De-privatize timezone funcs (pandas-dev#17502)

Author: jbrockmendel

pandas/_libs/index.pyx

@@ -17,7 +17,7 @@ cimport tslib
 
 from hashtable cimport HashTable
 
-from tslibs.timezones cimport _is_utc
+from tslibs.timezones cimport is_utc, get_utcoffset
 from pandas._libs import tslib, algos, hashtable as _hash
 from pandas._libs.tslib import Timestamp, Timedelta
 from datetime import datetime, timedelta
@@ -551,8 +551,8 @@ cdef inline _to_i8(object val):
  tzinfo = getattr(val, 'tzinfo', None)
  # Save the original date value so we can get the utcoffset from it.
  ival = _pydatetime_to_dts(val, &dts)
- if tzinfo is not None and not _is_utc(tzinfo):
- offset = tslib._get_utcoffset(tzinfo, val)
+ if tzinfo is not None and not is_utc(tzinfo):
+ offset = get_utcoffset(tzinfo, val)
  ival -= tslib._delta_to_nanoseconds(offset)
  return ival
  return val

pandas/_libs/period.pyx

@@ -34,7 +34,7 @@ from lib cimport is_null_datetimelike, is_period
 from pandas._libs import tslib, lib
 from pandas._libs.tslib import (Timedelta, Timestamp, iNaT,
  NaT)
-from tslibs.timezones cimport _is_utc, _is_tzlocal, _get_utcoffset
+from tslibs.timezones cimport is_utc, is_tzlocal, get_utcoffset
 from tslib cimport (
  maybe_get_tz,
  _get_dst_info,
@@ -533,23 +533,23 @@ cdef _reso_local(ndarray[int64_t] stamps, object tz):
  ndarray[int64_t] trans, deltas, pos
  pandas_datetimestruct dts
 
- if _is_utc(tz):
+ if is_utc(tz):
  for i in range(n):
  if stamps[i] == NPY_NAT:
  continue
  pandas_datetime_to_datetimestruct(stamps[i], PANDAS_FR_ns, &dts)
  curr_reso = _reso_stamp(&dts)
  if curr_reso < reso:
  reso = curr_reso
- elif _is_tzlocal(tz):
+ elif is_tzlocal(tz):
  for i in range(n):
  if stamps[i] == NPY_NAT:
  continue
  pandas_datetime_to_datetimestruct(stamps[i], PANDAS_FR_ns,
  &dts)
  dt = datetime(dts.year, dts.month, dts.day, dts.hour,
  dts.min, dts.sec, dts.us, tz)
- delta = int(_get_utcoffset(tz, dt).total_seconds()) * 1000000000
+ delta = int(get_utcoffset(tz, dt).total_seconds()) * 1000000000
  pandas_datetime_to_datetimestruct(stamps[i] + delta,
  PANDAS_FR_ns, &dts)
  curr_reso = _reso_stamp(&dts)
@@ -597,7 +597,7 @@ cdef ndarray[int64_t] localize_dt64arr_to_period(ndarray[int64_t] stamps,
  ndarray[int64_t] trans, deltas, pos
  pandas_datetimestruct dts
 
- if _is_utc(tz):
+ if is_utc(tz):
  for i in range(n):
  if stamps[i] == NPY_NAT:
  result[i] = NPY_NAT
@@ -607,7 +607,7 @@ cdef ndarray[int64_t] localize_dt64arr_to_period(ndarray[int64_t] stamps,
  dts.hour, dts.min, dts.sec,
  dts.us, dts.ps, freq)
 
- elif _is_tzlocal(tz):
+ elif is_tzlocal(tz):
  for i in range(n):
  if stamps[i] == NPY_NAT:
  result[i] = NPY_NAT
@@ -616,7 +616,7 @@ cdef ndarray[int64_t] localize_dt64arr_to_period(ndarray[int64_t] stamps,
  &dts)
  dt = datetime(dts.year, dts.month, dts.day, dts.hour,
  dts.min, dts.sec, dts.us, tz)
- delta = int(_get_utcoffset(tz, dt).total_seconds()) * 1000000000
+ delta = int(get_utcoffset(tz, dt).total_seconds()) * 1000000000
  pandas_datetime_to_datetimestruct(stamps[i] + delta,
  PANDAS_FR_ns, &dts)
  result[i] = get_period_ordinal(dts.year, dts.month, dts.day,

pandas/_libs/src/inference.pyx

@@ -3,7 +3,7 @@ from decimal import Decimal
 cimport util
 cimport cython
 from tslib import NaT
-from tslibs.timezones cimport _get_zone
+from tslibs.timezones cimport get_timezone
 from datetime import datetime, timedelta
 iNaT = util.get_nat()
 
@@ -901,13 +901,13 @@ cpdef bint is_datetime_with_singletz_array(ndarray[object] values):
  for i in range(n):
  base_val = values[i]
  if base_val is not NaT:
- base_tz = _get_zone(getattr(base_val, 'tzinfo', None))
+ base_tz = get_timezone(getattr(base_val, 'tzinfo', None))
 
  for j in range(i, n):
  val = values[j]
  if val is not NaT:
  tz = getattr(val, 'tzinfo', None)
- if base_tz != tz and base_tz != _get_zone(tz):
+ if base_tz != tz and base_tz != get_timezone(tz):
  return False
  break