PERF: optimize NaT lookups in cython modules

pandas/_libs/tslib.pyx

@@ -40,8 +40,8 @@ from tslibs.conversion cimport (tz_convert_single, _TSObject,
                                 tz_convert_utc_to_tzlocal)
 
 # many modules still look for NaT and iNaT here despite them not being needed
-from tslibs.nattype import nat_strings, NaT, iNaT  # noqa:F821
-from tslibs.nattype cimport checknull_with_nat, NPY_NAT
+from tslibs.nattype import nat_strings, iNaT  # noqa:F821
+from tslibs.nattype cimport checknull_with_nat, NPY_NAT, c_NaT as NaT
 
 from tslibs.offsets cimport to_offset
 

pandas/_libs/tslibs/conversion.pyx

@@ -39,8 +39,8 @@ from timezones cimport (is_utc, is_tzlocal, is_fixed_offset,
 from timezones import UTC
 from parsing import parse_datetime_string
 
-from nattype import nat_strings, NaT
-from nattype cimport NPY_NAT, checknull_with_nat
+from nattype import nat_strings
+from nattype cimport NPY_NAT, checknull_with_nat, c_NaT as NaT
 
 # ----------------------------------------------------------------------
 # Constants

pandas/_libs/tslibs/nattype.pxd

@@ -1,9 +1,20 @@
 # -*- coding: utf-8 -*-
 
+from cpython.datetime cimport datetime
+
 from numpy cimport int64_t
 cdef int64_t NPY_NAT
 
 cdef bint _nat_scalar_rules[6]
 
+
+cdef class _NaT(datetime):
+    cdef readonly:
+        int64_t value
+        object freq
+
+cdef _NaT c_NaT
+
+
 cdef bint checknull_with_nat(object val)
 cdef bint is_null_datetimelike(object val)

pandas/_libs/tslibs/nattype.pyx

@@ -47,7 +47,7 @@ def _make_nan_func(func_name, doc):
 
 def _make_nat_func(func_name, doc):
     def f(*args, **kwargs):
-        return NaT
+        return c_NaT
     f.__name__ = func_name
     f.__doc__ = doc
     return f
@@ -67,10 +67,10 @@ def _make_error_func(func_name, cls):
 
 
 cdef _nat_divide_op(self, other):
-    if PyDelta_Check(other) or is_timedelta64_object(other) or other is NaT:
+    if PyDelta_Check(other) or is_timedelta64_object(other) or other is c_NaT:
         return np.nan
     if is_integer_object(other) or is_float_object(other):
-        return NaT
+        return c_NaT
     return NotImplemented
 
 
@@ -82,15 +82,15 @@ cdef _nat_rdivide_op(self, other):
 
 def __nat_unpickle(*args):
     # return constant defined in the module
-    return NaT
+    return c_NaT
 
 # ----------------------------------------------------------------------
 
 
 cdef class _NaT(datetime):
-    cdef readonly:
-        int64_t value
-        object freq
+    # cdef readonly:
+    #    int64_t value
+    #    object freq
 
     def __hash__(_NaT self):
         # py3k needs this defined here
@@ -116,18 +116,18 @@ cdef class _NaT(datetime):
 
     def __add__(self, other):
         if PyDateTime_Check(other):
-            return NaT
+            return c_NaT
 
         elif hasattr(other, 'delta'):
             # Timedelta, offsets.Tick, offsets.Week
-            return NaT
+            return c_NaT
         elif getattr(other, '_typ', None) in ['dateoffset', 'series',
                                               'period', 'datetimeindex',
                                               'timedeltaindex']:
             # Duplicate logic in _Timestamp.__add__ to avoid needing
             # to subclass; allows us to @final(_Timestamp.__add__)
             return NotImplemented
-        return NaT
+        return c_NaT
 
     def __sub__(self, other):
         # Duplicate some logic from _Timestamp.__sub__ to avoid needing
@@ -184,19 +184,6 @@ cdef class _NaT(datetime):
         """ Returns a numpy.datetime64 object with 'ns' precision """
         return np.datetime64('NaT', 'ns')
 
-
-class NaTType(_NaT):
-    """(N)ot-(A)-(T)ime, the time equivalent of NaN"""
-
-    def __new__(cls):
-        cdef _NaT base
-
-        base = _NaT.__new__(cls, 1, 1, 1)
-        base.value = NPY_NAT
-        base.freq = None
-
-        return base
-
     def __repr__(self):
         return 'NaT'
 
@@ -216,20 +203,11 @@ class NaTType(_NaT):
     def __long__(self):
         return NPY_NAT
 
-    def __reduce_ex__(self, protocol):
-        # python 3.6 compat
-        # http://bugs.python.org/issue28730
-        # now __reduce_ex__ is defined and higher priority than __reduce__
-        return self.__reduce__()
-
-    def __reduce__(self):
-        return (__nat_unpickle, (None, ))
-
     def total_seconds(self):
         """
         Total duration of timedelta in seconds (to ns precision)
         """
-        # GH 10939
+        # GH#10939
         return np.nan
 
     @property
@@ -260,6 +238,28 @@ class NaTType(_NaT):
     def is_year_end(self):
         return False
 
+
+class NaTType(_NaT):
+    """(N)ot-(A)-(T)ime, the time equivalent of NaN"""
+
+    def __new__(cls):
+        cdef _NaT base
+
+        base = _NaT.__new__(cls, 1, 1, 1)
+        base.value = NPY_NAT
+        base.freq = None
+
+        return base
+
+    def __reduce_ex__(self, protocol):
+        # python 3.6 compat
+        # http://bugs.python.org/issue28730
+        # now __reduce_ex__ is defined and higher priority than __reduce__
+        return self.__reduce__()
+
+    def __reduce__(self):
+        return (__nat_unpickle, (None, ))
+
     def __rdiv__(self, other):
         return _nat_rdivide_op(self, other)
 
@@ -271,7 +271,7 @@ class NaTType(_NaT):
 
     def __rmul__(self, other):
         if is_integer_object(other) or is_float_object(other):
-            return NaT
+            return c_NaT
         return NotImplemented
 
     # ----------------------------------------------------------------------
@@ -659,14 +659,15 @@ class NaTType(_NaT):
         """)
 
 
-NaT = NaTType()
+c_NaT = NaTType()  # C-visible
+NaT = c_NaT        # Python-visible
 
 
 # ----------------------------------------------------------------------
 
 cdef inline bint checknull_with_nat(object val):
     """ utility to check if a value is a nat or not """
-    return val is None or util.is_nan(val) or val is NaT
+    return val is None or util.is_nan(val) or val is c_NaT
 
 
 cdef inline bint is_null_datetimelike(object val):
@@ -683,7 +684,7 @@ cdef inline bint is_null_datetimelike(object val):
     """
     if val is None or util.is_nan(val):
         return True
-    elif val is NaT:
+    elif val is c_NaT:
         return True
     elif util.is_timedelta64_object(val):
         return val.view('int64') == NPY_NAT

pandas/_libs/tslibs/period.pyx

@@ -46,8 +46,9 @@ from frequencies cimport (get_freq_code, get_base_alias,
                           get_rule_month)
 from parsing import parse_time_string
 from resolution import Resolution
-from nattype import nat_strings, NaT
-from nattype cimport _nat_scalar_rules, NPY_NAT, is_null_datetimelike
+from nattype import nat_strings
+from nattype cimport (
+    _nat_scalar_rules, NPY_NAT, is_null_datetimelike, c_NaT as NaT)
 from offsets cimport to_offset
 from offsets import _Tick
 

pandas/_libs/tslibs/timedeltas.pyx

@@ -33,8 +33,8 @@ from ccalendar import DAY_SECONDS
 from np_datetime cimport (cmp_scalar, reverse_ops, td64_to_tdstruct,
                           pandas_timedeltastruct)
 
-from nattype import nat_strings, NaT
-from nattype cimport checknull_with_nat, NPY_NAT
+from nattype import nat_strings
+from nattype cimport checknull_with_nat, NPY_NAT, c_NaT as NaT
 from offsets cimport to_offset
 
 # ----------------------------------------------------------------------

pandas/_libs/tslibs/timestamps.pyx

@@ -26,8 +26,7 @@ from conversion import tz_localize_to_utc, normalize_i8_timestamps
 from conversion cimport (tz_convert_single, _TSObject,
                          convert_to_tsobject, convert_datetime_to_tsobject)
 from fields import get_start_end_field, get_date_name_field
-from nattype import NaT
-from nattype cimport NPY_NAT
+from nattype cimport NPY_NAT, c_NaT as NaT
 from np_datetime import OutOfBoundsDatetime
 from np_datetime cimport (reverse_ops, cmp_scalar, check_dts_bounds,
                           npy_datetimestruct, dt64_to_dtstruct)

pandas/_libs/tslibs/timezones.pyx

@@ -2,6 +2,8 @@
 
 from cython import Py_ssize_t
 
+from cpython.datetime cimport tzinfo
+
 # dateutil compat
 from dateutil.tz import (
     tzutc as _dateutil_tzutc,

pandas/core/arrays/datetimes.py

@@ -6,10 +6,9 @@
 from pytz import utc
 
 from pandas._libs import lib, tslib
-from pandas._libs.tslib import NaT, Timestamp, iNaT
 from pandas._libs.tslibs import (
-    ccalendar, conversion, fields, normalize_date, resolution as libresolution,
-    timezones)
+    NaT, Timestamp, ccalendar, conversion, fields, iNaT, normalize_date,
+    resolution as libresolution, timezones)
 import pandas.compat as compat
 from pandas.errors import PerformanceWarning
 from pandas.util._decorators import Appender, cache_readonly

pandas/core/arrays/period.py

@@ -4,8 +4,7 @@
 
 import numpy as np
 
-from pandas._libs.tslib import NaT, iNaT
-from pandas._libs.tslibs import period as libperiod
+from pandas._libs.tslibs import NaT, iNaT, period as libperiod
 from pandas._libs.tslibs.fields import isleapyear_arr
 from pandas._libs.tslibs.period import (
     DIFFERENT_FREQ_INDEX, IncompatibleFrequency, Period, get_period_field_arr,

pandas/tests/scalar/test_nat.py

@@ -4,7 +4,7 @@
 import pytest
 import pytz
 
-from pandas._libs.tslib import iNaT
+from pandas._libs.tslibs import iNaT
 
 from pandas import (
     DatetimeIndex, Index, NaT, Period, Series, Timedelta, TimedeltaIndex,

pandas/tests/scalar/timedelta/test_timedelta.py

@@ -4,7 +4,7 @@
 import numpy as np
 import pytest
 
-from pandas._libs.tslib import NaT, iNaT
+from pandas._libs.tslibs import NaT, iNaT
 import pandas.compat as compat
 
 import pandas as pd

pandas/tests/tseries/offsets/test_offsets.py

@@ -5,13 +5,11 @@
 import pytest
 import pytz
 
-import pandas._libs.tslib as tslib
-from pandas._libs.tslib import NaT, Timestamp
-from pandas._libs.tslibs import conversion, timezones
+from pandas._libs.tslibs import (
+    NaT, OutOfBoundsDatetime, Timedelta, Timestamp, conversion, timezones)
 from pandas._libs.tslibs.frequencies import (
     INVALID_FREQ_ERR_MSG, get_freq_code, get_freq_str)
 import pandas._libs.tslibs.offsets as liboffsets
-from pandas._libs.tslibs.timedeltas import Timedelta
 import pandas.compat as compat
 from pandas.compat import range
 from pandas.compat.numpy import np_datetime64_compat
@@ -124,7 +122,7 @@ def test_apply_out_of_range(self, tz_naive_fixture):
             assert isinstance(result, datetime)
             assert t.tzinfo == result.tzinfo
 
-        except tslib.OutOfBoundsDatetime:
+        except OutOfBoundsDatetime:
             raise
         except (ValueError, KeyError):
             # we are creating an invalid offset