String dtype: avoid surfacing pyarrow excetion in binary operations

Author: jorisvandenbossche

pandas/core/arrays/arrow/array.py

@@ -736,8 +736,19 @@ def _cmp_method(self, other, op) -> ArrowExtensionArray:
             )
         return ArrowExtensionArray(result)
 
+    def _op_method_error_message(self, other, op) -> str:
+        if hasattr(other, "dtype"):
+            other_type = f"dtype '{other.dtype}'"
+        else:
+            other_type = f"object of type {type(other)}"
+        return (
+            f"operation '{op.__name__}' not supported for "
+            f"dtype '{self.dtype}' with {other_type}"
+        )
+
     def _evaluate_op_method(self, other, op, arrow_funcs) -> Self:
         pa_type = self._pa_array.type
+        other_original = other
         other = self._box_pa(other)
 
         if (
@@ -747,10 +758,15 @@ def _evaluate_op_method(self, other, op, arrow_funcs) -> Self:
         ):
             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)
+                try:
+                    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)
+                except pa.lib.ArrowNotImplementedError as err:
+                    raise TypeError(
+                        self._op_method_error_message(other_original, op)
+                    ) from err
                 return type(self)(result)
             elif op in [operator.mul, roperator.rmul]:
                 binary = self._pa_array
@@ -782,9 +798,14 @@ def _evaluate_op_method(self, other, op, arrow_funcs) -> Self:
 
         pc_func = arrow_funcs[op.__name__]
         if pc_func is NotImplemented:
+            if pa.types.is_string(pa_type) or pa.types.is_large_string(pa_type):
+                raise TypeError(self._op_method_error_message(other_original, op))
             raise NotImplementedError(f"{op.__name__} not implemented.")
 
-        result = pc_func(self._pa_array, other)
+        try:
+            result = pc_func(self._pa_array, other)
+        except pa.lib.ArrowNotImplementedError as err:
+            raise TypeError(self._op_method_error_message(other_original, op)) from err
         return type(self)(result)
 
     def _logical_method(self, other, op) -> Self:

pandas/tests/arrays/boolean/test_arithmetic.py

@@ -3,10 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
-from pandas.compat import HAS_PYARROW
-
 import pandas as pd
 import pandas._testing as tm
 
@@ -94,19 +90,8 @@ def test_op_int8(left_array, right_array, opname):
 # -----------------------------------------------------------------------------
 
 
-@pytest.mark.xfail(
-    using_string_dtype() and not HAS_PYARROW, reason="TODO(infer_string)"
-)
-def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string):
+def test_error_invalid_values(data, all_arithmetic_operators):
     # invalid ops
-
-    if using_infer_string:
-        import pyarrow as pa
-
-        err = (TypeError, pa.lib.ArrowNotImplementedError, NotImplementedError)
-    else:
-        err = TypeError
-
     op = all_arithmetic_operators
     s = pd.Series(data)
     ops = getattr(s, op)
@@ -116,7 +101,8 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
         "did not contain a loop with signature matching types|"
         "BooleanArray cannot perform the operation|"
         "not supported for the input types, and the inputs could not be safely coerced "
-        "to any supported types according to the casting rule ''safe''"
+        "to any supported types according to the casting rule ''safe''|"
+        "not supported for dtype"
     )
     with pytest.raises(TypeError, match=msg):
         ops("foo")
@@ -125,9 +111,10 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
             r"unsupported operand type\(s\) for",
             "Concatenation operation is not implemented for NumPy arrays",
             "has no kernel",
+            "not supported for dtype",
         ]
     )
-    with pytest.raises(err, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops(pd.Timestamp("20180101"))
 
     # invalid array-likes
@@ -140,7 +127,8 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
                 "not all arguments converted during string formatting",
                 "has no kernel",
                 "not implemented",
+                "not supported for dtype",
             ]
         )
-        with pytest.raises(err, match=msg):
+        with pytest.raises(TypeError, match=msg):
             ops(pd.Series("foo", index=s.index))

pandas/tests/arrays/floating/test_arithmetic.py

@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 import pandas as pd
 import pandas._testing as tm
 from pandas.core.arrays import FloatingArray
@@ -124,19 +122,11 @@ def test_arith_zero_dim_ndarray(other):
 # -----------------------------------------------------------------------------
 
 
-@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
-def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string):
+def test_error_invalid_values(data, all_arithmetic_operators):
     op = all_arithmetic_operators
     s = pd.Series(data)
     ops = getattr(s, op)
 
-    if using_infer_string:
-        import pyarrow as pa
-
-        errs = (TypeError, pa.lib.ArrowNotImplementedError, NotImplementedError)
-    else:
-        errs = TypeError
-
     # invalid scalars
     msg = "|".join(
         [
@@ -152,15 +142,17 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
             "Concatenation operation is not implemented for NumPy arrays",
             "has no kernel",
             "not implemented",
+            "not supported for dtype",
+            "Can only string multiply by an integer",
         ]
     )
-    with pytest.raises(errs, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops("foo")
-    with pytest.raises(errs, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops(pd.Timestamp("20180101"))
 
     # invalid array-likes
-    with pytest.raises(errs, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops(pd.Series("foo", index=s.index))
 
     msg = "|".join(
@@ -181,9 +173,10 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
             "cannot subtract DatetimeArray from ndarray",
             "has no kernel",
             "not implemented",
+            "not supported for dtype",
         ]
     )
-    with pytest.raises(errs, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops(pd.Series(pd.date_range("20180101", periods=len(s))))
 
 

pandas/tests/arrays/integer/test_arithmetic.py

@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 import pandas as pd
 import pandas._testing as tm
 from pandas.core import ops
@@ -174,19 +172,11 @@ def test_numpy_zero_dim_ndarray(other):
 # -----------------------------------------------------------------------------
 
 
-@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
 def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string):
     op = all_arithmetic_operators
     s = pd.Series(data)
     ops = getattr(s, op)
 
-    if using_infer_string:
-        import pyarrow as pa
-
-        errs = (TypeError, pa.lib.ArrowNotImplementedError, NotImplementedError)
-    else:
-        errs = TypeError
-
     # invalid scalars
     msg = "|".join(
         [
@@ -201,24 +191,21 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
             "has no kernel",
             "not implemented",
             "The 'out' kwarg is necessary. Use numpy.strings.multiply without it.",
+            "not supported for dtype",
         ]
     )
-    with pytest.raises(errs, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops("foo")
-    with pytest.raises(errs, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops(pd.Timestamp("20180101"))
 
     # invalid array-likes
     str_ser = pd.Series("foo", index=s.index)
     # with pytest.raises(TypeError, match=msg):
-    if (
-        all_arithmetic_operators
-        in [
-            "__mul__",
-            "__rmul__",
-        ]
-        and not using_infer_string
-    ):  # (data[~data.isna()] >= 0).all():
+    if all_arithmetic_operators in [
+        "__mul__",
+        "__rmul__",
+    ]:  # (data[~data.isna()] >= 0).all():
         res = ops(str_ser)
         expected = pd.Series(["foo" * x for x in data], index=s.index)
         expected = expected.fillna(np.nan)
@@ -227,7 +214,7 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
         #  more-correct than np.nan here.
         tm.assert_series_equal(res, expected)
     else:
-        with pytest.raises(errs, match=msg):
+        with pytest.raises(TypeError, match=msg):
             ops(str_ser)
 
     msg = "|".join(
@@ -242,9 +229,10 @@ def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string
             "cannot subtract DatetimeArray from ndarray",
             "has no kernel",
             "not implemented",
+            "not supported for dtype",
         ]
     )
-    with pytest.raises(errs, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ops(pd.Series(pd.date_range("20180101", periods=len(s))))