Back to is_ordered_list_like

pandas/core/dtypes/common.py

@@ -18,9 +18,9 @@
     ABCSparseArray, ABCSparseSeries, ABCCategoricalIndex, ABCIndexClass,
     ABCDateOffset)
 from pandas.core.dtypes.inference import (  # noqa:F401
-    is_bool, is_integer, is_float, is_number, is_decimal, is_complex,
-    is_re, is_re_compilable, is_dict_like, is_string_like, is_file_like,
-    is_list_like, is_nested_list_like, is_sequence, is_named_tuple,
+    is_bool, is_integer, is_float, is_number, is_decimal, is_complex, is_re,
+    is_re_compilable, is_dict_like, is_string_like, is_file_like, is_list_like,
+    is_ordered_list_like, is_nested_list_like, is_sequence, is_named_tuple,
     is_hashable, is_iterator, is_array_like, is_scalar, is_interval)
 
 

pandas/core/dtypes/inference.py

@@ -247,7 +247,7 @@ def is_re_compilable(obj):
         return True
 
 
-def is_list_like(obj, strict=False):
+def is_list_like(obj):
     """
     Check if the object is list-like.
 
@@ -259,8 +259,6 @@ def is_list_like(obj, strict=False):
     Parameters
     ----------
     obj : The object to check.
-    strict : boolean, default False
-        If this parameter is True, sets will not be considered list-like
 
     Returns
     -------
@@ -289,9 +287,28 @@ def is_list_like(obj, strict=False):
             # we do not count strings/unicode/bytes as list-like
             and not isinstance(obj, string_and_binary_types)
             # exclude zero-dimensional numpy arrays, effectively scalars
-            and not (isinstance(obj, np.ndarray) and obj.ndim == 0)
-            # exclude sets if ordered_only
-            and not (strict and isinstance(obj, Set)))
+            and not (isinstance(obj, np.ndarray) and obj.ndim == 0))
+
+
+def is_ordered_list_like(obj):
+    """
+    Check if the object is list-like and has a defined order
+
+    Works like :meth:`is_list_like` but excludes sets. Note that iterators can
+    not be inspected for order - this check will return True but it is up to
+    the user to make sure that their iterators are generated in an ordered way.
+
+    Parameters
+    ----------
+    obj : The object to check.
+
+    Returns
+    -------
+    is_ordered_list_like : bool
+        Whether `obj` is an ordered list-like
+    """
+    list_like = is_list_like(obj)
+    return list_like and not isinstance(obj, Set)
 
 
 def is_array_like(obj):

pandas/core/strings.py

@@ -11,6 +11,7 @@
     is_object_dtype,
     is_string_like,
     is_list_like,
+    is_ordered_list_like,
     is_scalar,
     is_integer,
     is_re)
@@ -1996,12 +1997,12 @@ def _get_series_list(self, others, ignore_index=False):
         elif isinstance(others, np.ndarray) and others.ndim == 2:
             others = DataFrame(others, index=idx)
             return ([others[x] for x in others], False)
-        elif is_list_like(others, strict=True):
+        elif is_ordered_list_like(others):
             others = list(others)  # ensure iterators do not get read twice etc
 
             # in case of list-like `others`, all elements must be
             # either one-dimensional list-likes or scalars
-            if all(is_list_like(x, strict=True) for x in others):
+            if all(is_ordered_list_like(x) for x in others):
                 los = []
                 join_warn = False
                 depr_warn = False
@@ -2029,7 +2030,7 @@ def _get_series_list(self, others, ignore_index=False):
                     # nested list-likes are forbidden:
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
-                                or all(not is_list_like(x, strict=True)
+                                or all(not is_ordered_list_like(x)
                                        for x in nxt))
 
                     # DataFrame is false positive of is_legal
@@ -2048,7 +2049,7 @@ def _get_series_list(self, others, ignore_index=False):
                                   'deprecated and will be removed in a future '
                                   'version.', FutureWarning, stacklevel=3)
                 return (los, join_warn)
-            elif all(not is_list_like(x, strict=True) for x in others):
+            elif all(not is_ordered_list_like(x) for x in others):
                 return ([Series(others, index=idx)], False)
         raise TypeError(err_msg)
 

pandas/tests/dtypes/test_inference.py

@@ -88,15 +88,15 @@ def test_is_list_like_fails(ll):
         DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
         np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
     ])
-def test_is_list_like_strict_passes(ll):
-    assert inference.is_list_like(ll, strict=True)
+def test_is_ordered_list_like_strict_passes(ll):
+    assert inference.is_ordered_list_like(ll)
 
 
 @pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2),
                                 {1, 'a'}, frozenset({1, 'a'})])
-def test_is_list_like_strict_fails(ll):
+def test_is_ordered_list_like_fails(ll):
     # GH 23061
-    assert not inference.is_list_like(ll, strict=True)
+    assert not inference.is_ordered_list_like(ll)
 
 
 def test_is_array_like():