BUG: pd.to_datetime() throws if caching is on with Null-like arguments (pandas-dev#26078)

Author: anmyachev

pandas/core/tools/datetimes.py

@@ -52,9 +52,10 @@ def _maybe_cache(arg, format, cache, convert_listlike):
     if cache:
         # Perform a quicker unique check
         from pandas import Index
-        if not Index(arg).is_unique:
-            unique_dates = algorithms.unique(arg)
-            cache_dates = convert_listlike(unique_dates, True, format)
+        unique_dates = Index(arg).unique()
+        if len(unique_dates) < len(arg):
+            cache_dates = convert_listlike(unique_dates.to_numpy(),
+                                           True, format)
             cache_array = Series(cache_dates, index=unique_dates)
     return cache_array
 

pandas/tests/indexes/datetimes/test_tools.py

@@ -1519,6 +1519,15 @@ def test_parsers(self, date_str, expected, cache):
                                  yearfirst=yearfirst)
             assert result7 == expected
 
+    @pytest.mark.parametrize('cache', [True, False])
+    def test_na_values_with_cache(self, cache, unique_nulls_fixture,
+                                  unique_nulls_fixture2):
+        # GH22305
+        expected = Index([NaT, NaT], dtype='datetime64[ns]')
+        result = to_datetime([unique_nulls_fixture, unique_nulls_fixture2],
+                             cache=cache)
+        tm.assert_index_equal(result, expected)
+
     def test_parsers_nat(self):
         # Test that each of several string-accepting methods return pd.NaT
         result1, _, _ = parsing.parse_time_string('NaT')