Last of the timezones funcs

pandas/_libs/tslib.pyx

@@ -105,7 +105,7 @@ from tslibs.timezones cimport (
  is_utc, is_tzlocal, is_fixed_offset,
  treat_tz_as_dateutil, treat_tz_as_pytz,
  get_timezone, get_utcoffset, maybe_get_tz,
- get_dst_info
+ get_dst_info, _infer_dst
  )
 
 
@@ -4003,48 +4003,7 @@ def tz_localize_to_utc(ndarray[int64_t] vals, object tz, object ambiguous=None,
  result_b[i] = v
 
  if infer_dst:
- dst_hours = np.empty(n, dtype=np.int64)
- dst_hours.fill(NPY_NAT)
-
- # Get the ambiguous hours (given the above, these are the hours
- # where result_a != result_b and neither of them are NAT)
- both_nat = np.logical_and(result_a != NPY_NAT, result_b != NPY_NAT)
- both_eq = result_a == result_b
- trans_idx = np.squeeze(np.nonzero(np.logical_and(both_nat, ~both_eq)))
- if trans_idx.size == 1:
- stamp = Timestamp(vals[trans_idx])
- raise pytz.AmbiguousTimeError(
- "Cannot infer dst time from %s as there "
- "are no repeated times" % stamp)
- # Split the array into contiguous chunks (where the difference between
- # indices is 1). These are effectively dst transitions in different
- # years which is useful for checking that there is not an ambiguous
- # transition in an individual year.
- if trans_idx.size > 0:
- one_diff = np.where(np.diff(trans_idx) != 1)[0] +1
- trans_grp = np.array_split(trans_idx, one_diff)
-
- # Iterate through each day, if there are no hours where the
- # delta is negative (indicates a repeat of hour) the switch
- # cannot be inferred
- for grp in trans_grp:
-
- delta = np.diff(result_a[grp])
- if grp.size == 1 or np.all(delta > 0):
- stamp = Timestamp(vals[grp[0]])
- raise pytz.AmbiguousTimeError(stamp)
-
- # Find the index for the switch and pull from a for dst and b
- # for standard
- switch_idx = (delta <= 0).nonzero()[0]
- if switch_idx.size > 1:
- raise pytz.AmbiguousTimeError(
- "There are %i dst switches when "
- "there should only be 1." % switch_idx.size)
- switch_idx = switch_idx[0] + 1 # Pull the only index and adjust
- a_idx = grp[:switch_idx]
- b_idx = grp[switch_idx:]
- dst_hours[grp] = np.hstack((result_a[a_idx], result_b[b_idx]))
+ dst_hours = _infer_dst(vals, result_a, result_b)
 
  for i in range(n):
  left = result_a[i]

pandas/_libs/tslibs/timezones.pxd

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 # cython: profile=False
 
-from numpy cimport ndarray
+from numpy cimport ndarray, int64_t
 
 cdef bint is_utc(object tz)
 cdef bint is_tzlocal(object tz)
@@ -16,3 +16,7 @@ cpdef get_utcoffset(tzinfo, obj)
 cdef bint is_fixed_offset(object tz)
 
 cdef object get_dst_info(object tz)
+
+cdef ndarray[int64_t] _infer_dst(ndarray[int64_t] vals,
+ ndarray[int64_t] result_a,
+ ndarray[int64_t] result_b)

pandas/_libs/tslibs/timezones.pyx

@@ -275,3 +275,84 @@ cdef object get_dst_info(object tz):
  dst_cache[cache_key] = (trans, deltas, typ)
 
  return dst_cache[cache_key]
+
+
+def _infer_tzinfo(start, end):
+ def _infer(a, b):
+ tz = a.tzinfo
+ if b and b.tzinfo:
+ if not (get_timezone(tz) == get_timezone(b.tzinfo)):
+ raise AssertionError('Inputs must both have the same timezone,'
+ ' {timezone1} != {timezone2}'
+ .format(timezone1=tz, timezone2=b.tzinfo))
+ return tz
+
+ tz = None
+ if start is not None:
+ tz = _infer(start, end)
+ elif end is not None:
+ tz = _infer(end, start)
+ return tz
+
+
+cdef ndarray[int64_t] _infer_dst(ndarray[int64_t] vals,
+ ndarray[int64_t] result_a,
+ ndarray[int64_t] result_b):
+ cdef:
+ Py_ssize_t n = len(vals)
+ ndarray[int64_t] dst_hours
+
+ dst_hours = np.empty(n, dtype=np.int64)
+ dst_hours.fill(NPY_NAT)
+
+ # Get the ambiguous hours (given the above, these are the hours
+ # where result_a != result_b and neither of them are NAT)
+ both_nat = np.logical_and(result_a != NPY_NAT, result_b != NPY_NAT)
+ both_eq = result_a == result_b
+ trans_idx = np.squeeze(np.nonzero(np.logical_and(both_nat, ~both_eq)))
+ if trans_idx.size == 1:
+ stamp = np.int64(vals[trans_idx]).astype('datetime64[ns]')
+ # Render `stamp` as e.g. '2017-08-30 07:59:23.123456'
+ # as opposed to str(stamp) which would
+ # be '2017-08-30T07:59:23.123456789'
+ stamp = str(stamp).replace('T', ' ')[:-3]
+ raise pytz.AmbiguousTimeError(
+ "Cannot infer dst time from %s as there "
+ "are no repeated times" % stamp)
+
+ # Split the array into contiguous chunks (where the difference between
+ # indices is 1). These are effectively dst transitions in different
+ # years which is useful for checking that there is not an ambiguous
+ # transition in an individual year.
+ if trans_idx.size > 0:
+ one_diff = np.where(np.diff(trans_idx) != 1)[0] +1
+ trans_grp = np.array_split(trans_idx, one_diff)
+
+ # Iterate through each day, if there are no hours where the
+ # delta is negative (indicates a repeat of hour) the switch
+ # cannot be inferred
+ for grp in trans_grp:
+
+ delta = np.diff(result_a[grp])
+ if grp.size == 1 or np.all(delta > 0):
+ stamp = np.int64(vals[grp[0]]).astype('datetime64[ns]')
+ # Render `stamp` as e.g. '2017-08-30 07:59:23.123456'
+ # as opposed to str(stamp) which would
+ # be '2017-08-30T07:59:23.123456789'
+ stamp = str(stamp).replace('T', ' ')[:-3]
+ raise pytz.AmbiguousTimeError(stamp)
+
+ # Find the index for the switch and pull from a for dst and b
+ # for standard
+ switch_idx = (delta <= 0).nonzero()[0]
+ if switch_idx.size > 1:
+ raise pytz.AmbiguousTimeError(
+ "There are %i dst switches when "
+ "there should only be 1." % switch_idx.size)
+
+ switch_idx = switch_idx[0] + 1 # Pull the only index and adjust
+ a_idx = grp[:switch_idx]
+ b_idx = grp[switch_idx:]
+ dst_hours[grp] = np.hstack((result_a[a_idx], result_b[b_idx]))
+
+ return dst_hours

pandas/core/tools/datetimes.py

@@ -4,7 +4,7 @@
 
 from pandas._libs import lib, tslib
 from pandas._libs.tslibs.strptime import array_strptime
-from pandas._libs.tslibs.timezones import get_timezone
+from pandas._libs.tslibs.timezones import get_timezone, _infer_tzinfo # noqa
 
 from pandas.core.dtypes.common import (
  _ensure_object,
@@ -42,22 +42,6 @@ def _lexer_split_from_str(dt_str):
  pass
 
 
-def _infer_tzinfo(start, end):
- def _infer(a, b):
- tz = a.tzinfo
- if b and b.tzinfo:
- if not (get_timezone(tz) == get_timezone(b.tzinfo)):
- raise AssertionError('Inputs must both have the same timezone,'
- ' {timezone1} != {timezone2}'
- .format(timezone1=tz, timezone2=b.tzinfo))
- return tz
-
- tz = None
- if start is not None:
- tz = _infer(start, end)
- elif end is not None:
- tz = _infer(end, start)
- return tz
 
 
 def _guess_datetime_format(dt_str, dayfirst=False,