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PERF: Using _Period for optimization #32973

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Merged
merged 10 commits into from
Mar 30, 2020
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PERF: Using _Period for optimization #32973

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PERF: Using _Period for optimization
Mar 24, 2020
1fdbf1b
cimporting _Period
Mar 24, 2020
49181b2
Merge remote-tracking branch 'upstream/master' into PERF-index-_Period
Mar 24, 2020
5f7a6eb
Minor fix
Mar 24, 2020
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Mar 25, 2020
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Merge remote-tracking branch 'upstream/master' into PERF-index-_Period
Mar 25, 2020
1842d76
Merge remote-tracking branch 'upstream/master' into PERF-index-_Period
Mar 26, 2020
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Merge remote-tracking branch 'upstream/master' into PERF-index-_Period
Mar 29, 2020
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Revert changes
Mar 29, 2020
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Merge remote-tracking branch 'upstream/master' into PERF-index-_Period
Mar 29, 2020
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4 changes: 1 addition & 3 deletions pandas/_libs/index.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@ cnp.import_array()

cimport pandas._libs.util as util

from pandas._libs.tslibs import Period
from pandas._libs.tslibs.nattype cimport c_NaT as NaT
from pandas._libs.tslibs.c_timestamp cimport _Timestamp

Expand Down Expand Up @@ -468,9 +467,8 @@ cdef class PeriodEngine(Int64Engine):
cdef int64_t _unbox_scalar(self, scalar) except? -1:
if scalar is NaT:
return scalar.value
if isinstance(scalar, Period):
if isinstance(scalar, periodlib._Period):
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you would need to cimport _Period to get the performance improvement

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Just so I don't do anything stupid, I need to create the file period.pxd at pandas/_libs/tslibs/, correct?

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yep

# NB: we assume that we have the correct freq here.
# TODO: potential optimize by checking for _Period?
return scalar.ordinal
raise TypeError(scalar)

Expand Down