Start porting offsets to cython

pandas/_libs/tslibs/offsets.pyx

@@ -0,0 +1,208 @@
+# -*- coding: utf-8 -*-
+# cython: profile=False
+
+cimport cython
+
+import time
+from cpython.datetime cimport time as dt_time
+
+import numpy as np
+cimport numpy as np
+np.import_array()
+
+
+from util cimport is_string_object
+
+
+from pandas._libs.tslib import pydt_to_i8, tz_convert_single
+
+# ---------------------------------------------------------------------
+# 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 = dict((v, k) for k, v in _int_to_month.items())
+
+
+class WeekDay(object):
+    MON = 0
+    TUE = 1
+    WED = 2
+    THU = 3
+    FRI = 4
+    SAT = 5
+    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',
+    'BM': 'M',
+    'BQS': 'Q',
+    'QS': 'Q',
+    'BQ': 'Q',
+    'BA': 'A',
+    'AS': 'A',
+    'BAS': 'A',
+    'MS': 'M',
+    'D': 'D',
+    'C': 'C',
+    'B': 'B',
+    'T': 'T',
+    'S': 'S',
+    'L': 'L',
+    'U': 'U',
+    'N': 'N',
+    'H': 'H',
+    'Q': 'Q',
+    'A': 'A',
+    'W': 'W',
+    'M': 'M',
+    'Y': 'A',
+    'BY': 'A',
+    'YS': 'A',
+    'BYS': 'A'}
+
+need_suffix = ['QS', 'BQ', 'BQS', 'YS', 'AS', 'BY', 'BA', 'BYS', 'BAS']
+
+
+for __prefix in need_suffix:
+    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:
+        _alias = '%s-%s' % (__prefix, _m)
+        _offset_to_period_map[_alias] = _alias
+
+_days = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']
+for _d in _days:
+    _offset_to_period_map['W-%s' % _d] = 'W-%s' % _d
+
+
+# ---------------------------------------------------------------------
+# Misc Helpers
+
+def as_datetime(obj):
+    f = getattr(obj, 'to_pydatetime', None)
+    if f is not None:
+        obj = f()
+    return obj
+
+
+def _is_normalized(dt):
+    if (dt.hour != 0 or dt.minute != 0 or dt.second != 0 or
+            dt.microsecond != 0 or getattr(dt, 'nanosecond', 0) != 0):
+        return False
+    return True
+
+
+# ---------------------------------------------------------------------
+# Business Helpers
+
+def _get_firstbday(wkday):
+    """
+    wkday is the result of monthrange(year, month)
+
+    If it's a saturday or sunday, increment first business day to reflect this
+    """
+    first = 1
+    if wkday == 5:  # on Saturday
+        first = 3
+    elif wkday == 6:  # on Sunday
+        first = 2
+    return first
+
+
+def _get_calendar(weekmask, holidays, calendar):
+    """Generate busdaycalendar"""
+    if isinstance(calendar, np.busdaycalendar):
+        if not holidays:
+            holidays = tuple(calendar.holidays)
+        elif not isinstance(holidays, tuple):
+            holidays = tuple(holidays)
+        else:
+            # trust that calendar.holidays and holidays are
+            # consistent
+            pass
+        return calendar, holidays
+
+    if holidays is None:
+        holidays = []
+    try:
+        holidays = holidays + calendar.holidays().tolist()
+    except AttributeError:
+        pass
+    holidays = [_to_dt64(dt, dtype='datetime64[D]') for dt in holidays]
+    holidays = tuple(sorted(holidays))
+
+    kwargs = {'weekmask': weekmask}
+    if holidays:
+        kwargs['holidays'] = holidays
+
+    busdaycalendar = np.busdaycalendar(**kwargs)
+    return busdaycalendar, holidays
+
+
+def _to_dt64(dt, dtype='datetime64'):
+    # Currently
+    # > np.datetime64(dt.datetime(2013,5,1),dtype='datetime64[D]')
+    # numpy.datetime64('2013-05-01T02:00:00.000000+0200')
+    # Thus astype is needed to cast datetime to datetime64[D]
+    if getattr(dt, 'tzinfo', None) is not None:
+        i8 = pydt_to_i8(dt)
+        dt = tz_convert_single(i8, 'UTC', dt.tzinfo)
+        dt = np.int64(dt).astype('datetime64[ns]')
+    else:
+        dt = np.datetime64(dt)
+    if dt.dtype.name != dtype:
+        dt = dt.astype(dtype)
+    return dt
+
+
+# ---------------------------------------------------------------------
+# Validation
+
+
+def _validate_business_time(t_input):
+    if is_string_object(t_input):
+        try:
+            t = time.strptime(t_input, '%H:%M')
+            return dt_time(hour=t.tm_hour, minute=t.tm_min)
+        except ValueError:
+            raise ValueError("time data must match '%H:%M' format")
+    elif isinstance(t_input, dt_time):
+        if t_input.second != 0 or t_input.microsecond != 0:
+            raise ValueError(
+                "time data must be specified only with hour and minute")
+        return t_input
+    else:
+        raise ValueError("time data must be string or datetime.time")
+
+# ---------------------------------------------------------------------
+# Mixins & Singletons
+
+
+class ApplyTypeError(TypeError):
+    # sentinel class for catching the apply error to return NotImplemented
+    pass
+
+
+# TODO: unused.  remove?
+class CacheableOffset(object):
+    _cacheable = True

pandas/tests/tseries/test_offsets.py

@@ -17,17 +17,18 @@
                                         get_offset, get_standard_freq)
 from pandas.core.indexes.datetimes import (
     _to_m8, DatetimeIndex, _daterange_cache)
+from pandas._libs.tseries offsets import WeekDay, CacheableOffset
 from pandas.tseries.offsets import (BDay, CDay, BQuarterEnd, BMonthEnd,
                                     BusinessHour, WeekOfMonth, CBMonthEnd,
-                                    CustomBusinessHour, WeekDay,
+                                    CustomBusinessHour,
                                     CBMonthBegin, BYearEnd, MonthEnd,
                                     MonthBegin, SemiMonthBegin, SemiMonthEnd,
                                     BYearBegin, QuarterBegin, BQuarterBegin,
                                     BMonthBegin, DateOffset, Week, YearBegin,
                                     YearEnd, Hour, Minute, Second, Day, Micro,
                                     QuarterEnd, BusinessMonthEnd, FY5253,
                                     Milli, Nano, Easter, FY5253Quarter,
-                                    LastWeekOfMonth, CacheableOffset)
+                                    LastWeekOfMonth)
 from pandas.core.tools.datetimes import (
     format, ole2datetime, parse_time_string,
     to_datetime, DateParseError)

pandas/tseries/frequencies.py

@@ -312,7 +312,7 @@ def _get_freq_str(base, mult=1):
 # ---------------------------------------------------------------------
 # Offset names ("time rules") and related functions
 
-
+from pandas._libs.tslibs.offsets import _offset_to_period_map
 from pandas.tseries.offsets import (Nano, Micro, Milli, Second,  # noqa
                                     Minute, Hour,
                                     Day, BDay, CDay, Week, MonthBegin,
@@ -328,51 +328,6 @@ def _get_freq_str(base, mult=1):
 #: cache of previously seen offsets
 _offset_map = {}
 
-_offset_to_period_map = {
-    'WEEKDAY': 'D',
-    'EOM': 'M',
-    'BM': 'M',
-    'BQS': 'Q',
-    'QS': 'Q',
-    'BQ': 'Q',
-    'BA': 'A',
-    'AS': 'A',
-    'BAS': 'A',
-    'MS': 'M',
-    'D': 'D',
-    'C': 'C',
-    'B': 'B',
-    'T': 'T',
-    'S': 'S',
-    'L': 'L',
-    'U': 'U',
-    'N': 'N',
-    'H': 'H',
-    'Q': 'Q',
-    'A': 'A',
-    'W': 'W',
-    'M': 'M',
-    'Y': 'A',
-    'BY': 'A',
-    'YS': 'A',
-    'BYS': 'A',
-}
-
-need_suffix = ['QS', 'BQ', 'BQS', 'YS', 'AS', 'BY', 'BA', 'BYS', 'BAS']
-for __prefix in need_suffix:
-    for _m in tslib._MONTHS:
-        _alias = '{prefix}-{month}'.format(prefix=__prefix, month=_m)
-        _offset_to_period_map[_alias] = _offset_to_period_map[__prefix]
-for __prefix in ['A', 'Q']:
-    for _m in tslib._MONTHS:
-        _alias = '{prefix}-{month}'.format(prefix=__prefix, month=_m)
-        _offset_to_period_map[_alias] = _alias
-
-_days = ['MON', 'TUE', 'WED', 'THU', 'FRI', 'SAT', 'SUN']
-for _d in _days:
-    _alias = 'W-{day}'.format(day=_d)
-    _offset_to_period_map[_alias] = _alias
-
 
 def get_period_alias(offset_str):
     """ alias to closest period strings BQ->Q etc"""