Backport PR pandas-dev#56691 on branch 2.2.x (Bug pyarrow implementat…

…ion of str.fullmatch matches partial string. issue pandas-dev#56652) (pandas-dev#56715) Backport PR pandas-dev#56691: Bug pyarrow implementation of str.fullmatch matches partial string. issue pandas-dev#56652 Co-authored-by: JackCollins91 <[email protected]>
meeseeksmachine · Jan 3, 2024 · d43af63 · d43af63
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Showing 5 changed files with 24 additions and 9 deletions.
diff --git a/doc/source/whatsnew/v2.2.0.rst b/doc/source/whatsnew/v2.2.0.rst
@@ -805,6 +805,7 @@ Strings
 - Bug in :meth:`Series.str.replace` when ``n < 0`` for :class:`ArrowDtype` with ``pyarrow.string`` (:issue:`56404`)
 - Bug in :meth:`Series.str.startswith` and :meth:`Series.str.endswith` with arguments of type ``tuple[str, ...]`` for :class:`ArrowDtype` with ``pyarrow.string`` dtype (:issue:`56579`)
 - Bug in :meth:`Series.str.startswith` and :meth:`Series.str.endswith` with arguments of type ``tuple[str, ...]`` for ``string[pyarrow]`` (:issue:`54942`)
+- Bug in :meth:`str.fullmatch` when ``dtype=pandas.ArrowDtype(pyarrow.string()))`` allows partial matches when regex ends in literal //$ (:issue:`56652`)
 - Bug in comparison operations for ``dtype="string[pyarrow_numpy]"`` raising if dtypes can't be compared (:issue:`56008`)
 
 Interval

diff --git a/pandas/core/arrays/arrow/array.py b/pandas/core/arrays/arrow/array.py
@@ -2277,7 +2277,7 @@ def _str_match(
     def _str_fullmatch(
         self, pat, case: bool = True, flags: int = 0, na: Scalar | None = None
     ):
-        if not pat.endswith("$") or pat.endswith("//$"):
+        if not pat.endswith("$") or pat.endswith("\\$"):
             pat = f"{pat}$"
         return self._str_match(pat, case, flags, na)
 

diff --git a/pandas/core/arrays/string_arrow.py b/pandas/core/arrays/string_arrow.py
@@ -433,7 +433,7 @@ def _str_match(
     def _str_fullmatch(
         self, pat, case: bool = True, flags: int = 0, na: Scalar | None = None
     ):
-        if not pat.endswith("$") or pat.endswith("//$"):
+        if not pat.endswith("$") or pat.endswith("\\$"):
             pat = f"{pat}$"
         return self._str_match(pat, case, flags, na)
 

diff --git a/pandas/tests/extension/test_arrow.py b/pandas/tests/extension/test_arrow.py
@@ -1903,16 +1903,21 @@ def test_str_match(pat, case, na, exp):
 @pytest.mark.parametrize(
     "pat, case, na, exp",
     [
-        ["abc", False, None, [True, None]],
-        ["Abc", True, None, [False, None]],
-        ["bc", True, None, [False, None]],
-        ["ab", False, True, [True, True]],
-        ["a[a-z]{2}", False, None, [True, None]],
-        ["A[a-z]{1}", True, None, [False, None]],
+        ["abc", False, None, [True, True, False, None]],
+        ["Abc", True, None, [False, False, False, None]],
+        ["bc", True, None, [False, False, False, None]],
+        ["ab", False, None, [True, True, False, None]],
+        ["a[a-z]{2}", False, None, [True, True, False, None]],
+        ["A[a-z]{1}", True, None, [False, False, False, None]],
+        # GH Issue: #56652
+        ["abc$", False, None, [True, False, False, None]],
+        ["abc\\$", False, None, [False, True, False, None]],
+        ["Abc$", True, None, [False, False, False, None]],
+        ["Abc\\$", True, None, [False, False, False, None]],
     ],
 )
 def test_str_fullmatch(pat, case, na, exp):
-    ser = pd.Series(["abc", None], dtype=ArrowDtype(pa.string()))
+    ser = pd.Series(["abc", "abc$", "$abc", None], dtype=ArrowDtype(pa.string()))
     result = ser.str.match(pat, case=case, na=na)
     expected = pd.Series(exp, dtype=ArrowDtype(pa.bool_()))
     tm.assert_series_equal(result, expected)

diff --git a/pandas/tests/strings/test_find_replace.py b/pandas/tests/strings/test_find_replace.py
@@ -730,6 +730,15 @@ def test_fullmatch(any_string_dtype):
     tm.assert_series_equal(result, expected)
 
 
+def test_fullmatch_dollar_literal(any_string_dtype):
+    # GH 56652
+    ser = Series(["foo", "foo$foo", np.nan, "foo$"], dtype=any_string_dtype)
+    result = ser.str.fullmatch("foo\\$")
+    expected_dtype = "object" if any_string_dtype in object_pyarrow_numpy else "boolean"
+    expected = Series([False, False, np.nan, True], dtype=expected_dtype)
+    tm.assert_series_equal(result, expected)
+
+
 def test_fullmatch_na_kwarg(any_string_dtype):
     ser = Series(
         ["fooBAD__barBAD", "BAD_BADleroybrown", np.nan, "foo"], dtype=any_string_dtype