Closes #3337: Fix can_cast with NumPy 2.0 breaking changes

arkouda/numpy/_numeric.py

@@ -1,3 +1,4 @@
+import builtins
 import json
 from enum import Enum
 from typing import TYPE_CHECKING, List, Sequence, Tuple, TypeVar, Union
@@ -9,13 +10,19 @@
 
 from arkouda.client import generic_msg
 from arkouda.groupbyclass import GroupBy, groupable
-from arkouda.numpy.dtypes import _datatype_check, bigint
+from arkouda.numpy.dtypes import (
+    _datatype_check,
+    _is_dtype_in_union,
+    bigint,
+)
 from arkouda.numpy.dtypes import bool_ as ak_bool
+from arkouda.numpy.dtypes import dtype as ak_dtype
 from arkouda.numpy.dtypes import dtype as akdtype
 from arkouda.numpy.dtypes import float64 as ak_float64
 from arkouda.numpy.dtypes import int64 as ak_int64
 from arkouda.numpy.dtypes import (
     int_scalars,
+    isSupportedInt,
     isSupportedNumber,
     numeric_scalars,
     resolve_scalar_dtype,

arkouda/numpy/dtypes/dtypes.py

@@ -42,6 +42,7 @@
     "bitType",
     "bool_",
     "bool_scalars",
+    "can_cast",
     "complex128",
     "complex64",
     "dtype",
@@ -121,6 +122,36 @@ def dtype(dtype):
         return np.dtype(dtype)
 
 
+def can_cast(from_, to) -> builtins.bool:
+    """
+    Returns True if cast between data types can occur according to the casting rule.
+
+    Parameters
+    __________
+
+    from_: dtype, dtype specifier, NumPy scalar, or pdarray
+        Data type, NumPy scalar, or array to cast from.
+    to: dtype or dtype specifier
+        Data type to cast to.
+
+    Return
+    ------
+    bool
+        True if cast can occur according to the casting rule.
+
+    """
+    if isSupportedInt(from_):
+        if (from_ < 2**64) and (from_ >= 0) and (to == dtype(uint64)):
+            return True
+
+    if (
+        np.isscalar(from_) or _is_dtype_in_union(from_, numeric_scalars)
+    ) and not isinstance(from_, (int, float, complex)):
+        return np.can_cast(from_, to)
+
+    return False
+
+
 def _is_dtype_in_union(dtype, union_type) -> builtins.bool:
     """
     Check if a given type is in a typing.Union.

arkouda/pdarrayclass.py

@@ -20,9 +20,15 @@
     bigint,
 )
 from arkouda.numpy.dtypes import bool_ as akbool
-from arkouda.numpy.dtypes import bool_scalars, dtype
+from arkouda.numpy.dtypes import (
+    bool_scalars,
+    dtype,
+)
 from arkouda.numpy.dtypes import float64 as akfloat64
-from arkouda.numpy.dtypes import get_byteorder, get_server_byteorder
+from arkouda.numpy.dtypes import (
+    get_byteorder,
+    get_server_byteorder,
+)
 from arkouda.numpy.dtypes import int64 as akint64
 from arkouda.numpy.dtypes import (
     int_scalars,
@@ -571,7 +577,9 @@ def _binop(self, other: pdarray, op: str) -> pdarray:
         # pdarray binop scalar
         # If scalar cannot be safely cast, server will infer the return dtype
         dt = resolve_scalar_dtype(other)
-        if self.dtype != bigint and np.can_cast(other, self.dtype):
+        from arkouda.numpy.dtypes import can_cast as ak_can_cast
+
+        if self.dtype != bigint and ak_can_cast(other, self.dtype):
             # If scalar can be losslessly cast to array dtype,
             # do the cast so that return array will have same dtype
             dt = self.dtype.name
@@ -616,7 +624,9 @@ def _r_binop(self, other: pdarray, op: str) -> pdarray:
         # pdarray binop scalar
         # If scalar cannot be safely cast, server will infer the return dtype
         dt = resolve_scalar_dtype(other)
-        if self.dtype != bigint and np.can_cast(other, self.dtype):
+        from arkouda.numpy.dtypes import can_cast as ak_can_cast
+
+        if self.dtype != bigint and ak_can_cast(other, self.dtype):
             # If scalar can be losslessly cast to array dtype,
             # do the cast so that return array will have same dtype
             dt = self.dtype.name
@@ -4131,31 +4141,30 @@ def fmod(dividend: Union[pdarray, numeric_scalars], divisor: Union[pdarray, nume
         )
     # TODO: handle shape broadcasting for multidimensional arrays
 
+    #   The code below creates a command string for fmod2vv, fmod2vs or fmod2sv.
 
-#   The code below creates a command string for fmod2vv, fmod2vs or fmod2sv.
-
-    if isinstance(dividend, pdarray) and isinstance(divisor, pdarray) :
+    if isinstance(dividend, pdarray) and isinstance(divisor, pdarray):
         cmdstring = f"fmod2vv<{dividend.dtype},{dividend.ndim},{divisor.dtype}>"
 
-    elif isinstance(dividend, pdarray) and not (isinstance(divisor, pdarray)) :
-        if resolve_scalar_dtype(divisor) in ['float64', 'int64', 'uint64', 'bool'] :
-            acmd = 'fmod2vs_'+resolve_scalar_dtype(divisor)
-        else :  # this condition *should* be impossible because of the isSupportedNumber check
+    elif isinstance(dividend, pdarray) and not (isinstance(divisor, pdarray)):
+        if resolve_scalar_dtype(divisor) in ["float64", "int64", "uint64", "bool"]:
+            acmd = "fmod2vs_" + resolve_scalar_dtype(divisor)
+        else:  # this condition *should* be impossible because of the isSupportedNumber check
             raise TypeError(f"Scalar divisor type {resolve_scalar_dtype(divisor)} not allowed in fmod")
         cmdstring = f"{acmd}<{dividend.dtype},{dividend.ndim}>"
 
-    elif not (isinstance(dividend, pdarray) and isinstance(divisor, pdarray)) :
-        if resolve_scalar_dtype(dividend) in ['float64', 'int64', 'uint64', 'bool'] :
-            acmd = 'fmod2sv_'+resolve_scalar_dtype(dividend)
-        else :  # this condition *should* be impossible because of the isSupportedNumber check
+    elif not (isinstance(dividend, pdarray) and isinstance(divisor, pdarray)):
+        if resolve_scalar_dtype(dividend) in ["float64", "int64", "uint64", "bool"]:
+            acmd = "fmod2sv_" + resolve_scalar_dtype(dividend)
+        else:  # this condition *should* be impossible because of the isSupportedNumber check
             raise TypeError(f"Scalar dividend type {resolve_scalar_dtype(dividend)} not allowed in fmod")
         cmdstring = f"{acmd}<{divisor.dtype},{divisor.ndim}>"  # type: ignore[union-attr]
 
     else:
         m = mod(dividend, divisor)
         return _create_scalar_array(m)
 
-#   We reach here if this was any case other than scalar & scalar
+    #   We reach here if this was any case other than scalar & scalar
 
     return create_pdarray(
         cast(