时间比较：

Question

鉴于此基准日期：

base_date = "10/29 06:58 AM"

我想在列表中找到一个包含base_date最近日期的元组，但它不能是更早的日期。

list_date = [('10/30 02:18 PM', '-103', '-107'), ('10/30 02:17 PM', '+100', '-110'), \
             ('10/29 02:15 AM', '-101', '-109')

所以这里的输出应该是('10/30 02:17 PM', '+100', '-110')（它不能是第3个元组，因为它的发生日期早于基准日期）

我的问题是，这个日期比较是否存在任何模块？我试图首先将数据全部更改为AM格式，然后进行比较，但我的代码变得很丑，有很多切片。

@edit：

要测试的大清单：

[('10/30 02:18 PM', '+13 -103', '-13 -107'), ('10/30 02:17 PM', '+13 +100', '-13 -110'), ('10/30 02:15 PM', '+13 -101', '-13 -109'), ('10/30 02:14 PM', '+13 -103', '-13 -107'), ('10/30 01:59 PM', '+13 -105', '-13 -105'), ('10/30 01:46 PM', '+13 -106', '-13 -104'), ('10/30 01:37 PM', '+13 -105', '-13 -105'), ('10/30 01:24 PM', '+13 -107', '-13 -103'), ('10/30 01:23 PM', '+13 -106', '-13 -104'), ('10/30 01:05 PM', '+13 -103', '-13 -107'), ('10/30 01:02 PM', '+13 -104', '-13 -106'), ('10/30 12:55 PM', '+13 -103', '-13 -107'), ('10/30 12:51 PM', '+13.5 -110', '-13.5 +100'), ('10/30 12:44 PM', '+13.5 -108', '-13.5 -102'), ('10/30 12:38 PM', '+13.5 -107', '-13.5 -103'), ('10/30 12:35 PM', '+13 -102', '-13 -108'), ('10/30 12:34 PM', '+13 -103', '-13 -107'), ('10/30 12:06 PM', '+13.5 -110', '-13.5 +100'), ('10/30 11:57 AM', '+13.5 -108', '-13.5 -102'), ('10/30 11:36 AM', '+13.5 -107', '-13.5 -103'), ('10/30 09:01 AM', '+13.5 -110', '-13.5 +100'), ('10/30 08:59 AM', '+13.5 -108', '-13.5 -102'), ('10/30 08:13 AM', '+13.5 -105', '-13.5 -105'), ('10/30 06:11 AM', '+13.5 +100', '-13.5 -110'), ('10/30 06:09 AM', '+13.5 -105', '-13.5 -105'), ('10/30 06:04 AM', '+13.5 -110', '-13.5 +100'), ('10/30 05:32 AM', '+13.5 -105', '-13.5 -105'), ('10/30 04:48 AM', '+13.5 -107', '-13.5 -103'), ('10/30 12:51 AM', '+13.5 -110', '-13.5 +100'), ('10/29 01:31 PM', '+13.5 -105', '-13.5 -105'), ('10/29 01:31 PM', '+13 +103', '-13 -113'), ('10/29 01:28 PM', '+13 -102', '-13 -108'), ('10/29 07:59 AM', '+13 -105', '-13 -105'), ('10/29 07:20 AM', '+13 -103', '-13 -107'), ('10/29 07:14 AM', '+13 -105', '-13 -105'), ('10/29 04:47 AM', '+13 +100', '-13 -110'), ('10/29 04:14 AM', '+13 -105', '-13 -105'), ('10/28 08:17 PM', '+12.5 +100', '-12.5 -110'), ('10/28 12:52 PM', '+12.5 -105', '-12.5 -105')]

test2的大清单：

[('10/30 04:30 PM', '+1.5 -111', '-1.5 +101'), ('10/30 04:24 PM', '+1.5 -110', '-1.5     +100'), ('10/30 04:21 PM', '+1.5 -111', '-1.5 +101'), ('10/30 04:15 PM', '+1.5 -112', '-1.5 +102'), ('10/30 04:14 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:57 PM', '+1.5 -111', '-1.5 +101'), ('10/30 03:40 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:31 PM', '+1.5 -111', '-1.5 +101'), ('10/30 03:30 PM', '+1.5 -109', '-1.5 -101'), ('10/30 03:25 PM', '+1.5 -107', '-1.5 -103'), ('10/30 03:24 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:23 PM', '+1.5 -108', '-1.5 -102'), ('10/30 03:22 PM', '+1.5 -106', '-1.5 -104'), ('10/30 02:14 PM', '+1.5 -104', '-1.5 -106'), ('10/30 01:41 PM', '+1.5 -105', '-1.5 -105'), ('10/30 01:37 PM', '+1.5 -107', '-1.5 -103'), ('10/30 01:36 PM', '+1.5 -105', '-1.5 -105'), ('10/30 01:06 PM', '+1.5 -103', '-1.5 -107'), ('10/30 12:56 PM', '+2 -111', '-2 +101'), ('10/30 12:53 PM', '+2 -110', '-2 +100'), ('10/30 12:50 PM', '+2 -113', '-2 +103'), ('10/30 12:49 PM', '+2 -112', '-2 +102'), ('10/30 12:46 PM', '+2 -113', '-2 +103'), ('10/30 12:45 PM', '+2 -110', '-2 +100'), ('10/30 12:43 PM', '+2 -108', '-2 -102'), ('10/30 12:38 PM', '+2.5 -116', '-2.5 +106'), ('10/30 12:38 PM', '+2.5 -113', '-2.5 +103'), ('10/30 12:37 PM', '+2.5 -110', '-2.5 +100'), ('10/30 10:30 AM', '+2.5 -105', '-2.5 -105'), ('10/30 10:07 AM', '+3 -113', '-3 +103'), ('10/30 09:55 AM', '+3 -112', '-3 +102'), ('10/30 09:51 AM', '+3 -110', '-3 +100'), ('10/30 09:32 AM', '+3 -109', '-3 -101'), ('10/30 06:04 AM', '+3 -110', '-3 +100'), ('10/30 03:16 AM', '+3 -107', '-3 -103'), ('10/30 03:14 AM', '+3.5 -116', '-3.5 +106'), ('10/30 01:03 AM', '+3.5 -115', '-3.5 +105'), ('10/30 12:17 AM', '+3.5 -110', '-3.5 +100'), ('10/29 08:52 PM', '+3.5 -108', '-3.5 -102'), ('10/29 01:31 PM', '+3.5 -105', '-3.5 -105'), ('10/29 06:48 AM', '+3.5 -110', '-3.5 +100'), ('10/29 06:47 AM', '+3.5 -109', '-3.5 -101'), ('10/29 05:39 AM', '+3.5 -113', '-3.5 +103'), ('10/29 03:34 AM', '+3.5 -108', '-3.5 -102'), ('10/29 12:44 AM', '+3.5 -110', '-3.5 +100'), ('10/29 12:41 AM', '+3.5 -107', '-3.5 -103'), ('10/29 12:40 AM', '+3.5 -105', '-3.5 -105'), ('10/28 12:52 PM', '+4 -105', '-4 -105')]

Answer 1

这可以使用datetime模块来完成，该模块能够将日期字符串解析为datetime对象，该对象支持日期的比较和算术：

from datetime import datetime

# function for parsing strings using specific format
get_datetime = lambda s: datetime.strptime(s, "%m/%d %I:%M %p")

base = get_datetime(base_date)
later = filter(lambda d: get_datetime(d[0]) > base, list_date)
closest_date = min(later, key = lambda d: get_datetime(d[0]))

Answer 2

>>> from datetime import timedelta, datetime
>>> base_date = "10/29 06:58 AM"
>>> b_d = datetime.strptime(base_date, "%m/%d %I:%M %p")
def func(x):
    d =  datetime.strptime(x[0], "%m/%d %I:%M %p")
    delta =  d - b_d if d > b_d else timedelta.max
    return delta
... 
>>> min(list_date, key = func)
('10/30 02:17 PM', '+100', '-110')

datetime.strptime将日期转换为日期时间对象，因此b_d现在看起来像这样：

>>> b_d
datetime.datetime(1900, 10, 29, 6, 58)

现在我们可以编写一个可以传递给key的{{1}}参数的函数：

min

如果delta = d - b_d if d > b_d else timedelta.max，即传递给d > b_d的日期大于min，则将其差异分配给base_date，否则为其分配delta。

timedelta.max

<强>更新

>>> timedelta.max
datetime.timedelta(999999999, 86399, 999999)

时间比较：

<强>脚本：

>>> from datetime import timedelta, datetime
>>> base_date = '10/29 06:59 AM'
>>> b_d = datetime.strptime(base_date, "%m/%d %I:%M %p")
>>> def func(x):
...         d =  datetime.strptime(x[0], "%m/%d %I:%M %p")
...         delta =  d - b_d if d > b_d else timedelta.max
...         return delta
... 
>>> lis2 = [('10/30 04:30 PM', '+1.5 -111', '-1.5 +101'), ('10/30 04:24 PM', '+1.5 -110', '-1.5     +100'), ('10/30 04:21 PM', '+1.5 -111', '-1.5 +101'), ('10/30 04:15 PM', '+1.5 -112', '-1.5 +102'), ('10/30 04:14 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:57 PM', '+1.5 -111', '-1.5 +101'), ('10/30 03:40 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:31 PM', '+1.5 -111', '-1.5 +101'), ('10/30 03:30 PM', '+1.5 -109', '-1.5 -101'), ('10/30 03:25 PM', '+1.5 -107', '-1.5 -103'), ('10/30 03:24 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:23 PM', '+1.5 -108', '-1.5 -102'), ('10/30 03:22 PM', '+1.5 -106', '-1.5 -104'), ('10/30 02:14 PM', '+1.5 -104', '-1.5 -106'), ('10/30 01:41 PM', '+1.5 -105', '-1.5 -105'), ('10/30 01:37 PM', '+1.5 -107', '-1.5 -103'), ('10/30 01:36 PM', '+1.5 -105', '-1.5 -105'), ('10/30 01:06 PM', '+1.5 -103', '-1.5 -107'), ('10/30 12:56 PM', '+2 -111', '-2 +101'), ('10/30 12:53 PM', '+2 -110', '-2 +100'), ('10/30 12:50 PM', '+2 -113', '-2 +103'), ('10/30 12:49 PM', '+2 -112', '-2 +102'), ('10/30 12:46 PM', '+2 -113', '-2 +103'), ('10/30 12:45 PM', '+2 -110', '-2 +100'), ('10/30 12:43 PM', '+2 -108', '-2 -102'), ('10/30 12:38 PM', '+2.5 -116', '-2.5 +106'), ('10/30 12:38 PM', '+2.5 -113', '-2.5 +103'), ('10/30 12:37 PM', '+2.5 -110', '-2.5 +100'), ('10/30 10:30 AM', '+2.5 -105', '-2.5 -105'), ('10/30 10:07 AM', '+3 -113', '-3 +103'), ('10/30 09:55 AM', '+3 -112', '-3 +102'), ('10/30 09:51 AM', '+3 -110', '-3 +100'), ('10/30 09:32 AM', '+3 -109', '-3 -101'), ('10/30 06:04 AM', '+3 -110', '-3 +100'), ('10/30 03:16 AM', '+3 -107', '-3 -103'), ('10/30 03:14 AM', '+3.5 -116', '-3.5 +106'), ('10/30 01:03 AM', '+3.5 -115', '-3.5 +105'), ('10/30 12:17 AM', '+3.5 -110', '-3.5 +100'), ('10/29 08:52 PM', '+3.5 -108', '-3.5 -102'), ('10/29 01:31 PM', '+3.5 -105', '-3.5 -105'), ('10/29 06:48 AM', '+3.5 -110', '-3.5 +100'), ('10/29 06:47 AM', '+3.5 -109', '-3.5 -101'), ('10/29 05:39 AM', '+3.5 -113', '-3.5 +103'), ('10/29 03:34 AM', '+3.5 -108', '-3.5 -102'), ('10/29 12:44 AM', '+3.5 -110', '-3.5 +100'), ('10/29 12:41 AM', '+3.5 -107', '-3.5 -103'), ('10/29 12:40 AM', '+3.5 -105', '-3.5 -105'), ('10/28 12:52 PM', '+4 -105', '-4 -105')]
>>> min(lis2, key = func)
('10/29 01:31 PM', '+3.5 -105', '-3.5 -105')

<强>结果：

from datetime import datetime, timedelta
import sys
import time
list_date = [('10/30 04:30 PM', '+1.5 -111', '-1.5 +101'), ('10/30 04:24 PM', '+1.5 -110', '-1.5     +100'), ('10/30 04:21 PM', '+1.5 -111', '-1.5 +101'), ('10/30 04:15 PM', '+1.5 -112', '-1.5 +102'), ('10/30 04:14 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:57 PM', '+1.5 -111', '-1.5 +101'), ('10/30 03:40 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:31 PM', '+1.5 -111', '-1.5 +101'), ('10/30 03:30 PM', '+1.5 -109', '-1.5 -101'), ('10/30 03:25 PM', '+1.5 -107', '-1.5 -103'), ('10/30 03:24 PM', '+1.5 -110', '-1.5 +100'), ('10/30 03:23 PM', '+1.5 -108', '-1.5 -102'), ('10/30 03:22 PM', '+1.5 -106', '-1.5 -104'), ('10/30 02:14 PM', '+1.5 -104', '-1.5 -106'), ('10/30 01:41 PM', '+1.5 -105', '-1.5 -105'), ('10/30 01:37 PM', '+1.5 -107', '-1.5 -103'), ('10/30 01:36 PM', '+1.5 -105', '-1.5 -105'), ('10/30 01:06 PM', '+1.5 -103', '-1.5 -107'), ('10/30 12:56 PM', '+2 -111', '-2 +101'), ('10/30 12:53 PM', '+2 -110', '-2 +100'), ('10/30 12:50 PM', '+2 -113', '-2 +103'), ('10/30 12:49 PM', '+2 -112', '-2 +102'), ('10/30 12:46 PM', '+2 -113', '-2 +103'), ('10/30 12:45 PM', '+2 -110', '-2 +100'), ('10/30 12:43 PM', '+2 -108', '-2 -102'), ('10/30 12:38 PM', '+2.5 -116', '-2.5 +106'), ('10/30 12:38 PM', '+2.5 -113', '-2.5 +103'), ('10/30 12:37 PM', '+2.5 -110', '-2.5 +100'), ('10/30 10:30 AM', '+2.5 -105', '-2.5 -105'), ('10/30 10:07 AM', '+3 -113', '-3 +103'), ('10/30 09:55 AM', '+3 -112', '-3 +102'), ('10/30 09:51 AM', '+3 -110', '-3 +100'), ('10/30 09:32 AM', '+3 -109', '-3 -101'), ('10/30 06:04 AM', '+3 -110', '-3 +100'), ('10/30 03:16 AM', '+3 -107', '-3 -103'), ('10/30 03:14 AM', '+3.5 -116', '-3.5 +106'), ('10/30 01:03 AM', '+3.5 -115', '-3.5 +105'), ('10/30 12:17 AM', '+3.5 -110', '-3.5 +100'), ('10/29 08:52 PM', '+3.5 -108', '-3.5 -102'), ('10/29 01:31 PM', '+3.5 -105', '-3.5 -105'), ('10/29 06:48 AM', '+3.5 -110', '-3.5 +100'), ('10/29 06:47 AM', '+3.5 -109', '-3.5 -101'), ('10/29 05:39 AM', '+3.5 -113', '-3.5 +103'), ('10/29 03:34 AM', '+3.5 -108', '-3.5 -102'), ('10/29 12:44 AM', '+3.5 -110', '-3.5 +100'), ('10/29 12:41 AM', '+3.5 -107', '-3.5 -103'), ('10/29 12:40 AM', '+3.5 -105', '-3.5 -105'), ('10/28 12:52 PM', '+4 -105', '-4 -105')]

base_date = "10/29 06:58 AM"

def func1(list_date):
    #http://stackoverflow.com/a/17249420/846892
    get_datetime = lambda s: datetime.strptime(s, "%m/%d %I:%M %p")
    base = get_datetime(base_date)
    later = filter(lambda d: get_datetime(d[0]) > base, list_date)
    return min(later, key = lambda d: get_datetime(d[0]))

def func2(list_date):
    #http://stackoverflow.com/a/17249470/846892
    b_d = datetime.strptime(base_date, "%m/%d %I:%M %p")
    def func(x):
       d =  datetime.strptime(x[0], "%m/%d %I:%M %p")
       delta =  d - b_d if d > b_d else timedelta.max
       return delta
    return min(list_date, key = func)

def func3(list_date):
    #http://stackoverflow.com/a/17249529/846892
    fmt = '%m/%d %I:%M %p'
    d = datetime.strptime(base_date, fmt)
    def foo(x):
        return (datetime.strptime(x[0],fmt)-d).total_seconds() > 0
    return sorted(list_date, key=foo)[-1]

def func4(list_date):
    #http://stackoverflow.com/a/17249441/846892
    fmt = '%m/%d %I:%M %p'
    base_d = datetime.strptime(base_date, fmt)
    candidates = ((datetime.strptime(d, fmt), d, x, y) for d, x, y in list_date)
    candidates = min((dt, d, x, y) for dt, d, x, y in candidates if dt > base_d)
    return  candidates[1:]

Answer 3

线性搜索？

import sys
import time

base_date = "10/29 06:58 AM"

def str_to_my_time(my_str):
    return time.mktime(time.strptime(my_str, "%m/%d %I:%M %p")) 
                # assume year 1900...

base_dt = str_to_my_time(base_date)

list_date = [('10/30 02:18 PM', '-103', '-107'), 
             ('10/30 02:17 PM', '+100', '-110'),
             ('10/29 02:15 AM', '-101', '-109')]


best_delta = sys.maxint
best_match = None

for t in list_date:
    the_dt = str_to_my_time(t[0])
    delta_sec = the_dt - base_dt
    if (delta_sec >= 0) and (delta_sec < best_delta):
        best_delta = delta_sec
        best_match = t

print best_match, best_delta

产：

('10/30 02:17 PM', '+100', '-110') 112740.0

Answer 4

装饰，过滤，找到最近的日期，不装饰

>>> base_date = "10/29 06:58 AM"
>>> list_date = [
...     ('10/30 02:18 PM', '-103', '-107'),
...     ('10/30 02:17 PM', '+100', '-110'),
...     ('10/29 02:15 AM', '-101', '-109')
... ]
>>> import datetime
>>> fmt = '%m/%d %H:%M %p'
>>> base_d = datetime.datetime.strptime(base_date, fmt)
>>> candidates = ((datetime.datetime.strptime(d, fmt), d, x, y) for d, x, y in list_date)
>>> candidates = min((dt, d, x, y) for dt, d, x, y in candidates if dt > base_d)
>>> print candidates[1:]
('10/30 02:17 PM', '+100', '-110')

Answer 5

import time
import sys

#The Function
def to_sec(date_string):
    return time.mktime(time.strptime(date_string, '%m/%d %I:%M %p'))


#The Test
base_date = "10/29 06:58 AM"
base_date_sec = to_sec(base_date)
result = None
difference = sys.maxint
list_date = [
        ('10/30 02:18 PM', '-103', '-107'),
        ('10/30 02:17 PM', '+100', '-110'), 
        ('10/29 02:15 AM', '-101', '-109') ]
for date_str in list_date:
    diff_sec = to_sec(date_str[0])-base_date_sec
    if diff_sec >= 0 and diff_sec < difference:
        result = date_str
        difference = diff_sec
print result

Answer 6

import datetime

fmt = '%m/%d %H:%M %p'
d = datetime.datetime.strptime(base_date, fmt)
def foo(x):
   return (datetime.datetime.strptime(x[0],fmt)-d).total_seconds() > 0
sorted(list_date, key=foo)[-1]

Answer 7

您可以考虑将日期列表放入Pandas索引中，然后使用'truncate'或'get_loc'函数。

import pandas as pd

##Initial inputs
list_date = [('10/30 02:18 PM', '-103', '-107'),('10/29 02:15 AM', '-101', '-109') , ('10/30 02:17 PM', '+100', '-110'), \
             ]  # reordered to show the method is input order insensitive
base_date = "10/29 06:58 AM"


##Make a data frame with data
df=pd.DataFrame(list_date)
df.columns=['date','val1','val2']
dateIndex=pd.to_datetime(df['date'], format='%m/%d %I:%M %p')
df=df.set_index(dateIndex) 
df=df.sort_index(ascending=False) #earliest comes on top 

##Find the result
base_dateObj=pd.to_datetime(base_date, format='%m/%d %I:%M %p')
result=df.truncate(after=base_dateObj).iloc[-1]  #take the bottom value, or the 1st after the base date
(result['date'],result['val1'], result['val2']) # result is ('10/30 02:17 PM', '+100', '-110')

参考：this link

Answer 8

我正在查找此问题，并找到了一些答案，其中大多数检查了所有要素。我对日期进行了排序（并假设大多数人都这样做了），所以如果您也这样做，请使用numpy：

import numpy as np
// dates is a numpy array of np.datetime64 objects
dates = np.array([date1, date2, date3, ...], dtype=np.datetime64)
timestamp = np.datetime64('Your date')
np.searchsorted(dates, timestamp)

searchsorted使用二进制搜索，该搜索使用日期已排序的事实，因此非常有效。如果您使用熊猫，这是可能的：

dates = df.index # df is a DatetimeIndex-ed dataframe
timestamp = pd.to_datetime('your date here', format='its format')
np.searchsorted(dates, timestamp)

该函数返回最接近日期的索引（如果搜索的日期包含在日期中，则返回其索引[如果不需要，请使用side ='right'作为该函数的参数]），因此要获取日期，请执行以下操作：

dates[np.searchsorted(dates, timestamp)]

获取最接近给定日期的日期

8 个答案:

时间比较：