move list-like check inside

Author: jorisvandenbossche

pandas/core/arrays/categorical.py

@@ -2001,8 +2001,7 @@ def __getitem__(self, key):
             else:
                 return self.categories[i]
 
-        if is_list_like(key) and not isinstance(key, tuple):
-            key = check_array_indexer(self, key)
+        key = check_array_indexer(self, key)
 
         result = self._codes[key]
         if result.ndim > 1:

pandas/core/arrays/datetimelike.py

@@ -530,7 +530,7 @@ def __getitem__(self, key):
             # see https://github.com/pandas-dev/pandas/issues/31299, need to allow
             # this for now (would otherwise raise in check_array_indexer)
             pass
-        elif is_list_like(key) and not isinstance(key, tuple):
+        else:
             key = check_array_indexer(self, key)
 
         is_period = is_period_dtype(self)

pandas/core/arrays/interval.py

@@ -496,8 +496,7 @@ def __len__(self) -> int:
         return len(self.left)
 
     def __getitem__(self, value):
-        if is_list_like(value) and not isinstance(value, tuple):
-            value = check_array_indexer(self, value)
+        value = check_array_indexer(self, value)
         left = self.left[value]
         right = self.right[value]
 

pandas/core/arrays/masked.py

@@ -4,12 +4,7 @@
 
 from pandas._libs import lib, missing as libmissing
 
-from pandas.core.dtypes.common import (
-    is_integer,
-    is_list_like,
-    is_object_dtype,
-    is_string_dtype,
-)
+from pandas.core.dtypes.common import is_integer, is_object_dtype, is_string_dtype
 from pandas.core.dtypes.missing import isna, notna
 
 from pandas.core.algorithms import take
@@ -39,8 +34,7 @@ def __getitem__(self, item):
                 return self.dtype.na_value
             return self._data[item]
 
-        elif is_list_like(item) and not isinstance(item, tuple):
-            item = check_array_indexer(self, item)
+        item = check_array_indexer(self, item)
 
         return type(self)(self._data[item], self._mask[item])
 

pandas/core/arrays/numpy_.py

@@ -9,7 +9,6 @@
 from pandas.util._decorators import Appender
 from pandas.util._validators import validate_fillna_kwargs
 
-from pandas.core.dtypes.common import is_list_like
 from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
 from pandas.core.dtypes.inference import is_array_like
@@ -234,8 +233,7 @@ def __getitem__(self, item):
         if isinstance(item, type(self)):
             item = item._ndarray
 
-        elif is_list_like(item) and not isinstance(item, tuple):
-            item = check_array_indexer(self, item)
+        item = check_array_indexer(self, item)
 
         result = self._ndarray[item]
         if not lib.is_scalar(item):

pandas/core/arrays/sparse/array.py

@@ -29,7 +29,6 @@
     is_datetime64_any_dtype,
     is_dtype_equal,
     is_integer,
-    is_list_like,
     is_object_dtype,
     is_scalar,
     is_string_dtype,
@@ -770,8 +769,7 @@ def __getitem__(self, key):
                 else:
                     key = np.asarray(key)
 
-            if is_list_like(key) and not isinstance(key, tuple):
-                key = check_array_indexer(self, key)
+            key = check_array_indexer(self, key)
 
             if com.is_bool_indexer(key):
                 key = check_bool_indexer(self, key)

pandas/core/indexers.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 
-from pandas._typing import AnyArrayLike
+from pandas._typing import Any, AnyArrayLike
 
 from pandas.core.dtypes.common import (
     is_array_like,
@@ -274,14 +274,18 @@ def deprecate_ndim_indexing(result):
 # Public indexer validation
 
 
-def check_array_indexer(array: AnyArrayLike, indexer) -> np.ndarray:
+def check_array_indexer(array: AnyArrayLike, indexer: Any) -> Any:
     """
     Check if `indexer` is a valid array indexer for `array`.
 
     For a boolean mask, `array` and `indexer` are checked to have the same
     length. The dtype is validated, and if it is an integer or boolean
     ExtensionArray, it is checked if there are missing values present, and
-    it is converted to the appropriate numpy array.
+    it is converted to the appropriate numpy array. Other dtypes will raise
+    an error.
+
+    Non-array indexers (integer, slice, Ellipsis, tuples, ..) are passed
+    through as is.
 
     .. versionadded:: 1.0.0
 
@@ -290,9 +294,9 @@ def check_array_indexer(array: AnyArrayLike, indexer) -> np.ndarray:
     array : array-like
         The array that is being indexed (only used for the length).
     indexer : array-like or list-like
-        The array-like that's used to index. The function assumes this is an
-        array-like, and input that is not yet an numpy array or an ExtensionArray
-        is converted to one.
+        The array-like that's used to index. List-like input that is not yet
+        a numpy array or an ExtensionArray is converted to one. Other input
+        types are passed through as is
 
     Returns
     -------
@@ -369,11 +373,23 @@ def check_array_indexer(array: AnyArrayLike, indexer) -> np.ndarray:
     """
     from pandas.core.construction import array as pd_array
 
+    # whathever is not an array-like is returned as-is (possible valid array
+    # indexers that are not array-like: integer, slice, Ellipsis, None)
+    # In this context, tuples are not considered as array-like, as they have
+    # a specific meaning in indexing (multi-dimensional indexing)
+    if is_list_like(indexer):
+        if isinstance(indexer, tuple):
+            return indexer
+    else:
+        return indexer
+
+    # convert list-likes to array
     if not is_array_like(indexer):
         indexer = pd_array(indexer)
         if len(indexer) == 0:
             # empty list is converted to float array by pd.array
             indexer = np.array([], dtype=np.intp)
+
     dtype = indexer.dtype
     if is_bool_dtype(dtype):
         try:

pandas/tests/extension/decimal/array.py

@@ -116,8 +116,7 @@ def __getitem__(self, item):
             return self._data[item]
         else:
             # array, slice.
-            if pd.api.types.is_list_like(item):
-                item = pd.api.indexers.check_array_indexer(self, item)
+            item = pd.api.indexers.check_array_indexer(self, item)
             return type(self)(self._data[item])
 
     def take(self, indexer, allow_fill=False, fill_value=None):

pandas/tests/indexing/test_check_indexer.py

@@ -85,3 +85,13 @@ def test_raise_invalid_array_dtypes(indexer):
     msg = "arrays used as indices must be of integer or boolean type"
     with pytest.raises(IndexError, match=msg):
         check_array_indexer(array, indexer)
+
+
+@pytest.mark.parametrize(
+    "indexer", [None, Ellipsis, slice(0, 3), (None,)],
+)
+def test_pass_through_non_array_likes(indexer):
+    array = np.array([1, 2, 3])
+
+    result = check_array_indexer(array, indexer)
+    assert result == indexer