Merge branch 'topic/default/check-py3.12-numpy2.0' into 'branch/default'

Check Python 3.12 and Numpy 2.0

See merge request fluiddyn/transonic!141

.github/workflows/ci-windows.yml

@@ -12,13 +12,13 @@ jobs:
         shell: bash -l {0}
     strategy:
       matrix:
-        python-version: ["3.11"]
+        python-version: ["3.11", "3.12"]
 
     steps:
     - uses: actions/checkout@v2
     - uses: prefix-dev/[email protected]
       with:
-        pixi-version: v0.23.0
+        pixi-version: v0.26.1
         cache: false
     - name: Tests
       run: |

data_tests/saved__backend__/cython/type_hint_notemplate.pxd

@@ -6,8 +6,8 @@ cimport numpy as np
 ctypedef fused __compute__Array_TypeIint_complex128I_NDimI1_3I:
    np.ndarray[np.complex128_t, ndim=1]
    np.ndarray[np.complex128_t, ndim=3]
-   np.ndarray[np.int_t, ndim=1]
-   np.ndarray[np.int_t, ndim=3]
+   np.ndarray[np.int32_t, ndim=1]
+   np.ndarray[np.int32_t, ndim=3]
 
 ctypedef fused __compute__TypeIint_complex128I:
    cython.int
@@ -18,7 +18,7 @@ ctypedef fused __compute__UnionArray_TypeIint_complex128I_NDimI1_3I_Array_float3
    np.ndarray[np.complex128_t, ndim=3]
    np.ndarray[np.float32_t, ndim=2]
    np.ndarray[np.float32_t, ndim=4]
-   np.ndarray[np.int_t, ndim=1]
-   np.ndarray[np.int_t, ndim=3]
+   np.ndarray[np.int32_t, ndim=1]
+   np.ndarray[np.int32_t, ndim=3]
 
 cpdef compute(__compute__Array_TypeIint_complex128I_NDimI1_3I a, __compute__Array_TypeIint_complex128I_NDimI1_3I b, __compute__TypeIint_complex128I c, __compute__UnionArray_TypeIint_complex128I_NDimI1_3I_Array_float32_NDimI1_3Ip1 d, cython.str e)

src/transonic/backends/cython.py

@@ -32,11 +32,14 @@
 
 
 def normalize_type_name_for_array(name):
-    if name == "bool_":
+
+    if name in ("bool_", "bool"):
         return "np.uint8"
+    if name == "int":
+        return "np.int32"
     if any(name.endswith(str(number)) for number in (8, 16, 32, 64, 128)):
         return "np." + name
-    if name in ("int", "float", "complex"):
+    if name in ("float", "complex"):
         return "np." + name
     return name
 

src/transonic_cl/cythonize.py

@@ -1,5 +1,5 @@
 import sys
-from distutils.core import setup
+from setuptools import setup
 
 import numpy as np
 from Cython.Build import cythonize

src/transonic_cl/run_backend.py

@@ -116,14 +116,14 @@ def main():
         args = [sys.executable, "-m", "transonic_cl.cythonize", name]
 
     name_lock.touch()
-    try:
-        completed_process = subprocess.run(
-            args, stdout=stdout, stderr=stderr, universal_newlines=True
-        )
-    except Exception:
-        pass
-    finally:
-        name_lock.unlink()
+    completed_process = subprocess.run(
+        args, stdout=stdout, stderr=stderr, text=True, check=False
+    )
+    name_lock.unlink()
+
+    if completed_process.returncode:
+        print(completed_process.stderr)
+        raise subprocess.CalledProcessError(completed_process.returncode, args)
     if backend == "pythran" and "-o" in args and path_tmp.exists():
         path_tmp.rename(path_out)
     elif backend == "cython":

tests/backends/test_cython.py

@@ -14,20 +14,20 @@ def compare(result, dtype, ndim, memview, mem_layout=None, positive_indices=None
 
 def test_memview():
     memview = "memview"
-    compare("np.int_t[:, ::1]", int, "2d", memview, "C")
-    compare("np.int_t[:, :, :]", int, "3d", memview, "strided")
+    compare("np.int32_t[:, ::1]", int, "2d", memview, "C")
+    compare("np.int32_t[:, :, :]", int, "3d", memview, "strided")
     compare("np.int32_t[::1, :]", np.int32, "2d", memview, "F")
 
 
 def test_array():
     memview = None
-    compare('np.ndarray[np.int_t, ndim=2, mode="c"]', int, "2d", memview, "C")
-    compare("np.ndarray[np.int_t, ndim=3]", int, "3d", memview, "strided")
+    compare('np.ndarray[np.int32_t, ndim=2, mode="c"]', int, "2d", memview, "C")
+    compare("np.ndarray[np.int32_t, ndim=3]", int, "3d", memview, "strided")
     compare(
         'np.ndarray[np.int32_t, ndim=2, mode="f"]', np.int32, "2d", memview, "F"
     )
     compare(
-        "np.ndarray[np.int_t, ndim=2, negative_indices=False]",
+        "np.ndarray[np.int32_t, ndim=2, negative_indices=False]",
         int,
         "2d",
         memview,