arr_dtype),
-@@ -1207,8 +1207,7 @@ class TestArrayMethods(MemoryLeakMixin, TestCase):
-                       np.dtype('uint32'): [np.float64, np.int64, np.float32],
-                       np.dtype('uint64'): [np.float64, np.int64],
-                       np.dtype('complex64'): [np.complex64, np.complex128],
--                      np.dtype('complex128'): [np.complex128],
--                      np.dtype(TIMEDELTA_M): [np.dtype(TIMEDELTA_M)]}
-+                      np.dtype('complex128'): [np.complex128]}
- 
-         for arr_list in all_test_arrays:
-             for arr in arr_list:
-@@ -1216,15 +1215,15 @@ class TestArrayMethods(MemoryLeakMixin, TestCase):
-                     subtest_str = ("Testing np.sum with {} input and {} output"
-                                    .format(arr.dtype, out_dtype))
-                     with self.subTest(subtest_str):
--                        self.assertPreciseEqual(pyfunc(arr, dtype=out_dtype),
--                                                cfunc(arr, dtype=out_dtype))
-+                            self.assertPreciseEqual(pyfunc(arr, dtype=out_dtype),
-+                                                    cfunc(arr, dtype=out_dtype))
- 
-     def test_sum_axis_dtype_kws(self):
-         """ test sum with axis and dtype parameters over a whole range of dtypes """
-         pyfunc = array_sum_axis_dtype_kws
-         cfunc = jit(nopython=True)(pyfunc)
-         all_dtypes = [np.float64, np.float32, np.int64, np.int32, np.uint32,
--                      np.uint64, np.complex64, np.complex128, TIMEDELTA_M]
-+                      np.uint64, np.complex64, np.complex128]
-         all_test_arrays = [
-             [np.ones((7, 6, 5, 4, 3), arr_dtype),
-              np.ones(1, arr_dtype),
-@@ -1238,9 +1237,7 @@ class TestArrayMethods(MemoryLeakMixin, TestCase):
-                       np.dtype('uint32'): [np.float64, np.int64, np.float32],
-                       np.dtype('uint64'): [np.float64, np.uint64],
-                       np.dtype('complex64'): [np.complex64, np.complex128],
--                      np.dtype('complex128'): [np.complex128],
--                      np.dtype(TIMEDELTA_M): [np.dtype(TIMEDELTA_M)],
--                      np.dtype(TIMEDELTA_Y): [np.dtype(TIMEDELTA_Y)]}
-+                      np.dtype('complex128'): [np.complex128]}
- 
-         for arr_list in all_test_arrays:
-             for arr in arr_list:
--- 
-2.39.1
-
-From 65df00379df1276b7045b44818347a119bb32361 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 24 Nov 2022 10:03:54 +0000
-Subject: [PATCH 07/13] Replace use of deprecated np.bool with np.bool_
-
-np.bool was removed in NumPy 1.24.
----
- numba/tests/test_np_functions.py | 8 ++++----
- 1 file changed, 4 insertions(+), 4 deletions(-)
-
-diff --git a/numba/tests/test_np_functions.py b/numba/tests/test_np_functions.py
-index 4cdaf548b..e195ac781 100644
---- a/numba/tests/test_np_functions.py
-+++ b/numba/tests/test_np_functions.py
-@@ -932,11 +932,11 @@ class TestNPFunctions(MemoryLeakMixin, TestCase):
-             yield np.inf, None
-             yield np.PINF, None
-             yield np.asarray([-np.inf, 0., np.inf]), None
--            yield np.NINF, np.zeros(1, dtype=np.bool)
--            yield np.inf, np.zeros(1, dtype=np.bool)
--            yield np.PINF, np.zeros(1, dtype=np.bool)
-+            yield np.NINF, np.zeros(1, dtype=np.bool_)
-+            yield np.inf, np.zeros(1, dtype=np.bool_)
-+            yield np.PINF, np.zeros(1, dtype=np.bool_)
-             yield np.NINF, np.empty(12)
--            yield np.asarray([-np.inf, 0., np.inf]), np.zeros(3, dtype=np.bool)
-+            yield np.asarray([-np.inf, 0., np.inf]), np.zeros(3, dtype=np.bool_)
- 
-         pyfuncs = [isneginf, isposinf]
-         for pyfunc in pyfuncs:
--- 
-2.39.1
-
-From 065475bd8d5f39ad0a2b0d154ca283dec10bf5d0 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Thu, 24 Nov 2022 09:56:06 +0000
-Subject: [PATCH 08/13] Overload np.MachAr only for NumPy < 1.24
-
----
- numba/np/arraymath.py            | 4 ++++
- numba/tests/test_np_functions.py | 4 +++-
- 2 files changed, 7 insertions(+), 1 deletion(-)
-
-diff --git a/numba/np/arraymath.py b/numba/np/arraymath.py
-index 9885526ee..f6e5f5560 100644
---- a/numba/np/arraymath.py
-+++ b/numba/np/arraymath.py
-@@ -4177,6 +4177,10 @@ iinfo = namedtuple('iinfo', _iinfo_supported)
- # This module is imported under the compiler lock which should deal with the
- # lack of thread safety in the warning filter.
- def _gen_np_machar():
-+    # NumPy 1.24 removed np.MachAr
-+    if numpy_version >= (1, 24):
-+        return
-+
-     np122plus = numpy_version >= (1, 22)
-     w = None
-     with warnings.catch_warnings(record=True) as w:
-diff --git a/numba/tests/test_np_functions.py b/numba/tests/test_np_functions.py
-index e195ac781..e8a9bccd0 100644
---- a/numba/tests/test_np_functions.py
-+++ b/numba/tests/test_np_functions.py
-@@ -4775,6 +4775,7 @@ def foo():
-         eval(compile(funcstr, '<string>', 'exec'))
-         return locals()['foo']
- 
-+    @unittest.skipIf(numpy_version >= (1, 24), "NumPy < 1.24 required")
-     def test_MachAr(self):
-         attrs = ('ibeta', 'it', 'machep', 'eps', 'negep', 'epsneg', 'iexp',
-                  'minexp', 'xmin', 'maxexp', 'xmax', 'irnd', 'ngrd',
-@@ -4817,7 +4818,8 @@ def foo():
-             cfunc = jit(nopython=True)(iinfo)
-             cfunc(np.float64(7))
- 
--    @unittest.skipUnless(numpy_version >= (1, 22), "Needs NumPy >= 1.22")
-+    @unittest.skipUnless((1, 22) <= numpy_version < (1, 24),
-+                         "Needs NumPy >= 1.22, < 1.24")
-     @TestCase.run_test_in_subprocess
-     def test_np_MachAr_deprecation_np122(self):
-         # Tests that Numba is replaying the NumPy 1.22 deprecation warning
--- 
-2.39.1
-
-From 4925287144b9dca5624886ac44a27831178a7198 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Fri, 25 Nov 2022 10:55:04 +0000
-Subject: [PATCH 09/13] _internal.c: Remove NPY_API_VERSION checks
-
-The API version has long since been greater than 0x7 / 0x8 for any
-supported NumPy.
----
- numba/np/ufunc/_internal.c | 14 --------------
- 1 file changed, 14 deletions(-)
-
-diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c
-index 98a643788..3ab725f8f 100644
---- a/numba/np/ufunc/_internal.c
-+++ b/numba/np/ufunc/_internal.c
-@@ -285,9 +285,7 @@ static struct _ufunc_dispatch {
-     PyCFunctionWithKeywords ufunc_accumulate;
-     PyCFunctionWithKeywords ufunc_reduceat;
-     PyCFunctionWithKeywords ufunc_outer;
--#if NPY_API_VERSION >= 0x00000008
-     PyCFunction ufunc_at;
--#endif
- } ufunc_dispatch;
- 
- static int
-@@ -303,10 +301,8 @@ init_ufunc_dispatch(int *numpy_uses_fastcall)
-             if (strncmp(crnt_name, "accumulate", 11) == 0) {
-                 ufunc_dispatch.ufunc_accumulate =
-                     (PyCFunctionWithKeywords)crnt->ml_meth;
--#if NPY_API_VERSION >= 0x00000008
-             } else if (strncmp(crnt_name, "at", 3) == 0) {
-                 ufunc_dispatch.ufunc_at = crnt->ml_meth;
--#endif
-             } else {
-                 result = -1;
-             }
-@@ -351,9 +347,7 @@ init_ufunc_dispatch(int *numpy_uses_fastcall)
-                   && (ufunc_dispatch.ufunc_accumulate != NULL)
-                   && (ufunc_dispatch.ufunc_reduceat != NULL)
-                   && (ufunc_dispatch.ufunc_outer != NULL)
--#if NPY_API_VERSION >= 0x00000008
-                   && (ufunc_dispatch.ufunc_at != NULL)
--#endif
-                   );
-     }
-     return result;
-@@ -425,13 +419,11 @@ dufunc_outer_fast(PyDUFuncObject * self,
- }
- 
- 
--#if NPY_API_VERSION >= 0x00000008
- static PyObject *
- dufunc_at(PyDUFuncObject * self, PyObject * args)
- {
-     return ufunc_dispatch.ufunc_at((PyObject*)self->ufunc, args);
- }
--#endif
- 
- static PyObject *
- dufunc__compile_for_args(PyDUFuncObject * self, PyObject * args,
-@@ -609,11 +601,9 @@ static struct PyMethodDef dufunc_methods[] = {
-     {"outer",
-         (PyCFunction)dufunc_outer,
-         METH_VARARGS | METH_KEYWORDS, NULL},
--#if NPY_API_VERSION >= 0x00000008
-     {"at",
-         (PyCFunction)dufunc_at,
-         METH_VARARGS, NULL},
--#endif
-     {"_compile_for_args",
-         (PyCFunction)dufunc__compile_for_args,
-         METH_VARARGS | METH_KEYWORDS,
-@@ -643,11 +633,9 @@ static struct PyMethodDef dufunc_methods_fast[] = {
-     {"outer",
-         (PyCFunction)dufunc_outer_fast,
-         METH_FASTCALL | METH_KEYWORDS, NULL},
--#if NPY_API_VERSION >= 0x00000008
-     {"at",
-         (PyCFunction)dufunc_at,
-         METH_VARARGS, NULL},
--#endif
-     {"_compile_for_args",
-         (PyCFunction)dufunc__compile_for_args,
-         METH_VARARGS | METH_KEYWORDS,
-@@ -791,9 +779,7 @@ MOD_INIT(_internal)
-     if (PyModule_AddIntMacro(m, PyUFunc_One)
-         || PyModule_AddIntMacro(m, PyUFunc_Zero)
-         || PyModule_AddIntMacro(m, PyUFunc_None)
--#if NPY_API_VERSION >= 0x00000007
-         || PyModule_AddIntMacro(m, PyUFunc_ReorderableNone)
--#endif
-         )
-         return MOD_ERROR_VAL;
- 
--- 
-2.39.1
-
-From 783ef5a297f15d16eec61fe38d13648b876e3750 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Tue, 3 Jan 2023 17:08:44 +0000
-Subject: [PATCH 10/13] init_ufunc_dispatch: Handle unexpected ufunc methods
- gracefully
-
-If an unexpected ufunc method was encountered, `init_ufunc_dispatch()`
-would return an error code indicating failure without setting an
-exception, leading to errors like
-
-```
-SystemError: initialization of _internal failed without raising an
-exception
-```
-
-as reported in Issue #8615.
-
-This commit fixes the issue by setting an appropriate exception in this
-case.
----
- numba/np/ufunc/_internal.c | 6 ++++++
- 1 file changed, 6 insertions(+)
-
-diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c
-index 3ab725f8f..6ce8989cd 100644
---- a/numba/np/ufunc/_internal.c
-+++ b/numba/np/ufunc/_internal.c
-@@ -337,6 +337,8 @@ init_ufunc_dispatch(int *numpy_uses_fastcall)
-                 *numpy_uses_fastcall = crnt->ml_flags & METH_FASTCALL;
-             }
-             else if (*numpy_uses_fastcall != (crnt->ml_flags & METH_FASTCALL)) {
-+                PyErr_SetString(PyExc_RuntimeError,
-+                    "ufunc.at() flags do not match numpy_uses_fastcall");
-                 return -1;
-             }
-         }
-@@ -349,7 +351,11 @@ init_ufunc_dispatch(int *numpy_uses_fastcall)
-                   && (ufunc_dispatch.ufunc_outer != NULL)
-                   && (ufunc_dispatch.ufunc_at != NULL)
-                   );
-+    } else {
-+        char const * const fmt = "Unexpected ufunc method %s()";
-+        PyErr_Format(PyExc_RuntimeError, fmt, crnt_name);
-     }
-+
-     return result;
- }
- 
--- 
-2.39.1
-
-From 5c259e46a8e510c2b82c7ff449b167d3b430294b Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Tue, 3 Jan 2023 17:11:10 +0000
-Subject: [PATCH 11/13] init_ufunc_dispatch: Update for NumPy 1.24
-
-NumPy 1.24 adds a new method, `resolve_dtypes()`, and a private method
-`_resolve_dtypes_and_context()`. We handle these by just ignoring them
-(ignoring all private methods in general) in order to provide the same
-level of functionality in Numba as for NumPy 1.23.
-
-There is further room to build new functionality on top of this:
-
-- Providing an implementation of `resolve_dtypes()` for `DUFunc`
-  objects.
-- Using the `resolve_dtypes()` method in place of logic in Numba that
-  implements a similar dtype resolution process.
----
- numba/np/ufunc/_internal.c | 5 +++++
- 1 file changed, 5 insertions(+)
-
-diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c
-index 6ce8989cd..e860081fb 100644
---- a/numba/np/ufunc/_internal.c
-+++ b/numba/np/ufunc/_internal.c
-@@ -322,10 +322,15 @@ init_ufunc_dispatch(int *numpy_uses_fastcall)
-             } else if (strncmp(crnt_name, "reduceat", 9) == 0) {
-                 ufunc_dispatch.ufunc_reduceat =
-                     (PyCFunctionWithKeywords)crnt->ml_meth;
-+            } else if (strncmp(crnt_name, "resolve_dtypes", 15) == 0) {
-+              /* Ignored */
-             } else {
-                 result = -1;
-             }
-             break;
-+        case '_':
-+            // We ignore private methods
-+            break;
-         default:
-             result = -1; /* Unknown method */
-         }
--- 
-2.39.1
-
-From 3736714982be943eb94f4a259368b1dce525ea64 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Wed, 11 Jan 2023 16:25:19 +0000
-Subject: [PATCH 12/13] Update comment on skipped test
-
-PR #8691 feedback.
----
- numba/tests/test_comprehension.py | 4 +++-
- 1 file changed, 3 insertions(+), 1 deletion(-)
-
-diff --git a/numba/tests/test_comprehension.py b/numba/tests/test_comprehension.py
-index 092ed51da..9327b4ed3 100644
---- a/numba/tests/test_comprehension.py
-+++ b/numba/tests/test_comprehension.py
-@@ -361,7 +361,9 @@ class TestArrayComprehension(unittest.TestCase):
-         self.check(comp_nest_with_array_conditional, 5,
-                    assert_allocate_list=True)
- 
--    @unittest.skipUnless(numpy_version < (1, 24), 'Removed in NumPy 1.24')
-+    @unittest.skipUnless(numpy_version < (1, 24),
-+                         'Setting an array element with a sequence is removed '
-+                         'in NumPy 1.24')
-     def test_comp_nest_with_dependency(self):
-         def comp_nest_with_dependency(n):
-             l = np.array([[i * j for j in range(i+1)] for i in range(n)])
--- 
-2.39.1
-
-From 3cbab7ee436e3452e7d078f8283136671a36d944 Mon Sep 17 00:00:00 2001
-From: Graham Markall <gmarkall@nvidia.com>
-Date: Fri, 27 Jan 2023 12:06:57 +0000
-Subject: [PATCH 13/13] Correct name of ufunc method in fastcall flags error
-
-The name of the method should be given, which was never `at()`.
----
- numba/np/ufunc/_internal.c | 5 +++--
- 1 file changed, 3 insertions(+), 2 deletions(-)
-
-diff --git a/numba/np/ufunc/_internal.c b/numba/np/ufunc/_internal.c
-index e860081fb..0a33de170 100644
---- a/numba/np/ufunc/_internal.c
-+++ b/numba/np/ufunc/_internal.c
-@@ -342,8 +342,9 @@ init_ufunc_dispatch(int *numpy_uses_fastcall)
-                 *numpy_uses_fastcall = crnt->ml_flags & METH_FASTCALL;
-             }
-             else if (*numpy_uses_fastcall != (crnt->ml_flags & METH_FASTCALL)) {
--                PyErr_SetString(PyExc_RuntimeError,
--                    "ufunc.at() flags do not match numpy_uses_fastcall");
-+                PyErr_Format(PyExc_RuntimeError,
-+                    "ufunc.%s() flags do not match numpy_uses_fastcall",
-+                    crnt_name);
-                 return -1;
-             }
-         }
--- 
-2.39.1
-