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"""
ipython analogue:
tr = TimeIntsToPydatetime()
mi = pd.MultiIndex.from_product(
tr.params[:-1] + ([str(x) for x in tr.params[-1]],)
)
df = pd.DataFrame(np.nan, index=mi, columns=["mean", "stdev"])
for box in tr.params[0]:
for size in tr.params[1]:
for tz in tr.params[2]:
tr.setup(box, size, tz)
key = (box, size, str(tz))
print(key)
val = %timeit -o tr.time_ints_to_pydatetime(box, size, tz)
df.loc[key] = (val.average, val.stdev)
"""
from datetime import timedelta, timezone
from dateutil.tz import gettz, tzlocal
import numpy as np
import pytz
try:
from pandas._libs.tslibs import ints_to_pydatetime
except ImportError:
from pandas._libs.tslib import ints_to_pydatetime
_tzs = [
None,
timezone.utc,
timezone(timedelta(minutes=60)),
pytz.timezone("US/Pacific"),
gettz("Asia/Tokyo"),
tzlocal(),
]
_sizes = [0, 1, 100, 10 ** 4, 10 ** 6]
class TimeIntsToPydatetime:
params = (
["time", "date", "datetime", "timestamp"],
_sizes,
_tzs,
)
param_names = ["box", "size", "tz"]
# TODO: fold? freq?
def setup(self, box, size, tz):
arr = np.random.randint(0, 10, size=size, dtype="i8")
self.i8data = arr
def time_ints_to_pydatetime(self, box, size, tz):
if box == "date":
# ints_to_pydatetime does not allow non-None tz with date;
# this will mean doing some duplicate benchmarks
tz = None
ints_to_pydatetime(self.i8data, tz, box=box)
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