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BUG #34621 added nanosecond support to class Period #34720

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BUG #34621 added nanosecond support to class Period #34720

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91a7c7e
BUG #34621 added nanosecond support to class Period
Jun 11, 2020
73a6eab
BUG #34621 added tests
Jun 12, 2020
ea9f69c
BUG #34621 added tests (black pandas passed)
Jun 12, 2020
ab5640f
#34131 fix one test failure
Jun 13, 2020
95d740e
#34621 review taken into account
Jun 15, 2020
abb0936
#34621 review taken into account, and suppress a bad copy/paste on li…
Jun 15, 2020
8a559cb
#34621 Added nanosecond support to Period constructor
Jun 16, 2020
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11 changes: 10 additions & 1 deletion pandas/_libs/tslibs/period.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -2355,6 +2355,7 @@ class Period(_Period):

if freq is not None:
freq = cls._maybe_convert_freq(freq)
nanosecond = 0

if ordinal is not None and value is not None:
raise ValueError("Only value or ordinal but not both should be "
Expand Down Expand Up @@ -2404,6 +2405,14 @@ class Period(_Period):
value = str(value)
value = value.upper()
dt, reso = parse_time_string(value, freq)
try:
ts = Timestamp(value)
except ValueError:
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we end up parsing this twice which is not good, yeah i think this needs to be integrated a bit more to parse_time_string.

i guess the currently soln would be ok in the interim, but would need to run asv's on all periods to see what kind of perf hit here.

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As far I read, nanosecond was not accepted into dateutil module. This interim solution could stand for a while.
I stay tuned...

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As far I read, nanosecond was not accepted into dateutil module. This interim solution could stand for a while.
I stay tuned...

we don't wait for dateutil in this, as it will not likey every support nanosecond because the standard library does not

nanosecond = 0
else:
nanosecond = ts.nanosecond
if nanosecond != 0:
reso = 'nanosecond'
if dt is NaT:
ordinal = NPY_NAT

Expand Down Expand Up @@ -2435,7 +2444,7 @@ class Period(_Period):
base = freq_to_dtype_code(freq)
ordinal = period_ordinal(dt.year, dt.month, dt.day,
dt.hour, dt.minute, dt.second,
dt.microsecond, 0, base)
dt.microsecond, 1000*nanosecond, base)

return cls._from_ordinal(ordinal, freq)

Expand Down
16 changes: 16 additions & 0 deletions pandas/tests/scalar/period/test_period.py
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Expand Up @@ -484,6 +484,22 @@ def test_period_cons_combined(self):
with pytest.raises(ValueError, match=msg):
Period("2011-01", freq="1D1W")

@pytest.mark.parametrize("day_", ["1970/01/01 ", "2020-12-31 ", "1981/09/13 "])
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i dont think the trailing underscores are necessary for these names

@pytest.mark.parametrize("hour_", ["00:00:00", "00:00:01", "23:59:59", "12:00:59"])
@pytest.mark.parametrize(
"floating_sec_, expected",
[
(".000000001", 1),
(".000000999", 999),
(".123456789", 789),
(".999999999", 999),
],
)
def test_period_constructor_nanosecond(self, day_, hour_, floating_sec_, expected):
# GH 34621
result = Period(day_ + hour_ + floating_sec_).start_time.nanosecond
assert result == expected


class TestPeriodMethods:
def test_round_trip(self):
Expand Down