PERF: Faster Series.__getattribute__

doc/source/whatsnew/v0.23.0.txt

@@ -958,6 +958,7 @@ Performance Improvements
 - Improved performance of :func:`pandas.core.groupby.GroupBy.any` and :func:`pandas.core.groupby.GroupBy.all` (:issue:`15435`)
 - Improved performance of :func:`pandas.core.groupby.GroupBy.pct_change` (:issue:`19165`)
 - Improved performance of :func:`Series.isin` in the case of categorical dtypes (:issue:`20003`)
+- Improved performance of ``Series.__getattribute__`` when the Series has certain index types. This manifiested in slow printing of large Series with a ``DatetimeIndex`` (:issue:`19764`)
 - Fixed a performance regression for :func:`GroupBy.nth` and :func:`GroupBy.last` with some object columns (:issue:`19283`)
 
 .. _whatsnew_0230.docs:

pandas/core/generic.py

@@ -4375,7 +4375,7 @@ def __getattr__(self, name):
                 name in self._accessors):
             return object.__getattribute__(self, name)
         else:
-            if name in self._info_axis:
+            if self._info_axis._is_dotable and name in self._info_axis:
                 return self[name]
             return object.__getattribute__(self, name)
 

pandas/core/indexes/base.py

@@ -244,6 +244,12 @@ class Index(IndexOpsMixin, PandasObject):
     _engine_type = libindex.ObjectEngine
 
     _accessors = set(['str'])
+    # Whether items can be selected from NDFrame.<item>
+    # Some indexes (DatetimeIndex, Int64Index) cannot contain
+    # valid Python identifiers. Setting _is_dotable = False is an
+    # optimization.
+    # https://github.com/pandas-dev/pandas/issues/19764
+    _is_dotable = True
 
     str = CachedAccessor("str", StringMethods)
 

pandas/core/indexes/interval.py

@@ -207,6 +207,7 @@ class IntervalIndex(IntervalMixin, Index):
     _typ = 'intervalindex'
     _comparables = ['name']
     _attributes = ['name', 'closed']
+    _is_dotable = False  # can't contain Python identifiers
 
     # we would like our indexing holder to defer to us
     _defer_to_indexing = True

pandas/core/indexes/numeric.py

@@ -31,6 +31,7 @@ class NumericIndex(Index):
 
     """
     _is_numeric_dtype = True
+    _is_dotable = False  # Can't contain Python identifiers
 
     def __new__(cls, data=None, dtype=None, copy=False, name=None,
                 fastpath=False):

pandas/core/indexes/period.py

@@ -204,6 +204,7 @@ class PeriodIndex(DatelikeOps, DatetimeIndexOpsMixin, Int64Index):
     """
     _typ = 'periodindex'
     _attributes = ['name', 'freq']
+    _is_dotable = False  # Can't contain Python identifiers
 
     # define my properties & methods for delegation
     _other_ops = []

pandas/tests/indexes/datetimelike.py

@@ -8,6 +8,10 @@
 
 class DatetimeLike(Base):
 
+    def test_is_dotable(self):
+        idx = self.create_index()
+        assert idx._is_dotable is False
+
     def test_shift_identity(self):
 
         idx = self.create_index()

pandas/tests/indexes/test_base.py

@@ -66,6 +66,10 @@ def generate_index_types(self, skip_index_keys=[]):
             if key not in skip_index_keys:
                 yield key, idx
 
+    def test_is_dotable(self):
+        idx = self.create_index()
+        assert idx._is_dotable is True
+
     def test_new_axis(self):
         new_index = self.dateIndex[None, :]
         assert new_index.ndim == 2

pandas/tests/indexes/test_category.py

@@ -33,6 +33,10 @@ def create_index(self, categories=None, ordered=False):
         return CategoricalIndex(
             list('aabbca'), categories=categories, ordered=ordered)
 
+    def test_is_dotable(self):
+        ci = self.create_index(categories=list('abcd'))
+        assert ci._is_dotable is True
+
     def test_construction(self):
 
         ci = self.create_index(categories=list('abcd'))

pandas/tests/indexes/test_multi.py

@@ -48,6 +48,10 @@ def setup_method(self, method):
     def create_index(self):
         return self.index
 
+    def test_is_dotable(self):
+        idx = self.create_index()
+        assert idx._is_dotable is True
+
     def test_boolean_context_compat2(self):
 
         # boolean context compat

pandas/tests/indexes/test_numeric.py

@@ -64,6 +64,10 @@ def test_index_rdiv_timedelta(self, scalar_td, index):
 
 class Numeric(Base):
 
+    def test_is_dotable(self):
+        idx = self.create_index()
+        assert idx._is_dotable is False
+
     def test_numeric_compat(self):
         pass  # override Base method
 

pandas/tests/indexes/test_range.py

@@ -44,6 +44,10 @@ def check_binop(self, ops, scalars, idxs):
                     expected = op(Int64Index(idx), scalar)
                     tm.assert_index_equal(result, expected)
 
+    def test_is_dotable(self):
+        idx = self.create_index()
+        assert idx._is_dotable is False
+
     def test_binops(self):
         ops = [operator.add, operator.sub, operator.mul, operator.floordiv,
                operator.truediv]