Fix integer handling with NumPy 2.0 on Windows (pyccel#2116)

Fix integer handling with NumPy 2.0 on Windows. The default integer is
correctly deduced however the handling in the wrapper was incorrect.
This was fixed (fixes pyccel#2115). Additionally the dtype error output is
cleaned up so the positions of the datatypes in NumPy's enum are not
hard coded on our side.

This fix was complicated by the fact that `np.random.randint`'s default
dtype is maintained at `np.long` and therefore does not match the
default used by all other NumPy functions in v2:

![image](https://github.com/user-attachments/assets/3f331352-2e92-44d4-8176-1e410af5cfd6)

Author: EmilyBourne

.github/actions/windows_install/action.yml

@@ -4,6 +4,7 @@ runs:
   using: "composite"
   steps:
     - name: Fix 'Unknown MS Compiler version 1900' problem
+      continue-on-error: True
       run: |
         $PYTHON_EXE_PATH=(Get-Command python).Source
         $PYTHON_PATH=(Split-Path -Path ${PYTHON_EXE_PATH})

CHANGELOG.md

@@ -95,6 +95,7 @@ All notable changes to this project will be documented in this file.
 -   #2094 : Fix slicing of array allocated in an if block.
 -   #2085 : Fix calling class methods before they are defined.
 -   #2111 : Fix declaration of class attributes with name conflicts using type annotations.
+-   #2115 : Fix integer handling with NumPy 2.0 on Windows.
 
 ### Changed
 

pyccel/ast/numpy_wrapper.py

@@ -199,11 +199,11 @@ def get_numpy_max_acceptable_version_file():
 numpy_ubyte_type        = Variable(CNativeInt(),  name = 'NPY_UBYTE')
 numpy_short_type        = Variable(CNativeInt(),  name = 'NPY_SHORT')
 numpy_ushort_type       = Variable(CNativeInt(),  name = 'NPY_USHORT')
-numpy_int_type          = Variable(CNativeInt(),  name = 'NPY_INT32')
+numpy_int32_type        = Variable(CNativeInt(),  name = 'NPY_INT32')
 numpy_uint_type         = Variable(CNativeInt(),  name = 'NPY_UINT')
 numpy_long_type         = Variable(CNativeInt(),  name = 'NPY_LONG')
 numpy_ulong_type        = Variable(CNativeInt(),  name = 'NPY_ULONG')
-numpy_longlong_type     = Variable(CNativeInt(),  name = 'NPY_INT64')
+numpy_int64_type        = Variable(CNativeInt(),  name = 'NPY_INT64')
 numpy_ulonglong_type    = Variable(CNativeInt(),  name = 'NPY_ULONGLONG')
 numpy_float_type        = Variable(CNativeInt(),  name = 'NPY_FLOAT')
 numpy_double_type       = Variable(CNativeInt(),  name = 'NPY_DOUBLE')
@@ -212,36 +212,11 @@ def get_numpy_max_acceptable_version_file():
 numpy_cdouble_type      = Variable(CNativeInt(),  name = 'NPY_CDOUBLE')
 numpy_clongdouble_type  = Variable(CNativeInt(),  name = 'NPY_CLONGDOUBLE')
 
-numpy_num_to_type = {0 : numpy_bool_type,
-                     1 : numpy_byte_type,
-                     2 : numpy_ubyte_type,
-                     3 : numpy_short_type,
-                     4 : numpy_ushort_type,
-                     5 : numpy_int_type,
-                     6 : numpy_uint_type,
-                     7 : numpy_long_type,
-                     8 : numpy_ulong_type,
-                     9 : numpy_longlong_type,
-                    10 : numpy_ulonglong_type,
-                    11 : numpy_float_type,
-                    12 : numpy_double_type,
-                    13 : numpy_longdouble_type,
-                    14 : numpy_cfloat_type,
-                    15 : numpy_cdouble_type,
-                    16 : numpy_clongdouble_type}
-
-# This dictionary is required as the precision does not line up with the expected type on windows
-numpy_int_type_precision_map = {
-        1 : np.dtype(np.int8).num,
-        2 : np.dtype(np.int16).num,
-        4 : np.dtype(np.int32).num,
-        8 : np.dtype(np.int64).num}
-
 numpy_dtype_registry = {PythonNativeBool()    : numpy_bool_type,
-                        NumpyInt8Type()       : numpy_num_to_type[numpy_int_type_precision_map[1]],
-                        NumpyInt16Type()      : numpy_num_to_type[numpy_int_type_precision_map[2]],
-                        NumpyInt32Type()      : numpy_num_to_type[numpy_int_type_precision_map[4]],
-                        NumpyInt64Type()      : numpy_num_to_type[numpy_int_type_precision_map[8]],
+                        NumpyInt8Type()       : numpy_byte_type,
+                        NumpyInt16Type()      : numpy_short_type,
+                        NumpyInt32Type()      : numpy_int32_type,
+                        NumpyInt64Type()      : numpy_int64_type,
                         NumpyFloat32Type()    : numpy_float_type,
                         NumpyFloat64Type()    : numpy_double_type,
                         NumpyFloat128Type()   : numpy_longdouble_type,

pyccel/stdlib/cwrapper/cwrapper.c

@@ -7,15 +7,6 @@
 
 
 
-// strings order needs to be the same as its equivalent numpy macro
-// https://numpy.org/doc/stable/reference/c-api/dtype.html
-const char* dataTypes[17] = {"Bool", "Int8", "UInt8", "Int16", "UIn16", "Int32", "UInt32",
-                             "Int64", "UInt64", "Int128", "UInt128", "Float32", "Float64",
-                             "Float128", "Complex64", "Complex128", "Complex256"};
-
-
-
-
 /* Casting python object to c type
  *
  * Reference of the used c python api function
@@ -174,7 +165,7 @@ void capsule_cleanup(PyObject *capsule) {
 #endif
 }
 
-#ifdef _WIN32
+#if defined(WIN32) && (PyArray_RUNTIME_VERSION >= NPY_2_0_API_VERSION)
 PyObject* to_pyarray(int nd, enum NPY_TYPES typenum, void* data, int32_t shape[], bool c_order, bool release_memory)
 #else
 PyObject* to_pyarray(int nd, enum NPY_TYPES typenum, void* data, int64_t shape[], bool c_order, bool release_memory)

pyccel/stdlib/cwrapper/cwrapper.h

@@ -25,8 +25,6 @@
 # define PY_ARRAY_UNIQUE_SYMBOL CWRAPPER_ARRAY_API
 # include "numpy/arrayobject.h"
 
-extern const char* dataTypes[17];
-
 /*
  * A function which can be passed to a PyCapsule in order to free data that was created by Pyccel.
  */
@@ -50,7 +48,7 @@ void capsule_cleanup(PyObject *capsule);
  * c_order : True if the data is in C order, False otherwise.
  * release_memory : If true a Capsule is created to automatically free the data when the created PyArrayObject goes out of scope.
  */
-#ifdef _WIN32
+#if defined(_WIN32) && (PyArray_RUNTIME_VERSION >= NPY_2_0_API_VERSION)
 PyObject* to_pyarray(int nd, enum NPY_TYPES typenum, void* data, int32_t shape[], bool c_order, bool release_memory);
 #else
 PyObject* to_pyarray(int nd, enum NPY_TYPES typenum, void* data, int64_t shape[], bool c_order, bool release_memory);

pyccel/stdlib/cwrapper_ndarrays/cwrapper_ndarrays.c

@@ -100,10 +100,15 @@ static char*	_check_pyarray_dtype(PyArrayObject *a, int dtype)
 	current_dtype = PyArray_TYPE(a);
 	if (current_dtype != dtype)
 	{
+        PyObject* current_type_name = PyObject_Str(PyArray_DESCR(a)->typeobj);
+        PyObject* expected_type_name = PyObject_Str(PyArray_TypeObjectFromType(dtype));
+        Py_ssize_t c_size;
+        const char* current_name = PyUnicode_AsUTF8AndSize(current_type_name, &c_size);
+        const char* expected_name = PyUnicode_AsUTF8AndSize(expected_type_name, &c_size);
         char* error = (char *)malloc(200);
         sprintf(error, "argument dtype must be %s, not %s",
-			dataTypes[dtype],
-			dataTypes[current_dtype]);
+			expected_name,
+			current_name);
 		return error;
 	}