apacheGH-35040: [Python] Pyarrow scalar cast should use compute kernel (

apache#35395)

### Rationale for this change

Scalar cast should use the computer kernel just like Arrays, instead of its own custom implementation.

### Are these changes tested?

Added test cases for apacheGH-35370, apacheGH-34901, and apacheGH-35040

### Are there any user-facing changes?

The Scalar.cast() API is enhanced and backwards compatible. 
* Closes: apache#35040

Authored-by: Dane Pitkin <[email protected]>
Signed-off-by: Alenka Frim <[email protected]>

python/pyarrow/scalar.pxi

@@ -67,27 +67,29 @@ cdef class Scalar(_Weakrefable):
         """
         return self.wrapped.get().is_valid
 
-    def cast(self, object target_type):
+    def cast(self, object target_type=None, safe=None, options=None, memory_pool=None):
         """
-        Attempt a safe cast to target data type.
+        Cast scalar value to another data type.
+
+        See :func:`pyarrow.compute.cast` for usage.
 
         Parameters
         ----------
-        target_type : DataType or string coercible to DataType
-            The type to cast the scalar to.
+        target_type : DataType, default None
+            Type to cast scalar to.
+        safe : boolean, default True
+            Whether to check for conversion errors such as overflow.
+        options : CastOptions, default None
+            Additional checks pass by CastOptions
+        memory_pool : MemoryPool, optional
+            memory pool to use for allocations during function execution.
 
         Returns
         -------
         scalar : A Scalar of the given target data type.
         """
-        cdef:
-            DataType type = ensure_type(target_type)
-            shared_ptr[CScalar] result
-
-        with nogil:
-            result = GetResultValue(self.wrapped.get().CastTo(type.sp_type))
-
-        return Scalar.wrap(result)
+        return _pc().cast(self, target_type, safe=safe,
+                          options=options, memory_pool=memory_pool)
 
     def validate(self, *, full=False):
         """

python/pyarrow/tests/test_scalars.py

@@ -295,6 +295,35 @@ def test_cast():
         pa.scalar('foo').cast('int32')
 
 
+def test_cast_timestamp_to_string():
+    # GH-35370
+    pytest.importorskip("pytz")
+    import pytz
+    dt = datetime.datetime(2000, 1, 1, 0, 0, 0, tzinfo=pytz.utc)
+    ts = pa.scalar(dt, type=pa.timestamp("ns", tz="UTC"))
+    assert ts.cast(pa.string()) == pa.scalar('2000-01-01 00:00:00.000000000Z')
+
+
+def test_cast_float_to_int():
+    # GH-35040
+    float_scalar = pa.scalar(1.5, type=pa.float64())
+    unsafe_cast = float_scalar.cast(pa.int64(), safe=False)
+    expected_unsafe_cast = pa.scalar(1, type=pa.int64())
+    assert unsafe_cast == expected_unsafe_cast
+    with pytest.raises(pa.ArrowInvalid):
+        float_scalar.cast(pa.int64())  # verify default is safe cast
+
+
+def test_cast_int_to_float():
+    # GH-34901
+    int_scalar = pa.scalar(18014398509481983, type=pa.int64())
+    unsafe_cast = int_scalar.cast(pa.float64(), safe=False)
+    expected_unsafe_cast = pa.scalar(18014398509481983.0, type=pa.float64())
+    assert unsafe_cast == expected_unsafe_cast
+    with pytest.raises(pa.ArrowInvalid):
+        int_scalar.cast(pa.float64())  # verify default is safe cast
+
+
 @pytest.mark.pandas
 def test_timestamp():
     import pandas as pd