From bd487d7d25170a1220ea98c1ec002fcd74f5405e Mon Sep 17 00:00:00 2001
From: Miro Hrončok <miro@hroncok.cz>
Date: May 07 2021 09:43:02 +0000
Subject: Fix for Python 3.10.0b1+


Fixes https://bugzilla.redhat.com/show_bug.cgi?id=1958052

---

diff --git a/ad2a73c18d.patch b/ad2a73c18d.patch
new file mode 100644
index 0000000..3ca84ec
--- /dev/null
+++ b/ad2a73c18d.patch
@@ -0,0 +1,126 @@
+From ad2a73c18dcff95d844c382c94ab7f73b5571cf3 Mon Sep 17 00:00:00 2001
+From: Sebastian Berg <sebastian@sipsolutions.net>
+Date: Tue, 4 May 2021 17:43:26 -0500
+Subject: [PATCH] MAINT: Adjust NumPy float hashing to Python's slightly
+ changed hash
+
+This is necessary, since we use the Python double hash and the
+semi-private function to calculate it in Python has a new signature
+to return the identity-hash when the value is NaN.
+
+closes gh-18833, gh-18907
+---
+ numpy/core/src/common/npy_pycompat.h        | 16 ++++++++++
+ numpy/core/src/multiarray/scalartypes.c.src | 13 ++++----
+ numpy/core/tests/test_scalarmath.py         | 34 +++++++++++++++++++++
+ 3 files changed, 57 insertions(+), 6 deletions(-)
+
+diff --git a/numpy/core/src/common/npy_pycompat.h b/numpy/core/src/common/npy_pycompat.h
+index aa0b5c1224d3..9e94a971090a 100644
+--- a/numpy/core/src/common/npy_pycompat.h
++++ b/numpy/core/src/common/npy_pycompat.h
+@@ -3,4 +3,20 @@
+ 
+ #include "numpy/npy_3kcompat.h"
+ 
++
++/*
++ * In Python 3.10a7 (or b1), python started using the identity for the hash
++ * when a value is NaN.  See https://bugs.python.org/issue43475
++ */
++#if PY_VERSION_HEX > 0x030a00a6
++#define Npy_HashDouble _Py_HashDouble
++#else
++static NPY_INLINE Py_hash_t
++Npy_HashDouble(PyObject *NPY_UNUSED(identity), double val)
++{
++    return _Py_HashDouble(val);
++}
++#endif
++
++
+ #endif /* _NPY_COMPAT_H_ */
+diff --git a/numpy/core/src/multiarray/scalartypes.c.src b/numpy/core/src/multiarray/scalartypes.c.src
+index a001500b0a97..9930f7791d6e 100644
+--- a/numpy/core/src/multiarray/scalartypes.c.src
++++ b/numpy/core/src/multiarray/scalartypes.c.src
+@@ -3172,7 +3172,7 @@ static npy_hash_t
+ static npy_hash_t
+ @lname@_arrtype_hash(PyObject *obj)
+ {
+-    return _Py_HashDouble((double) PyArrayScalar_VAL(obj, @name@));
++    return Npy_HashDouble(obj, (double)PyArrayScalar_VAL(obj, @name@));
+ }
+ 
+ /* borrowed from complex_hash */
+@@ -3180,14 +3180,14 @@ static npy_hash_t
+ c@lname@_arrtype_hash(PyObject *obj)
+ {
+     npy_hash_t hashreal, hashimag, combined;
+-    hashreal = _Py_HashDouble((double)
+-            PyArrayScalar_VAL(obj, C@name@).real);
++    hashreal = Npy_HashDouble(
++            obj, (double)PyArrayScalar_VAL(obj, C@name@).real);
+ 
+     if (hashreal == -1) {
+         return -1;
+     }
+-    hashimag = _Py_HashDouble((double)
+-            PyArrayScalar_VAL(obj, C@name@).imag);
++    hashimag = Npy_HashDouble(
++            obj, (double)PyArrayScalar_VAL(obj, C@name@).imag);
+     if (hashimag == -1) {
+         return -1;
+     }
+@@ -3202,7 +3202,8 @@ c@lname@_arrtype_hash(PyObject *obj)
+ static npy_hash_t
+ half_arrtype_hash(PyObject *obj)
+ {
+-    return _Py_HashDouble(npy_half_to_double(PyArrayScalar_VAL(obj, Half)));
++    return Npy_HashDouble(
++            obj, npy_half_to_double(PyArrayScalar_VAL(obj, Half)));
+ }
+ 
+ static npy_hash_t
+diff --git a/numpy/core/tests/test_scalarmath.py b/numpy/core/tests/test_scalarmath.py
+index d91b4a39146d..09a734284a76 100644
+--- a/numpy/core/tests/test_scalarmath.py
++++ b/numpy/core/tests/test_scalarmath.py
+@@ -707,3 +707,37 @@
+                 shift_arr = np.array([shift]*32, dtype=dt)
+                 res_arr = op(val_arr, shift_arr)
+                 assert_equal(res_arr, res_scl)
++
++
++class TestHash:
++    @pytest.mark.parametrize("type_code", np.typecodes['AllInteger'])
++    def test_integer_hashes(self, type_code):
++        scalar = np.dtype(type_code).type
++        for i in range(128):
++            assert hash(i) == hash(scalar(i))
++
++    @pytest.mark.parametrize("type_code", np.typecodes['AllFloat'])
++    def test_float_and_complex_hashes(self, type_code):
++        scalar = np.dtype(type_code).type
++        for val in [np.pi, np.inf, 3, 6.]:
++            numpy_val = scalar(val)
++            # Cast back to Python, in case the NumPy scalar has less precision
++            if numpy_val.dtype.kind == 'c':
++                val = complex(numpy_val)
++            else:
++                val = float(numpy_val)
++            assert val == numpy_val
++            print(repr(numpy_val), repr(val))
++            assert hash(val) == hash(numpy_val)
++
++        if hash(float(np.nan)) != hash(float(np.nan)):
++            # If Python distinguises different NaNs we do so too (gh-18833)
++            assert hash(scalar(np.nan)) != hash(scalar(np.nan))
++
++    @pytest.mark.parametrize("type_code", np.typecodes['Complex'])
++    def test_complex_hashes(self, type_code):
++        # Test some complex valued hashes specifically:
++        scalar = np.dtype(type_code).type
++        for val in [np.pi+1j, np.inf-3j, 3j, 6.+1j]:
++            numpy_val = scalar(val)
++            assert hash(complex(numpy_val)) == hash(numpy_val)
diff --git a/numpy.spec b/numpy.spec
index 5403d47..6790b86 100644
--- a/numpy.spec
+++ b/numpy.spec
@@ -30,6 +30,11 @@ URL:            http://www.numpy.org/
 Source0:        https://github.com/%{name}/%{name}/releases/download/v%{version}/%{name}-%{version}.tar.gz
 Source1:        https://numpy.org/doc/1.19/numpy-html.zip
 
+# Adjust NumPy float hashing to Python's slightly changed hash (Python 3.10.0b1+)
+# Merged upstream, rebased slightly
+# https://github.com/numpy/numpy/commit/ad2a73c18d.patch
+Patch1:         ad2a73c18d.patch
+
 %description
 NumPy is a general-purpose array-processing package designed to
 efficiently manipulate large multi-dimensional arrays of arbitrary