forked from pandas-dev/pandas
-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathstrftime.py
109 lines (81 loc) · 3.45 KB
/
strftime.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
import numpy as np
import pandas as pd
from pandas import offsets
class DatetimeStrftime:
timeout = 1500
params = [1000, 10000]
param_names = ["nobs"]
def setup(self, nobs):
d = "2018-11-29"
dt = "2018-11-26 11:18:27.0"
self.data = pd.DataFrame(
{
"dt": [np.datetime64(dt)] * nobs,
"d": [np.datetime64(d)] * nobs,
"r": [np.random.uniform()] * nobs,
}
)
def time_frame_date_to_str(self, nobs):
self.data["d"].astype(str)
def time_frame_date_formatting_default(self, nobs):
self.data["d"].dt.strftime(date_format=None)
def time_frame_date_formatting_default_explicit(self, nobs):
self.data["d"].dt.strftime(date_format="%Y-%m-%d")
def time_frame_date_formatting_custom(self, nobs):
self.data["d"].dt.strftime(date_format="%Y---%m---%d")
def time_frame_datetime_to_str(self, nobs):
self.data["dt"].astype(str)
def time_frame_datetime_formatting_default(self, nobs):
self.data["dt"].dt.strftime(date_format=None)
def time_frame_datetime_formatting_default_explicit_date_only(self, nobs):
self.data["dt"].dt.strftime(date_format="%Y-%m-%d")
def time_frame_datetime_formatting_default_explicit(self, nobs):
self.data["dt"].dt.strftime(date_format="%Y-%m-%d %H:%M:%S")
def time_frame_datetime_formatting_default_with_float(self, nobs):
self.data["dt"].dt.strftime(date_format="%Y-%m-%d %H:%M:%S.%f")
def time_frame_datetime_formatting_custom(self, nobs):
self.data["dt"].dt.strftime(date_format="%Y-%m-%d --- %H:%M:%S")
class PeriodStrftime:
timeout = 1500
params = ([1000, 10000], ["D", "h"])
param_names = ["nobs", "freq"]
def setup(self, nobs, freq):
self.data = pd.DataFrame(
{
"p": pd.period_range(start="2000-01-01", periods=nobs, freq=freq),
"r": [np.random.uniform()] * nobs,
}
)
self.data["i"] = self.data["p"]
self.data.set_index("i", inplace=True)
if freq == "D":
self.default_fmt = "%Y-%m-%d"
elif freq == "h":
self.default_fmt = "%Y-%m-%d %H:00"
def time_frame_period_to_str(self, nobs, freq):
self.data["p"].astype(str)
def time_frame_period_formatting_default(self, nobs, freq):
self.data["p"].dt.strftime(date_format=None)
def time_frame_period_formatting_default_explicit(self, nobs, freq):
self.data["p"].dt.strftime(date_format=self.default_fmt)
def time_frame_period_formatting_custom(self, nobs, freq):
self.data["p"].dt.strftime(date_format="%Y-%m-%d --- %H:%M:%S")
def time_frame_period_formatting_iso8601_strftime_Z(self, nobs, freq):
self.data["p"].dt.strftime(date_format="%Y-%m-%dT%H:%M:%SZ")
def time_frame_period_formatting_iso8601_strftime_offset(self, nobs, freq):
"""Not optimized yet as %z is not supported by `convert_strftime_format`"""
self.data["p"].dt.strftime(date_format="%Y-%m-%dT%H:%M:%S%z")
class BusinessHourStrftime:
timeout = 1500
params = [1000, 10000]
param_names = ["nobs"]
def setup(self, nobs):
self.data = pd.DataFrame(
{
"off": [offsets.BusinessHour()] * nobs,
}
)
def time_frame_offset_str(self, nobs):
self.data["off"].apply(str)
def time_frame_offset_repr(self, nobs):
self.data["off"].apply(repr)