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Move NaT to self-contained module #18014

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Merged
merged 14 commits into from
Nov 1, 2017
Merged

Move NaT to self-contained module #18014

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3926da5
move NaT to self-contained module
jbrockmendel Oct 28, 2017
c232845
de-privatize _nat_strings, copy/paste docstrings instead of patching
jbrockmendel Oct 28, 2017
dd99721
Merge branch 'master' of https://github.com/pandas-dev/pandas into ts…
jbrockmendel Oct 28, 2017
776d581
Update pickle_compat
jbrockmendel Oct 28, 2017
3a44c2c
fix import of NaTType
jbrockmendel Oct 28, 2017
009c907
update import; fixes downstream test
jbrockmendel Oct 29, 2017
449d5de
import nat_unpickle to fix backcompat pickle
jbrockmendel Oct 29, 2017
05e5981
flake8 fixup
jbrockmendel Oct 29, 2017
8af334a
Merge branch 'master' of https://github.com/pandas-dev/pandas into ts…
jbrockmendel Oct 29, 2017
a2c3c7e
Merge branch 'master' of https://github.com/pandas-dev/pandas into ts…
jbrockmendel Oct 31, 2017
63ff688
remove import to try to recreate test failure
jbrockmendel Oct 31, 2017
5f3b512
nat_pickle fixup
jbrockmendel Oct 31, 2017
11e699c
another try at nat_pickle
jbrockmendel Oct 31, 2017
4b7593e
Merge branch 'master' of https://github.com/pandas-dev/pandas into ts…
jbrockmendel Oct 31, 2017
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move NaT to self-contained module
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@jbrockmendel
jbrockmendel committed Oct 28, 2017
commit 3926da5f7c120331ced6efdd5ed0dc95280e69db
5 changes: 3 additions & 2 deletions pandas/_libs/period.pyx
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Expand Up @@ -33,10 +33,11 @@ from pandas._libs import tslib
from pandas._libs.tslib import Timestamp, iNaT, NaT
from tslibs.timezones cimport (
is_utc, is_tzlocal, get_utcoffset, get_dst_info, maybe_get_tz)
from tslib cimport _nat_scalar_rules

from tslibs.parsing import parse_time_string, NAT_SENTINEL
from tslibs.frequencies cimport get_freq_code
from tslibs.nattype import _nat_strings
from tslibs.nattype cimport _nat_scalar_rules
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@jreback jreback Oct 31, 2017

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in followup I could de-privatize this _nat_scalar_rules)
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@jbrockmendel jbrockmendel Oct 31, 2017

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That works. I'm also ok with getting rid of it, since op != Py_NE is pretty easy.

from pandas.tseries import offsets
from pandas.tseries import frequencies
Expand Down Expand Up @@ -1185,7 +1186,7 @@ class Period(_Period):
converted = other.asfreq(freq)
ordinal = converted.ordinal

elif is_null_datetimelike(value) or value in tslib._nat_strings:
elif is_null_datetimelike(value) or value in _nat_strings:
ordinal = iNaT

elif is_string_object(value) or util.is_integer_object(value):
Expand Down
2 changes: 1 addition & 1 deletion pandas/_libs/src/inference.pyx
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Expand Up @@ -2,7 +2,7 @@ import sys
from decimal import Decimal
cimport util
cimport cython
from tslib import NaT
from tslibs.nattype import NaT
from tslibs.timezones cimport get_timezone
from datetime import datetime, timedelta
iNaT = util.get_nat()
Expand Down
1 change: 0 additions & 1 deletion pandas/_libs/tslib.pxd
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Expand Up @@ -2,7 +2,6 @@ from numpy cimport ndarray, int64_t

cdef convert_to_tsobject(object, object, object, bint, bint)
cpdef convert_to_timedelta64(object, object)
cdef bint _nat_scalar_rules[6]
cdef bint _check_all_nulls(obj)

cdef _to_i8(object val)
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