raise error on unsafe decimal parse with pyarrow types (#56985)

* raise error on unsafe decimal parse with pyarrow types

* fix min versions

* restore typeerrro

* success

---------

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

Author: rohanjain101

pandas/core/arrays/arrow/array.py

@@ -527,11 +527,7 @@ def _box_pa_array(
             else:
                 try:
                     pa_array = pa_array.cast(pa_type)
-                except (
-                    pa.ArrowInvalid,
-                    pa.ArrowTypeError,
-                    pa.ArrowNotImplementedError,
-                ):
+                except (pa.ArrowNotImplementedError, pa.ArrowTypeError):
                     if pa.types.is_string(pa_array.type) or pa.types.is_large_string(
                         pa_array.type
                     ):

pandas/tests/extension/test_arrow.py

@@ -3203,6 +3203,30 @@ def test_pow_missing_operand():
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.skipif(
+    pa_version_under11p0, reason="Decimal128 to string cast implemented in pyarrow 11"
+)
+def test_decimal_parse_raises():
+    # GH 56984
+    ser = pd.Series(["1.2345"], dtype=ArrowDtype(pa.string()))
+    with pytest.raises(
+        pa.lib.ArrowInvalid, match="Rescaling Decimal128 value would cause data loss"
+    ):
+        ser.astype(ArrowDtype(pa.decimal128(1, 0)))
+
+
+@pytest.mark.skipif(
+    pa_version_under11p0, reason="Decimal128 to string cast implemented in pyarrow 11"
+)
+def test_decimal_parse_succeeds():
+    # GH 56984
+    ser = pd.Series(["1.2345"], dtype=ArrowDtype(pa.string()))
+    dtype = ArrowDtype(pa.decimal128(5, 4))
+    result = ser.astype(dtype)
+    expected = pd.Series([Decimal("1.2345")], dtype=dtype)
+    tm.assert_series_equal(result, expected)
+
+
 @pytest.mark.parametrize("pa_type", tm.TIMEDELTA_PYARROW_DTYPES)
 def test_duration_fillna_numpy(pa_type):
     # GH 54707