diff --git a/pandas/core/indexers.py b/pandas/core/indexers.py
index cadae9da6092f..4fb42fce29e1a 100644
--- a/pandas/core/indexers.py
+++ b/pandas/core/indexers.py
@@ -270,6 +270,33 @@ def deprecate_ndim_indexing(result):
         )
 
 
+def unpack_1tuple(tup):
+    """
+    If we have a length-1 tuple/list that contains a slice, unpack to just
+    the slice.
+
+    Notes
+    -----
+    The list case is deprecated.
+    """
+    if len(tup) == 1 and isinstance(tup[0], slice):
+        # if we don't have a MultiIndex, we may still be able to handle
+        #  a 1-tuple.  see test_1tuple_without_multiindex
+
+        if isinstance(tup, list):
+            # GH#31299
+            warnings.warn(
+                "Indexing with a single-item list containing a "
+                "slice is deprecated and will raise in a future "
+                "version.  Pass a tuple instead.",
+                FutureWarning,
+                stacklevel=3,
+            )
+
+        return tup[0]
+    return tup
+
+
 # -----------------------------------------------------------
 # Public indexer validation
 
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 256586f3d36a1..15fe0bb98b536 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -72,7 +72,7 @@
     sanitize_array,
 )
 from pandas.core.generic import NDFrame
-from pandas.core.indexers import maybe_convert_indices
+from pandas.core.indexers import maybe_convert_indices, unpack_1tuple
 from pandas.core.indexes.accessors import CombinedDatetimelikeProperties
 from pandas.core.indexes.api import (
     Float64Index,
@@ -851,6 +851,8 @@ def __getitem__(self, key):
         key_is_scalar = is_scalar(key)
         if key_is_scalar:
             key = self.index._convert_scalar_indexer(key, kind="getitem")
+        elif isinstance(key, (list, tuple)):
+            key = unpack_1tuple(key)
 
         if key_is_scalar or isinstance(self.index, MultiIndex):
             # Otherwise index.get_value will raise InvalidIndexError
@@ -893,16 +895,7 @@ def _get_with(self, key):
                 "supported, use the appropriate DataFrame column"
             )
         elif isinstance(key, tuple):
-            try:
-                return self._get_values_tuple(key)
-            except ValueError:
-                # if we don't have a MultiIndex, we may still be able to handle
-                #  a 1-tuple.  see test_1tuple_without_multiindex
-                if len(key) == 1:
-                    key = key[0]
-                    if isinstance(key, slice):
-                        return self._get_values(key)
-                raise
+            return self._get_values_tuple(key)
 
         if not isinstance(key, (list, np.ndarray, ExtensionArray, Series, Index)):
             key = list(key)
@@ -924,26 +917,8 @@ def _get_with(self, key):
             else:
                 return self.iloc[key]
 
-        if isinstance(key, (list, tuple)):
-            # TODO: de-dup with tuple case handled above?
+        if isinstance(key, list):
             # handle the dup indexing case GH#4246
-            if len(key) == 1 and isinstance(key[0], slice):
-                # [slice(0, 5, None)] will break if you convert to ndarray,
-                # e.g. as requested by np.median
-                # FIXME: hack
-                if isinstance(key, list):
-                    # GH#31299
-                    warnings.warn(
-                        "Indexing with a single-item list containing a "
-                        "slice is deprecated and will raise in a future "
-                        "version.  Pass a tuple instead.",
-                        FutureWarning,
-                        stacklevel=3,
-                    )
-                    # TODO: use a message more like numpy's?
-                    key = tuple(key)
-                return self._get_values(key)
-
             return self.loc[key]
 
         return self.reindex(key)