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try:
from pandas._libs.tslibs import (
is_date_array_normalized,
normalize_i8_timestamps,
)
except ImportError:
from pandas._libs.tslibs.conversion import (
normalize_i8_timestamps,
is_date_array_normalized,
)
import pandas as pd
from .tslib import (
_sizes,
_tzs,
tzlocal_obj,
)
class Normalize:
params = [
_sizes,
_tzs,
]
param_names = ["size", "tz"]
def setup(self, size, tz):
# use an array that will have is_date_array_normalized give True,
# so we do not short-circuit early.
dti = pd.date_range("2016-01-01", periods=10, tz=tz).repeat(size // 10)
self.i8data = dti.asi8
if size == 10**6 and tz is tzlocal_obj:
# tzlocal is cumbersomely slow, so skip to keep runtime in check
raise NotImplementedError
def time_normalize_i8_timestamps(self, size, tz):
# 10 i.e. NPY_FR_ns
normalize_i8_timestamps(self.i8data, tz, 10)
def time_is_date_array_normalized(self, size, tz):
# TODO: cases with different levels of short-circuiting
# 10 i.e. NPY_FR_ns
is_date_array_normalized(self.i8data, tz, 10)
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