python-3.x - 将各种字符串更改为时间戳 Python 3？

Question

鉴于我可以从我的用户（聊天机器人）那里获得所有可能的时间格式：

09:03
9:23A.M.
9:23 A.m.
13:44 pm
20:00 P.m
15:40
00:00
12:33
4:33p.M
...

我想将它们转换为适当的时间。不会有我可以使用的一种格式。

请告知如何解决此类问题？

我已经strptime从datetime包中尝试过，但我需要指定格式，并且每次都可能不同。

标签： python-3.xdatetimetime

Answer 1

感谢这个惊人的来源，找到我的答案！为他人发帖：

dateutil

dateutil 模块是 datetime 模块的扩展。我们不需要传递任何解析代码来解析字符串。例如：

from dateutil.parser import parse

datetime = parse('2018-06-29 22:21:41')

print(datetime)
This parse function will parse the string automatically and store it in the datetime variable. Parsing is done automatically. You don't have to mention any format string. Let's try to parse different types of strings using dateutil:

from dateutil.parser import parse

date_array = [
    '2018-06-29 08:15:27.243860',
    'Jun 28 2018  7:40AM',
    'Jun 28 2018 at 7:40AM',
    'September 18, 2017, 22:19:55',
    'Sun, 05/12/1999, 12:30PM',
    'Mon, 21 March, 2015',
    '2018-03-12T10:12:45Z',
    '2018-06-29 17:08:00.586525+00:00',
    '2018-06-29 17:08:00.586525+05:00',
    'Tuesday , 6th September, 2017 at 4:30pm'
]

for date in date_array:
    print('Parsing: ' + date)
    dt = parse(date)
    print(dt.date())
    print(dt.time())
    print(dt.tzinfo)
    print('\n')

Output:

$ python3 dateutil-1.py
Parsing: 2018-06-29 08:15:27.243860
2018-06-29
08:15:27.243860
None

Parsing: Jun 28 2018  7:40AM
2018-06-28
07:40:00
None

Parsing: Jun 28 2018 at 7:40AM
2018-06-28
07:40:00
None

Parsing: September 18, 2017, 22:19:55
2017-09-18
22:19:55
None

Parsing: Sun, 05/12/1999, 12:30PM
1999-05-12
12:30:00
None

Parsing: Mon, 21 March, 2015
2015-03-21
00:00:00
None

Parsing: 2018-03-12T10:12:45Z
2018-03-12
10:12:45
tzutc()

Parsing: 2018-06-29 17:08:00.586525+00:00
2018-06-29
17:08:00.586525
tzutc()

Parsing: 2018-06-29 17:08:00.586525+05:00
2018-06-29
17:08:00.586525
tzoffset(None, 18000)

Parsing: Tuesday , 6th September, 2017 at 4:30pm
2017-09-06
16:30:00
None

您可以看到几乎任何类型的字符串都可以使用 dateutil 模块轻松解析。

Maya

Maya 还使解析字符串和更改时区变得非常容易。一些简单的例子如下所示：

import maya

dt = maya.parse('2018-04-29T17:45:25Z').datetime()
print(dt.date())
print(dt.time())
print(dt.tzinfo)
Output:

$ python3 maya-1.py
2018-04-29
17:45:25
UTC
For converting the time to a different timezone:

import maya

dt = maya.parse('2018-04-29T17:45:25Z').datetime(to_timezone='America/New_York', naive=False)
print(dt.date())
print(dt.time())
print(dt.tzinfo)
Output:

$ python3 maya-2.py
2018-04-29
13:45:25
America/New_York

现在是不是很容易使用？让我们尝试maya使用与 相同的字符串集dateutil：

import maya

date_array = [
    '2018-06-29 08:15:27.243860',
    'Jun 28 2018  7:40AM',
    'Jun 28 2018 at 7:40AM',
    'September 18, 2017, 22:19:55',
    'Sun, 05/12/1999, 12:30PM',
    'Mon, 21 March, 2015',
    '2018-03-12T10:12:45Z',
    '2018-06-29 17:08:00.586525+00:00',
    '2018-06-29 17:08:00.586525+05:00',
    'Tuesday , 6th September, 2017 at 4:30pm'
]

for date in date_array:
    print('Parsing: ' + date)
    dt = maya.parse(date).datetime()
    print(dt)
    print(dt.date())
    print(dt.time())
    print(dt.tzinfo)
Output:

$ python3 maya-3.py
Parsing: 2018-06-29 08:15:27.243860
2018-06-29 08:15:27.243860+00:00
2018-06-29
08:15:27.243860
UTC

Parsing: Jun 28 2018  7:40AM
2018-06-28 07:40:00+00:00
2018-06-28
07:40:00
UTC

Parsing: Jun 28 2018 at 7:40AM
2018-06-28 07:40:00+00:00
2018-06-28
07:40:00
UTC

Parsing: September 18, 2017, 22:19:55
2017-09-18 22:19:55+00:00
2017-09-18
22:19:55
UTC

Parsing: Sun, 05/12/1999, 12:30PM
1999-05-12 12:30:00+00:00
1999-05-12
12:30:00
UTC

Parsing: Mon, 21 March, 2015
2015-03-21 00:00:00+00:00
2015-03-21
00:00:00
UTC

Parsing: 2018-03-12T10:12:45Z
2018-03-12 10:12:45+00:00
2018-03-12
10:12:45
UTC

Parsing: 2018-06-29 17:08:00.586525+00:00
2018-06-29 17:08:00.586525+00:00
2018-06-29
17:08:00.586525
UTC

Parsing: 2018-06-29 17:08:00.586525+05:00
2018-06-29 12:08:00.586525+00:00
2018-06-29
12:08:00.586525
UTC

Parsing: Tuesday , 6th September, 2017 at 4:30pm
2017-09-06 16:30:00+00:00
2017-09-06
16:30:00
UTC

如您所见，所有日期格式均已解析，但您注意到其中的不同了吗？如果我们不提供时区信息，它会自动将其转换为 UTC。因此，需要注意的是，如果时间不是 UTC，我们需要提供 to_timezone 和 naive 参数。