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Use the third party dateutil library:

from dateutil import parser
dt = parser.parse("Aug 28 1999 12:00AM")

It can handle most date formats, including the one you need to parse. It's more convenient than strptime as it can guess the correct format most of the time.

It very useful for writing tests, where readability is more important than performance.

You can install it with:

pip install python-dateutil

Check out strptime in the time module. It is the inverse of strftime.

$ python
>>> import time
>>> time.strptime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p')
time.struct_time(tm_year=2005, tm_mon=6, tm_mday=1,
 tm_hour=13, tm_min=33, tm_sec=0,
 tm_wday=2, tm_yday=152, tm_isdst=-1)

I have put together a project that can convert some really neat expressions. Check out timestring.

Here are some examples below:

>>> import timestring
>>> timestring.Date('monday, aug 15th 2015 at 8:40 pm')
<timestring.Date 2015-08-15 20:40:00 4491909392>
>>> timestring.Date('monday, aug 15th 2015 at 8:40 pm').date
datetime.datetime(2015, 8, 15, 20, 40)
>>> timestring.Range('next week')
<timestring.Range From 03/10/14 00:00:00 to 03/03/14 00:00:00 4496004880>
>>> (timestring.Range('next week').start.date, timestring.Range('next week').end.date)
(datetime.datetime(2014, 3, 10, 0, 0), datetime.datetime(2014, 3, 14, 0, 0))

Remember this and you didn't need to get confused in datetime conversion again.

String to datetime object = strptime

datetime object to other formats = strftime

Jun 1 2005 1:33PM

is equals to

%b %d %Y %I:%M%p

%b Month as locale’s abbreviated name(Jun)

%d Day of the month as a zero-padded decimal number(1)

%Y Year with century as a decimal number(2015)

%I Hour (12-hour clock) as a zero-padded decimal number(01)

%M Minute as a zero-padded decimal number(33)

%p Locale’s equivalent of either AM or PM(PM)

so you need strptime i-e converting string to

>>> dates = 
>>> dates.append('Jun 1 2005 1:33PM')
>>> dates.append('Aug 28 1999 12:00AM')
>>> from datetime import datetime
>>> for d in dates:
... date = datetime.strptime(d, '%b %d %Y %I:%M%p')
... print type(date)
... print date
... 

Output

<type 'datetime.datetime'>
2005-06-01 13:33:00
<type 'datetime.datetime'>
1999-08-28 00:00:00

What if you have different format of dates you can use panda or dateutil.parse

>>> import dateutil
>>> dates = 
>>> dates.append('12 1 2017')
>>> dates.append('1 1 2017')
>>> dates.append('1 12 2017')
>>> dates.append('June 1 2017 1:30:00AM')
>>> [parser.parse(x) for x in dates]

OutPut

[datetime.datetime(2017, 12, 1, 0, 0), datetime.datetime(2017, 1, 1, 0, 0), datetime.datetime(2017, 1, 12, 0, 0), datetime.datetime(2017, 6, 1, 1, 30)]

Many timestamps have an implied timezone. To ensure that your code will work in every timezone, you should use UTC internally and attach a timezone each time a foreign object enters the system.

Python 3.2+:

>>> datetime.datetime.strptime(
... "March 5, 2014, 20:13:50", "%B %d, %Y, %H:%M:%S"
... ).replace(tzinfo=datetime.timezone(datetime.timedelta(hours=-3)))

Something that isn't mentioned here and is useful: adding a suffix to the day. I decoupled the suffix logic so you can use it for any number you like, not just dates.

import time

def num_suffix(n):
 '''
 Returns the suffix for any given int
 '''
 suf = ('th','st', 'nd', 'rd')
 n = abs(n) # wise guy
 tens = int(str(n)[-2:])
 units = n % 10
 if tens > 10 and tens < 20:
 return suf[0] # teens with 'th'
 elif units <= 3:
 return suf[units]
 else:
 return suf[0] # 'th'

def day_suffix(t):
 '''
 Returns the suffix of the given struct_time day
 '''
 return num_suffix(t.tm_mday)

# Examples
print num_suffix(123)
print num_suffix(3431)
print num_suffix(1234)
print ''
print day_suffix(time.strptime("1 Dec 00", "%d %b %y"))
print day_suffix(time.strptime("2 Nov 01", "%d %b %y"))
print day_suffix(time.strptime("3 Oct 02", "%d %b %y"))
print day_suffix(time.strptime("4 Sep 03", "%d %b %y"))
print day_suffix(time.strptime("13 Nov 90", "%d %b %y"))
print day_suffix(time.strptime("14 Oct 10", "%d %b %y"))​​​​​​​

Here are two solutions using Pandas to convert dates formatted as strings into datetime.date objects.

import pandas as pd

dates = ['2015-12-25', '2015-12-26']

# 1) Use a list comprehension.
>>> [d.date() for d in pd.to_datetime(dates)]
[datetime.date(2015, 12, 25), datetime.date(2015, 12, 26)]

# 2) Convert the dates to a DatetimeIndex and extract the python dates.
>>> pd.DatetimeIndex(dates).date.tolist()
[datetime.date(2015, 12, 25), datetime.date(2015, 12, 26)]

Timings

dates = pd.DatetimeIndex(start='2000-1-1', end='2010-1-1', freq='d').date.tolist()

>>> %timeit [d.date() for d in pd.to_datetime(dates)]
# 100 loops, best of 3: 3.11 ms per loop

>>> %timeit pd.DatetimeIndex(dates).date.tolist()
# 100 loops, best of 3: 6.85 ms per loop

And here is how to convert the OP's original date-time examples:

datetimes = ['Jun 1 2005 1:33PM', 'Aug 28 1999 12:00AM']

>>> pd.to_datetime(datetimes).to_pydatetime().tolist()
[datetime.datetime(2005, 6, 1, 13, 33), 
 datetime.datetime(1999, 8, 28, 0, 0)]

There are many options for converting from the strings to Pandas Timestamps using to_datetime, so check the docs if you need anything special.

Likewise, Timestamps have many properties and methods that can be accessed in addition to .date

Django Timezone aware datetime object example.

import datetime
from django.utils.timezone import get_current_timezone
tz = get_current_timezone()

format = '%b %d %Y %I:%M%p'
date_object = datetime.datetime.strptime('Jun 1 2005 1:33PM', format)
date_obj = tz.localize(date_object)

This conversion is very important for Django and Python when you have USE_TZ = True:

RuntimeWarning: DateTimeField MyModel.created received a naive datetime (2016-03-04 00:00:00) while time zone support is active.

I personally like the solution using the parser module, which is the second Answer to this question and is beautiful, as you don't have to construct any string literals to get it working. However, one downside is that it is 90% slower than the accepted answer with strptime.

from dateutil import parser
from datetime import datetime
import timeit

def dt():
 dt = parser.parse("Jun 1 2005 1:33PM")
def strptime():
 datetime_object = datetime.strptime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p')

print(timeit.timeit(stmt=dt, number=10**5))
print(timeit.timeit(stmt=strptime, number=10**5))
>10.70296801342902
>1.3627995655316933

As long as you are not doing this a million times over and over again, I still think the parser method is more convenient and will handle most of the time formats automatically.

In [34]: import datetime

In [35]: _now = datetime.datetime.now()

In [36]: _now
Out[36]: datetime.datetime(2016, 1, 19, 9, 47, 0, 432000)

In [37]: print _now
2016-01-19 09:47:00.432000

In [38]: _parsed = datetime.datetime.strptime(str(_now),"%Y-%m-%d %H:%M:%S.%f")

In [39]: _parsed
Out[39]: datetime.datetime(2016, 1, 19, 9, 47, 0, 432000)

In [40]: assert _now == _parsed

Create a small utility function like:

def date(datestr="", format="%Y-%m-%d"):
 from datetime import datetime
 if not datestr:
 return datetime.today().date()
 return datetime.strptime(datestr, format).date()

This is versatile enough:

• If you don't pass any arguments it will return today's date.


• There's a date format as default that you can override.


• You can easily modify it to return a datetime.

The datetime Python module is good for getting date time and converting date time formats.

import datetime

new_date_format1 = datetime.datetime.strptime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p')
new_date_format2 = datetime.datetime.strptime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p').strftime('%Y/%m/%d %I:%M%p')
print new_date_format1
print new_date_format2

Output:

2005-06-01 13:33:00
2005/06/01 01:33PM

arrow offers many useful functions for dates and times. This bit of code provides an answer to the question and shows that arrow is also capable of formatting dates easily and displaying information for other locales.

>>> import arrow
>>> dateStrings = [ 'Jun 1 2005 1:33PM', 'Aug 28 1999 12:00AM' ]
>>> for dateString in dateStrings:
... dateString
... arrow.get(dateString.replace(' ',' '), 'MMM D YYYY H:mmA').datetime
... arrow.get(dateString.replace(' ',' '), 'MMM D YYYY H:mmA').format('ddd, Do MMM YYYY HH:mm')
... arrow.get(dateString.replace(' ',' '), 'MMM D YYYY H:mmA').humanize(locale='de')
...
'Jun 1 2005 1:33PM'
datetime.datetime(2005, 6, 1, 13, 33, tzinfo=tzutc())
'Wed, 1st Jun 2005 13:33'
'vor 11 Jahren'
'Aug 28 1999 12:00AM'
datetime.datetime(1999, 8, 28, 0, 0, tzinfo=tzutc())
'Sat, 28th Aug 1999 00:00'
'vor 17 Jahren'

See http://arrow.readthedocs.io/en/latest/ for more.

for unix / mysql format 2018-10-15 20:59:29

from datetime import datetime

datetime_object = datetime.strptime('2018-10-15 20:59:29', '%Y-%m-%d %H:%M:%S')

You can use easy_date to make it easy:

import date_converter
converted_date = date_converter.string_to_datetime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p')

If you want only date format then you can manually convert it by passing your individual fields like:

>>> import datetime
>>> date = datetime.date(int('2017'),int('12'),int('21'))
>>> date
datetime.date(2017, 12, 21)
>>> type(date)
<type 'datetime.date'>

You can pass your split string values to convert it into date type like:

selected_month_rec = '2017-09-01'
date_formate = datetime.date(int(selected_month_rec.split('-')[0]),int(selected_month_rec.split('-')[1]),int(selected_month_rec.split('-')[2]))

You will get the resulting value in date format.

It would do the helpful for converting string to datetime and also with time zone

def convert_string_to_time(date_string, timezone):
 from datetime import datetime
 import pytz
 date_time_obj = datetime.strptime(date_string[:26], '%Y-%m-%d %H:%M:%S.%f')
 date_time_obj_timezone = pytz.timezone(timezone).localize(date_time_obj)

 return date_time_obj_timezone

date = '2018-08-14 13:09:24.543953+00:00'
TIME_ZONE = 'UTC'
date_time_obj_timezone = convert_string_to_time(date, TIME_ZONE)

See my answer.

In real-world data this is a real problem: multiple, mismatched, incomplete, inconsistent and multilanguage/region date formats, often mixed freely in one dataset. It's not ok for production code to fail, let alone go exception-happy like a fox.

We need to try...catch multiple datetime formats fmt1,fmt2,...,fmtn and suppress/handle the exceptions (from strptime()) for all those that mismatch (and in particular, avoid needing a yukky n-deep indented ladder of try..catch clauses). From my solution

def try_strptime(s, fmts=['%d-%b-%y','%m/%d/%Y']):
 for fmt in fmts:
 try:
 return datetime.strptime(s, fmt)
 except:
 continue

 return None # or reraise the ValueError if no format matched, if you prefer