Python generating a list of dates between two dates

I'm surprised this isn't a standard function in datetime package.

Here's a function that does what is requested:

from datetime import timedelta

def date_range_list(start_date, end_date):
    # Return list of datetime.date objects between start_date and end_date (inclusive).
    date_list = []
    curr_date = start_date
    while curr_date <= end_date:
        date_list.append(curr_date)
        curr_date += timedelta(days=1)
    return date_list

Usage:

from datetime import date, timedelta

def date_range_list(start_date, end_date):
    # Return list of datetime.date objects between start_date and end_date (inclusive).
    date_list = []
    curr_date = start_date
    while curr_date <= end_date:
        date_list.append(curr_date)
        curr_date += timedelta(days=1)
    return date_list

start_date = datetime.date(year=2021, month=12, day=20)
stop_date = datetime.date(year=2021, month=12, day=25)
date_list = date_range_list(start_date, stop_date)

date_list

Output:

[datetime.date(2021, 12, 20),
 datetime.date(2021, 12, 21),
 datetime.date(2021, 12, 22),
 datetime.date(2021, 12, 23),
 datetime.date(2021, 12, 24),
 datetime.date(2021, 12, 25)]

Your code rewritten as a list comprehension:

[sdate+timedelta(days=x) for x in range((edate-sdate).days)]

results:

[datetime.date(2019, 3, 22),
 datetime.date(2019, 3, 23),
 datetime.date(2019, 3, 24),
          :
 datetime.date(2019, 4, 7),
 datetime.date(2019, 4, 8)]

from datetime import date, timedelta

sdate = date(2019,3,22)   # start date
edate = date(2019,4,9)   # end date
date_modified=sdate
list=[sdate] 


while date_modified<edate:
    date_modified+=timedelta(days=nbDaysbtw2dates) 
    list.append(date_modified)

print(list) 

You can use pandas.date_range() for this:

import pandas
pandas.date_range(sdate,edate-timedelta(days=1),freq='d')

---

DatetimeIndex(['2019-03-22', '2019-03-23', '2019-03-24', '2019-03-25',
           '2019-03-26', '2019-03-27', '2019-03-28', '2019-03-29',
           '2019-03-30', '2019-03-31', '2019-04-01', '2019-04-02',
           '2019-04-03', '2019-04-04', '2019-04-05', '2019-04-06',
           '2019-04-07', '2019-04-08'],
          dtype='datetime64[ns]', freq='D')