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"""
Timedelta benchmarks with non-tslibs dependencies. See
benchmarks.tslibs.timedelta for benchmarks that rely only on tslibs.
"""
import numpy as np
from pandas import DataFrame, Series, timedelta_range, to_timedelta
class ToTimedelta:
def setup(self):
self.ints = np.random.randint(0, 60, size=10000)
self.str_days = []
self.str_seconds = []
for i in self.ints:
self.str_days.append(f"{i} days")
self.str_seconds.append(f"00:00:{i:02d}")
def time_convert_int(self):
to_timedelta(self.ints, unit="s")
def time_convert_string_days(self):
to_timedelta(self.str_days)
def time_convert_string_seconds(self):
to_timedelta(self.str_seconds)
class ToTimedeltaErrors:
params = ["coerce", "ignore"]
param_names = ["errors"]
def setup(self, errors):
ints = np.random.randint(0, 60, size=10000)
self.arr = [f"{i} days" for i in ints]
self.arr[-1] = "apple"
def time_convert(self, errors):
to_timedelta(self.arr, errors=errors)
class DatetimeAccessor:
def setup_cache(self):
N = 100000
series = Series(timedelta_range("1 days", periods=N, freq="h"))
return series
def time_dt_accessor(self, series):
series.dt
def time_timedelta_days(self, series):
series.dt.days
def time_timedelta_seconds(self, series):
series.dt.seconds
def time_timedelta_microseconds(self, series):
series.dt.microseconds
def time_timedelta_nanoseconds(self, series):
series.dt.nanoseconds
class TimedeltaIndexing:
def setup(self):
self.index = timedelta_range(start="1985", periods=1000, freq="D")
self.index2 = timedelta_range(start="1986", periods=1000, freq="D")
self.series = Series(range(1000), index=self.index)
self.timedelta = self.index[500]
def time_get_loc(self):
self.index.get_loc(self.timedelta)
def time_shallow_copy(self):
self.index._shallow_copy()
def time_series_loc(self):
self.series.loc[self.timedelta]
def time_align(self):
DataFrame({"a": self.series, "b": self.series[:500]})
def time_intersection(self):
self.index.intersection(self.index2)
def time_union(self):
self.index.union(self.index2)
def time_unique(self):
self.index.unique()
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