Support multiplication of pd.ArrowDtype(pa.string()) and integral value where integral value is a series (pandas-dev#56538)

* allow repeat count to be a series

* fix validation

* gh reference

* fix conditional logic

* Revert "fix conditional logic"

This reverts commit 15f1990.

* remove condition

* inline

---------

Co-authored-by: Rohan Jain <[email protected]>

Author: rohanjain101

pandas/core/arrays/arrow/array.py

@@ -693,22 +693,31 @@ def _evaluate_op_method(self, other, op, arrow_funcs):
         other = self._box_pa(other)
 
         if pa.types.is_string(pa_type) or pa.types.is_binary(pa_type):
-            if op in [operator.add, roperator.radd, operator.mul, roperator.rmul]:
+            if op in [operator.add, roperator.radd]:
                 sep = pa.scalar("", type=pa_type)
                 if op is operator.add:
                     result = pc.binary_join_element_wise(self._pa_array, other, sep)
                 elif op is roperator.radd:
                     result = pc.binary_join_element_wise(other, self._pa_array, sep)
-                else:
-                    if not (
-                        isinstance(other, pa.Scalar) and pa.types.is_integer(other.type)
-                    ):
-                        raise TypeError("Can only string multiply by an integer.")
-                    result = pc.binary_join_element_wise(
-                        *([self._pa_array] * other.as_py()), sep
-                    )
                 return type(self)(result)
-
+            elif op in [operator.mul, roperator.rmul]:
+                binary = self._pa_array
+                integral = other
+                if not pa.types.is_integer(integral.type):
+                    raise TypeError("Can only string multiply by an integer.")
+                pa_integral = pc.if_else(pc.less(integral, 0), 0, integral)
+                result = pc.binary_repeat(binary, pa_integral)
+                return type(self)(result)
+        elif (
+            pa.types.is_string(other.type) or pa.types.is_binary(other.type)
+        ) and op in [operator.mul, roperator.rmul]:
+            binary = other
+            integral = self._pa_array
+            if not pa.types.is_integer(integral.type):
+                raise TypeError("Can only string multiply by an integer.")
+            pa_integral = pc.if_else(pc.less(integral, 0), 0, integral)
+            result = pc.binary_repeat(binary, pa_integral)
+            return type(self)(result)
         if (
             isinstance(other, pa.Scalar)
             and pc.is_null(other).as_py()

pandas/tests/extension/test_arrow.py

@@ -1334,6 +1334,26 @@ def test_arrowdtype_construct_from_string_type_only_one_pyarrow():
         pd.Series(range(3), dtype=invalid)
 
 
+def test_arrow_string_multiplication():
+    # GH 56537
+    binary = pd.Series(["abc", "defg"], dtype=ArrowDtype(pa.string()))
+    repeat = pd.Series([2, -2], dtype="int64[pyarrow]")
+    result = binary * repeat
+    expected = pd.Series(["abcabc", ""], dtype=ArrowDtype(pa.string()))
+    tm.assert_series_equal(result, expected)
+    reflected_result = repeat * binary
+    tm.assert_series_equal(result, reflected_result)
+
+
+def test_arrow_string_multiplication_scalar_repeat():
+    binary = pd.Series(["abc", "defg"], dtype=ArrowDtype(pa.string()))
+    result = binary * 2
+    expected = pd.Series(["abcabc", "defgdefg"], dtype=ArrowDtype(pa.string()))
+    tm.assert_series_equal(result, expected)
+    reflected_result = 2 * binary
+    tm.assert_series_equal(reflected_result, expected)
+
+
 @pytest.mark.parametrize(
     "interpolation", ["linear", "lower", "higher", "nearest", "midpoint"]
 )