Convert string "Jun 1 2005 1:33PM" into datetime

datetime.strptime parses an input string in the user-specified format into a timezone-naive datetime object:

>>> from datetime import datetime
>>> datetime.strptime('Jun 1 2005  1:33PM', '%b %d %Y %I:%M%p')
datetime.datetime(2005, 6, 1, 13, 33)

To obtain a date object using an existing datetime object, convert it using .date():

>>> datetime.strptime('Jun 1 2005', '%b %d %Y').date()
date(2005, 6, 1)

Links:

• strptime docs: Python 2, Python 3

• strptime/strftime format string docs: Python 2, Python 3

• strftime.org format string cheatsheet

Notes:

• strptime = "string parse time"
• strftime = "string format time"

Use the third-party dateutil library:

from dateutil import parser
parser.parse("Aug 28 1999 12:00AM")  # datetime.datetime(1999, 8, 28, 0, 0)

It can handle most date formats and is more convenient than strptime since it usually guesses the correct format. It is also very useful for writing tests, where readability is more important than performance.

Install it with:

pip install python-dateutil

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

$ python
>>> import time
>>> my_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)

timestamp = time.mktime(my_time)
# convert time object to datetime
from datetime import datetime
my_datetime = datetime.fromtimestamp(timestamp)
# convert time object to date
from datetime import date
my_date = date.fromtimestamp(timestamp)

Python >= 3.7

To convert a YYYY-MM-DD string to a datetime object, datetime.fromisoformat could be used.

from datetime import datetime

date_string = "2012-12-12 10:10:10"
print (datetime.fromisoformat(date_string))
2012-12-12 10:10:10

Caution from the documentation:

This does not support parsing arbitrary ISO 8601 strings - it is only intended as the inverse operation of datetime.isoformat(). A more full-featured ISO 8601 parser, dateutil.parser.isoparse is available in the third-party package dateutil.

If your string is in ISO 8601 format and you have Python 3.7+, you can use the following simple code:

import datetime

aDate = datetime.date.fromisoformat('2020-10-04')

for dates and

import datetime

aDateTime = datetime.datetime.fromisoformat('2020-10-04 22:47:00')

for strings containing date and time. If timestamps are included, the function datetime.datetime.isoformat() supports the following format:

YYYY-MM-DD[*HH[:MM[:SS[.fff[fff]]]][+HH:MM[:SS[.ffffff]]]]

Where * matches any single character. See also here and here.

This would be helpful for converting a string to datetime and also with a 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)

You can also check out dateparser:

dateparser provides modules to easily parse localized dates in almost any string formats commonly found on web pages.

Install:

pip install dateparser

This is, I think, the easiest way you can parse dates.

The most straightforward way is to use the dateparser.parse function, that wraps around most of the functionality in the module.

Sample code:

import dateparser

t1 = 'Jun 1 2005  1:33PM'
t2 = 'Aug 28 1999 12:00AM'

dt1 = dateparser.parse(t1)
dt2 = dateparser.parse(t2)

print(dt1)
print(dt2)

Output:

2005-06-01 13:33:00
1999-08-28 00:00:00

Similar to Javed's answer, I just wanted date from string - so combining Simon's and Javed's logic, we get:

from dateutil import parser
import datetime

s = '2021-03-04'

parser.parse(s).date()

Output

datetime.date(2021, 3, 4)

It seems using pandas Timestamp is the fastest:

import pandas as pd

N = 1000

l = ['Jun 1 2005  1:33PM'] * N

list(pd.to_datetime(l, format=format))

%timeit _ = list(pd.to_datetime(l, format=format))
1.58 ms ± 21.6 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

Other solutions

from datetime import datetime
%timeit _ = list(map(lambda x: datetime.strptime(x, format), l))
9.41 ms ± 95.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

from dateutil.parser import parse
%timeit _ = list(map(lambda x: parse(x), l))
73.8 ms ± 1.14 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

If the string is an ISO 8601 string, please use csio8601:

import ciso8601

l = ['2014-01-09'] * N

%timeit _ = list(map(lambda x: ciso8601.parse_datetime(x), l))
186 µs ± 4.13 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

If you don't want to explicitly specify which format your string is in with respect to the date time format, you can use this hack to by pass that step:

from dateutil.parser import parse

# Function that'll guess the format and convert it into the python datetime format
def update_event(start_datetime=None, end_datetime=None, description=None):
    if start_datetime is not None:
        new_start_time = parse(start_datetime)

        return new_start_time

# Sample input dates in different formats
d = ['06/07/2021 06:40:23.277000', '06/07/2021 06:40', '06/07/2021']

new = [update_event(i) for i in d]

for date in new:
    print(date)
    # Sample output dates in Python datetime object
    #   2014-04-23 00:00:00
    #   2013-04-24 00:00:00
    #   2014-04-25 00:00:00

If you want to convert it into some other datetime format, just modify the last line with the format you like for example something like date.strftime('%Y/%m/%d %H:%M:%S.%f'):

from dateutil.parser import parse

def update_event(start_datetime=None, end_datetime=None, description=None):
    if start_datetime is not None:
        new_start_time = parse(start_datetime)

        return new_start_time

# Sample input dates in different formats
d = ['06/07/2021 06:40:23.277000', '06/07/2021 06:40', '06/07/2021']

# Passing the dates one by one through the function
new = [update_event(i) for i in d]

for date in new:
    print(date.strftime('%Y/%m/%d %H:%M:%S.%f'))
    # Sample output dates in required Python datetime object
    #   2021/06/07 06:40:23.277000
    #   2021/06/07 06:40:00.000000
    #   2021/06/07 00:00:00.000000

Try running the above snippet to have a better clarity.

Use:

emp = pd.read_csv("C:\\py\\programs\\pandas_2\\pandas\\employees.csv")
emp.info()

It shows "Start Date Time" Column and "Last Login Time" both are "object = strings" in data-frame:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1000 entries, 0 to 999
Data columns (total 8 columns):
First Name           933 non-null object
Gender               855 non-null object

    Start Date           1000 non-null object

    Last Login Time      1000 non-null object

Salary               1000 non-null int64
Bonus %              1000 non-null float64
Senior Management    933 non-null object
Team                 957 non-null object
dtypes: float64(1), int64(1), object(6)
memory usage: 62.6+ KB

By using the parse_dates option in read_csv mention, you can convert your string datetime into the pandas datetime format.

emp = pd.read_csv("C:\\py\\programs\\pandas_2\\pandas\\employees.csv", parse_dates=["Start Date", "Last Login Time"])
emp.info()

Output:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1000 entries, 0 to 999
Data columns (total 8 columns):
First Name           933 non-null object
Gender               855 non-null object

     Start Date           1000 non-null datetime64[ns]
     Last Login Time      1000 non-null datetime64[ns]

Salary               1000 non-null int64
Bonus %              1000 non-null float64
Senior Management    933 non-null object
Team                 957 non-null object
dtypes: datetime64[ns](2), float64(1), int64(1), object(4)
memory usage: 62.6+ KB

A short sample mapping a yyyy-mm-dd date string to a datetime.date object:

from datetime import date
date_from_yyyy_mm_dd = lambda δ : date(*[int(_) for _ in δ.split('-')])
date_object = date_from_yyyy_mm_dd('2021-02-15')