centralize and de-privatize month/day name constants

pandas/_libs/tslibs/ccalendar.pyx

@@ -33,6 +33,17 @@ cdef int32_t* _month_offset = [
     0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334, 365,
     0, 31, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335, 366]
 
+# Canonical location for other modules to find name constants
+MONTHS = ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',
+          'AUG', 'SEP', 'OCT', 'NOV', 'DEC']
+MONTH_NUMBERS = {name: num for num, name in enumerate(MONTHS)}
+MONTH_ALIASES = {(num + 1): name for num, name in enumerate(MONTHS)}
+MONTH_TO_CAL_NUM = {name: num + 1 for num, name in enumerate(MONTHS)}
+
+DAYS = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']
+int_to_weekday = {num: name for num, name in enumerate(DAYS)}
+weekday_to_int = {int_to_weekday[key]: key for key in int_to_weekday}
+
 # ----------------------------------------------------------------------
 
 

pandas/_libs/tslibs/fields.pyx

@@ -139,8 +139,8 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
         int mo_off, dom, doy, dow, ldom
 
     _month_offset = np.array(
-        [[ 0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334, 365 ],
-         [ 0, 31, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335, 366 ]],
+        [[0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334, 365],
+         [0, 31, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335, 366]],
         dtype=np.int32)
 
     count = len(dtindex)
@@ -380,8 +380,8 @@ def get_date_field(ndarray[int64_t] dtindex, object field):
         int mo_off, doy, dow
 
     _month_offset = np.array(
-        [[ 0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334, 365 ],
-         [ 0, 31, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335, 366 ]],
+        [[0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334, 365],
+         [0, 31, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335, 366]],
         dtype=np.int32 )
 
     count = len(dtindex)

pandas/_libs/tslibs/offsets.pyx

@@ -17,6 +17,7 @@ np.import_array()
 
 from util cimport is_string_object, is_integer_object
 
+from ccalendar import MONTHS, DAYS
 from conversion cimport tz_convert_single, pydt_to_i8
 from frequencies cimport get_freq_code
 from nattype cimport NPY_NAT
@@ -27,14 +28,9 @@ from np_datetime cimport (pandas_datetimestruct,
 # ---------------------------------------------------------------------
 # Constants
 
-# Duplicated in tslib
-_MONTHS = ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',
-           'AUG', 'SEP', 'OCT', 'NOV', 'DEC']
-_int_to_month = {(k + 1): v for k, v in enumerate(_MONTHS)}
-_month_to_int = {v: k for k, v in _int_to_month.items()}
-
 
 class WeekDay(object):
+    # TODO: Remove: This is not used outside of tests
     MON = 0
     TUE = 1
     WED = 2
@@ -44,18 +40,6 @@ class WeekDay(object):
     SUN = 6
 
 
-_int_to_weekday = {
-    WeekDay.MON: 'MON',
-    WeekDay.TUE: 'TUE',
-    WeekDay.WED: 'WED',
-    WeekDay.THU: 'THU',
-    WeekDay.FRI: 'FRI',
-    WeekDay.SAT: 'SAT',
-    WeekDay.SUN: 'SUN'}
-
-_weekday_to_int = {_int_to_weekday[key]: key for key in _int_to_weekday}
-
-
 _offset_to_period_map = {
     'WEEKDAY': 'D',
     'EOM': 'M',
@@ -88,17 +72,16 @@ _offset_to_period_map = {
 need_suffix = ['QS', 'BQ', 'BQS', 'YS', 'AS', 'BY', 'BA', 'BYS', 'BAS']
 
 for __prefix in need_suffix:
-    for _m in _MONTHS:
+    for _m in MONTHS:
         key = '%s-%s' % (__prefix, _m)
         _offset_to_period_map[key] = _offset_to_period_map[__prefix]
 
 for __prefix in ['A', 'Q']:
-    for _m in _MONTHS:
+    for _m in MONTHS:
         _alias = '%s-%s' % (__prefix, _m)
         _offset_to_period_map[_alias] = _alias
 
-_days = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']
-for _d in _days:
+for _d in DAYS:
     _offset_to_period_map['W-%s' % _d] = 'W-%s' % _d
 
 

pandas/_libs/tslibs/parsing.pyx

@@ -41,6 +41,9 @@ from dateutil.relativedelta import relativedelta
 from dateutil.parser import DEFAULTPARSER
 from dateutil.parser import parse as du_parse
 
+from ccalendar import MONTH_NUMBERS
+from nattype import nat_strings
+
 # ----------------------------------------------------------------------
 # Constants
 
@@ -49,14 +52,8 @@ class DateParseError(ValueError):
     pass
 
 
-_nat_strings = set(['NaT', 'nat', 'NAT', 'nan', 'NaN', 'NAN'])
-
 _DEFAULT_DATETIME = datetime(1, 1, 1).replace(hour=0, minute=0,
                                               second=0, microsecond=0)
-_MONTHS = ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',
-           'AUG', 'SEP', 'OCT', 'NOV', 'DEC']
-_MONTH_NUMBERS = {k: i for i, k in enumerate(_MONTHS)}
-_MONTH_ALIASES = {(k + 1): v for k, v in enumerate(_MONTHS)}
 
 cdef object _TIMEPAT = re.compile(r'^([01]?[0-9]|2[0-3]):([0-5][0-9])')
 
@@ -213,7 +210,7 @@ cdef inline object _parse_dateabbr_string(object date_string, object default,
     # len(date_string) == 0
     # should be NaT???
 
-    if date_string in _nat_strings:
+    if date_string in nat_strings:
         return NAT_SENTINEL, NAT_SENTINEL, ''
 
     date_string = date_string.upper()
@@ -267,7 +264,7 @@ cdef inline object _parse_dateabbr_string(object date_string, object default,
             if freq is not None:
                 # hack attack, #1228
                 try:
-                    mnum = _MONTH_NUMBERS[_get_rule_month(freq)] + 1
+                    mnum = MONTH_NUMBERS[_get_rule_month(freq)] + 1
                 except (KeyError, ValueError):
                     msg = ('Unable to retrieve month information from given '
                            'freq: {0}').format(freq)

pandas/_libs/tslibs/period.pyx

@@ -32,8 +32,9 @@ from timestamps import Timestamp
 from timezones cimport is_utc, is_tzlocal, get_utcoffset, get_dst_info
 from timedeltas cimport delta_to_nanoseconds
 
+from ccalendar import MONTH_NUMBERS
 from parsing import (parse_time_string, NAT_SENTINEL,
-                     _get_rule_month, _MONTH_NUMBERS)
+                     _get_rule_month)
 from frequencies cimport get_freq_code
 from resolution import resolution, Resolution
 from nattype import nat_strings, NaT, iNaT
@@ -1148,7 +1149,7 @@ def _quarter_to_myear(year, quarter, freq):
         if quarter <= 0 or quarter > 4:
             raise ValueError('Quarter must be 1 <= q <= 4')
 
-        mnum = _MONTH_NUMBERS[_get_rule_month(freq)] + 1
+        mnum = MONTH_NUMBERS[_get_rule_month(freq)] + 1
         month = (mnum + (quarter - 1) * 3) % 12 + 1
         if month > mnum:
             year -= 1

pandas/_libs/tslibs/resolution.pyx

@@ -17,13 +17,13 @@ from pandas._libs.khash cimport (khiter_t,
 
 from cpython.datetime cimport datetime
 
-from np_datetime cimport (pandas_datetimestruct,
-                          dtstruct_to_dt64, dt64_to_dtstruct)
+from np_datetime cimport pandas_datetimestruct, dt64_to_dtstruct
 from frequencies cimport get_freq_code
 from timezones cimport (is_utc, is_tzlocal,
                         maybe_get_tz, get_dst_info, get_utcoffset)
 from fields import build_field_sarray
 from conversion import tz_convert
+from ccalendar import DAYS, MONTH_ALIASES, int_to_weekday
 
 from pandas._libs.properties import cache_readonly
 from pandas._libs.tslib import Timestamp
@@ -50,13 +50,6 @@ _ONE_MINUTE = 60 * _ONE_SECOND
 _ONE_HOUR = 60 * _ONE_MINUTE
 _ONE_DAY = 24 * _ONE_HOUR
 
-DAYS = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']
-_weekday_rule_aliases = {k: v for k, v in enumerate(DAYS)}
-
-_MONTHS = ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',
-           'AUG', 'SEP', 'OCT', 'NOV', 'DEC']
-_MONTH_ALIASES = {(k + 1): v for k, v in enumerate(_MONTHS)}
-
 # ----------------------------------------------------------------------
 
 cpdef resolution(ndarray[int64_t] stamps, tz=None):
@@ -354,7 +347,7 @@ class Resolution(object):
 # Frequency Inference
 
 
-# TODO: this is non performiant logic here (and duplicative) and this
+# TODO: this is non performant logic here (and duplicative) and this
 # simply should call unique_1d directly
 # plus no reason to depend on khash directly
 cdef unique_deltas(ndarray[int64_t] arr):
@@ -537,15 +530,15 @@ class _FrequencyInferer(object):
         annual_rule = self._get_annual_rule()
         if annual_rule:
             nyears = self.ydiffs[0]
-            month = _MONTH_ALIASES[self.rep_stamp.month]
+            month = MONTH_ALIASES[self.rep_stamp.month]
             alias = '{prefix}-{month}'.format(prefix=annual_rule, month=month)
             return _maybe_add_count(alias, nyears)
 
         quarterly_rule = self._get_quarterly_rule()
         if quarterly_rule:
             nquarters = self.mdiffs[0] / 3
             mod_dict = {0: 12, 2: 11, 1: 10}
-            month = _MONTH_ALIASES[mod_dict[self.rep_stamp.month % 3]]
+            month = MONTH_ALIASES[mod_dict[self.rep_stamp.month % 3]]
             alias = '{prefix}-{month}'.format(prefix=quarterly_rule,
                                               month=month)
             return _maybe_add_count(alias, nquarters)
@@ -558,7 +551,7 @@ class _FrequencyInferer(object):
             days = self.deltas[0] / _ONE_DAY
             if days % 7 == 0:
                 # Weekly
-                day = _weekday_rule_aliases[self.rep_stamp.weekday()]
+                day = int_to_weekday[self.rep_stamp.weekday()]
                 return _maybe_add_count('W-{day}'.format(day=day), days / 7)
             else:
                 return _maybe_add_count('D', days)
@@ -630,7 +623,7 @@ class _FrequencyInferer(object):
 
         # get which week
         week = week_of_months[0] + 1
-        wd = _weekday_rule_aliases[weekdays[0]]
+        wd = int_to_weekday[weekdays[0]]
 
         return 'WOM-{week}{weekday}'.format(week=week, weekday=wd)
 
@@ -642,7 +635,7 @@ class _TimedeltaFrequencyInferer(_FrequencyInferer):
             days = self.deltas[0] / _ONE_DAY
             if days % 7 == 0:
                 # Weekly
-                wd = _weekday_rule_aliases[self.rep_stamp.weekday()]
+                wd = int_to_weekday[self.rep_stamp.weekday()]
                 alias = 'W-{weekday}'.format(weekday=wd)
                 return _maybe_add_count(alias, days / 7)
             else:

pandas/tests/indexes/period/test_tools.py

@@ -6,7 +6,8 @@
 import pandas.core.indexes.period as period
 from pandas.compat import lrange
 from pandas.tseries.frequencies import get_freq
-from pandas._libs.tslibs.resolution import _MONTHS as MONTHS
+
+from pandas._libs.tslibs.ccalendar import MONTHS
 from pandas._libs.tslibs.period import period_ordinal, period_asfreq
 from pandas import (PeriodIndex, Period, DatetimeIndex, Timestamp, Series,
                     date_range, to_datetime, period_range)

pandas/tests/scalar/test_period.py

@@ -12,9 +12,9 @@
 
 from pandas._libs import tslib
 from pandas._libs.tslibs import period as libperiod
+from pandas._libs.tslibs.ccalendar import DAYS, MONTHS
 from pandas._libs.tslibs.parsing import DateParseError
 from pandas import Period, Timestamp, offsets
-from pandas._libs.tslibs.resolution import DAYS, _MONTHS as MONTHS
 
 
 class TestPeriodProperties(object):

pandas/tests/test_resample.py

@@ -22,7 +22,7 @@
 from pandas.core.base import SpecificationError, AbstractMethodError
 from pandas.errors import UnsupportedFunctionCall
 from pandas.core.groupby import DataError
-from pandas._libs.tslibs.resolution import DAYS, _MONTHS as MONTHS
+
 from pandas.tseries.frequencies import to_offset
 from pandas.core.indexes.datetimes import date_range
 from pandas.tseries.offsets import Minute, BDay
@@ -33,6 +33,7 @@
 from pandas.util.testing import (assert_series_equal, assert_almost_equal,
                                  assert_frame_equal, assert_index_equal)
 from pandas._libs.tslibs.period import IncompatibleFrequency
+from pandas._libs.tslibs.ccalendar import DAYS, MONTHS
 
 bday = BDay()
 

pandas/tseries/frequencies.py

@@ -25,7 +25,8 @@
 from pandas._libs.tslibs.resolution import (Resolution,
                                             _FrequencyInferer,
                                             _TimedeltaFrequencyInferer)
-from pandas._libs.tslibs.parsing import _get_rule_month, _MONTH_NUMBERS
+from pandas._libs.tslibs.parsing import _get_rule_month
+from pandas._libs.tslibs.ccalendar import MONTH_NUMBERS
 
 from pytz import AmbiguousTimeError
 
@@ -496,8 +497,8 @@ def _is_annual(rule):
 
 
 def _quarter_months_conform(source, target):
-    snum = _MONTH_NUMBERS[source]
-    tnum = _MONTH_NUMBERS[target]
+    snum = MONTH_NUMBERS[source]
+    tnum = MONTH_NUMBERS[target]
     return snum % 3 == tnum % 3