Fix contains check in string column (#8834)

Fixes: #8832 

This PR fixes `contains` check in the `StringColumn`.  We were using `f"^{item}$"` to generate a regex and do a `contains_re` to check for an exact match for `item` in the `StringColumn`, but this approach would break if `item` by itself has some regex special characters, so replaced these checks with `libcudf.search.contains` which does the exact check for `item` in the `StringColumn`.

Authors:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

Approvers:
  - Ram (Ramakrishna Prabhu) (https://github.com/rgsl888prabhu)
  - Charles Blackmon-Luca (https://github.com/charlesbluca)

URL: #8834

python/cudf/cudf/core/column/string.py

@@ -5042,7 +5042,14 @@ def set_base_children(self, value: Tuple["column.ColumnBase", ...]):
         super().set_base_children(value)
 
     def __contains__(self, item: ScalarLike) -> bool:
-        return True in libstrings.contains_re(self, f"^{item}$")
+        if is_scalar(item):
+            return True in libcudf.search.contains(
+                self, column.as_column([item], dtype=self.dtype)
+            )
+        else:
+            return True in libcudf.search.contains(
+                self, column.as_column(item, dtype=self.dtype)
+            )
 
     def as_numerical_column(
         self, dtype: Dtype, **kwargs
@@ -5303,7 +5310,9 @@ def fillna(
             return super().fillna(method=method)
 
     def _find_first_and_last(self, value: ScalarLike) -> Tuple[int, int]:
-        found_indices = libstrings.contains_re(self, f"^{value}$")
+        found_indices = libcudf.search.contains(
+            self, column.as_column([value], dtype=self.dtype)
+        )
         found_indices = libcudf.unary.cast(found_indices, dtype=np.int32)
         first = column.as_column(found_indices).find_first_value(np.int32(1))
         last = column.as_column(found_indices).find_last_value(np.int32(1))

python/cudf/cudf/tests/test_categorical.py

@@ -830,3 +830,14 @@ def test_serialize_categorical_columns(data):
     df = cudf.DataFrame(data)
     recreated = df.__class__.deserialize(*df.serialize())
     assert_eq(recreated, df)
+
+
+@pytest.mark.parametrize(
+    "data", [["$ 1", "$ 2", "hello"], ["($) 1", "( 2", "hello", "^1$"]]
+)
+@pytest.mark.parametrize("value", ["$ 1", "hello", "$", "^1$"])
+def test_categorical_string_index_contains(data, value):
+    idx = cudf.CategoricalIndex(data)
+    pidx = idx.to_pandas()
+
+    assert_eq(value in idx, value in pidx)