CLN: trim unreachable branches in _compare_or_regex_search (#33598)

Author: jbrockmendel

pandas/core/internals/managers.py

@@ -1723,7 +1723,7 @@ def form_blocks(arrays, names: Index, axes) -> List[Block]:
     return blocks
 
 
-def _simple_blockify(tuples, dtype):
+def _simple_blockify(tuples, dtype) -> List[Block]:
     """
     return a single array of a block that has a single dtype; if dtype is
     not None, coerce to this dtype
@@ -1846,7 +1846,7 @@ def _merge_blocks(
 
 
 def _compare_or_regex_search(
-    a: Union[ArrayLike, Scalar], b: Union[ArrayLike, Scalar], regex: bool = False
+    a: ArrayLike, b: Scalar, regex: bool = False
 ) -> Union[ArrayLike, bool]:
     """
     Compare two array_like inputs of the same shape or two scalar values
@@ -1856,8 +1856,8 @@ def _compare_or_regex_search(
 
     Parameters
     ----------
-    a : array_like or scalar
-    b : array_like or scalar
+    a : array_like
+    b : scalar
     regex : bool, default False
 
     Returns
@@ -1866,29 +1866,21 @@ def _compare_or_regex_search(
     """
 
     def _check_comparison_types(
-        result: Union[ArrayLike, bool],
-        a: Union[ArrayLike, Scalar],
-        b: Union[ArrayLike, Scalar],
-    ) -> Union[ArrayLike, bool]:
+        result: Union[ArrayLike, bool], a: ArrayLike, b: Scalar,
+    ):
         """
         Raises an error if the two arrays (a,b) cannot be compared.
         Otherwise, returns the comparison result as expected.
         """
-        if is_scalar(result) and (
-            isinstance(a, np.ndarray) or isinstance(b, np.ndarray)
-        ):
+        if is_scalar(result) and isinstance(a, np.ndarray):
             type_names = [type(a).__name__, type(b).__name__]
 
             if isinstance(a, np.ndarray):
                 type_names[0] = f"ndarray(dtype={a.dtype})"
 
-            if isinstance(b, np.ndarray):
-                type_names[1] = f"ndarray(dtype={b.dtype})"
-
             raise TypeError(
                 f"Cannot compare types {repr(type_names[0])} and {repr(type_names[1])}"
             )
-        return result
 
     if not regex:
         op = lambda x: operator.eq(x, b)
@@ -1902,18 +1894,13 @@ def _check_comparison_types(
     # GH#32621 use mask to avoid comparing to NAs
     if isinstance(a, np.ndarray) and not isinstance(b, np.ndarray):
         mask = np.reshape(~(isna(a)), a.shape)
-    elif isinstance(b, np.ndarray) and not isinstance(a, np.ndarray):
-        mask = np.reshape(~(isna(b)), b.shape)
-    elif isinstance(a, np.ndarray) and isinstance(b, np.ndarray):
-        mask = ~(isna(a) | isna(b))
     if isinstance(a, np.ndarray):
         a = a[mask]
-    if isinstance(b, np.ndarray):
-        b = b[mask]
 
     if is_datetimelike_v_numeric(a, b) or is_numeric_v_string_like(a, b):
         # GH#29553 avoid deprecation warnings from numpy
-        return _check_comparison_types(False, a, b)
+        _check_comparison_types(False, a, b)
+        return False
 
     result = op(a)
 
@@ -1924,7 +1911,8 @@ def _check_comparison_types(
         tmp[mask] = result
         result = tmp
 
-    return _check_comparison_types(result, a, b)
+    _check_comparison_types(result, a, b)
+    return result
 
 
 def _fast_count_smallints(arr: np.ndarray) -> np.ndarray: