Python playing with dates

18.04.2020 — python, pandas — 1 min read

I have a problem, which is trying to get a next available date from within list of dates. This list of dates contains dates which are not saturday/sunday or any public holiday. My inputs will be like, what was the first available date in last 180 days, plan is to build a function like below,

1d = current date - interval 180 days
2d = get_next_available_date(d)

Breaking down the problem

Get next available from any list of dates
Create function from point(1) solution to solve problem

1. Get next available from any list of dates

Initializations

1# Initializing full feb dates
2test_dates = ['01-02-2020', '02-02-2020', '03-02-2020', '04-02-2020', '05-02-2020',
3 '06-02-2020', '07-02-2020', '08-02-2020', '09-02-2020', '10-02-2020', '11-02-2020',
4 '12-02-2020', '13-02-2020', '14-02-2020', '15-02-2020', '16-02-2020', '17-02-2020',
5 '18-02-2020', '19-02-2020', '20-02-2020', '21-02-2020', '22-02-2020', '23-02-2020',
6 '24-02-2020', '25-02-2020', '26-02-2020', '27-02-2020', '28-02-2020', '29-02-2020']

Remove a week from feb between 09/02/2020 - 15/02/2020

1del test_dates[8:15]

After removing a week data looks like this

1print(test_dates)
2
3#Output:
4
5['01-02-2020', '02-02-2020', '03-02-2020', '04-02-2020',
6 '05-02-2020', '06-02-2020', '07-02-2020', '08-02-2020', '16-02-2020', '17-02-2020',
7 '18-02-2020', '19-02-2020', '20-02-2020', '21-02-2020', '22-02-2020', '23-02-2020',
8 '24-02-2020', '25-02-2020', '26-02-2020', '27-02-2020', '28-02-2020', '29-02-2020']

Converts string to datetime format

1get_datetime = lambda s: dt.datetime.strptime(s, '%d-%m-%Y')

Main logic to get the next available date

1base_date = '10-02-2020'
2base = get_datetime(base_date)
3
4# Converting all the dates to datetime format
5availdates = list(map(lambda d: get_datetime(d), test_dates))
6print('\n Base date =',base, 'Type =',type(base))
7print('\n Available dates =\n',availdates, 'Type =',type(availdates), 'Element Type =', type(availdates[0]))
8
9# Filtering the dates greater than base date
10later = filter(lambda d: d > base, availdates)
11
12# Finding the minimum date among the dates greater than base date
13closest_date = min(later)
14print('\n Next available date =',closest_date, 'Type =',type(closest_date))
15print('\n Next available date =',closest_date.strftime("%Y-%m-%d"), 'Type =',type(closest_date.strftime("%Y-%m-%d")))

Output:

1test_dates after removing a week = 
2 ['01-02-2020', '02-02-2020', '03-02-2020', '04-02-2020', '05-02-2020', '06-02-2020', '07-02-2020', '08-02-2020', '16-02-2020', '17-02-2020', '18-02-2020', '19-02-2020', '20-02-2020', '21-02-2020', '22-02-2020', '23-02-2020', '24-02-2020', '25-02-2020', '26-02-2020', '27-02-2020', '28-02-2020', '29-02-2020']
3
4 Base date = 2020-02-10 00:00:00 Type = <class 'datetime.datetime'>
5
6 Available dates =
7 [datetime.datetime(2020, 2, 1, 0, 0), datetime.datetime(2020, 2, 2, 0, 0), datetime.datetime(2020, 2, 3, 0, 0), datetime.datetime(2020, 2, 4, 0, 0), datetime.datetime(2020, 2, 5, 0, 0), datetime.datetime(2020, 2, 6, 0, 0), datetime.datetime(2020, 2, 7, 0, 0), datetime.datetime(2020, 2, 8, 0, 0), datetime.datetime(2020, 2, 16, 0, 0), datetime.datetime(2020, 2, 17, 0, 0), datetime.datetime(2020, 2, 18, 0, 0), datetime.datetime(2020, 2, 19, 0, 0), datetime.datetime(2020, 2, 20, 0, 0), datetime.datetime(2020, 2, 21, 0, 0), datetime.datetime(2020, 2, 22, 0, 0), datetime.datetime(2020, 2, 23, 0, 0), datetime.datetime(2020, 2, 24, 0, 0), datetime.datetime(2020, 2, 25, 0, 0), datetime.datetime(2020, 2, 26, 0, 0), datetime.datetime(2020, 2, 27, 0, 0), datetime.datetime(2020, 2, 28, 0, 0), datetime.datetime(2020, 2, 29, 0, 0)] Type = <class 'list'> Element Type = <class 'datetime.datetime'>
8
9 Next available date = 2020-02-16 00:00:00 Type = <class 'datetime.datetime'>
10
11 Next available date = 2020-02-16 Type = <class 'str'>

2. Create function from point(1) solution to solve problem

Difference between .today() & .now()

.today()
Returns the current local datetime, without tzinfo

1dt.datetime.today()        # datetime.datetime(2020, 4, 19, 11, 58, 28, 547738)
2print(dt.datetime.today()) # 2020-04-19 11:58:28.831696

.now()
Return the current local date and time. If optional argument tz is None or not specified, this is like today(), but, if possible, supplies more precision

1dt.datetime.now()          # datetime.datetime(2020, 4, 19, 11, 58, 28, 335700)
2print(dt.datetime.now())   # 2020-04-19 11:58:28.830691

Making .now() timezone aware you will have to use import pytz

1import pytz
2d = dt.datetime.now()
3timezone = pytz.timezone('Asia/Calcutta')
4d_aware = timezone.localize(d)
5d_aware.tzinfo
6
7#Output:
8#<DstTzInfo 'Asia/Calcutta' IST+5:30:00 STD>

pytz.all_timezones will list all available timezones

1['Africa/Abidjan',
2...
3'Asia/Calcutta',
4'Asia/Shanghai',
5'Europe/London',
6'America/Los_Angeles',
7'America/New_York',
8...
9 'Zulu']

Above timezone thing, has nothing to do with this article, i just got bit side-tracked.

Below, i am subracting 180 days from current date, that will be the base date or start date.

1base = dt.datetime.today() - dt.timedelta(days=180)
2print('Base Date : ',base)
3#Output:
4#Base Date :  2019-10-22 12:29:19.946372

Now, merging point(1) and timedelta of point(2) to create a new function,

1def get_next_available_date(test_dates, days):
2    base = dt.datetime.today() - dt.timedelta(days=days)
3    print(' Base date =',base, 'Type =',type(base))
4    availdates = list(map(lambda d: get_datetime(d), test_dates))
5    #print('\n Available dates =\n',availdates, 'Type =',type(availdates), 'Element Type =', type(availdates[0]))
6    later = filter(lambda d: d > base, availdates)
7    #closest_date = min(later, key = lambda d: get_datetime(d))
8    closest_date = min(later)
9    print(' Next available date =',closest_date, 'Type =',type(closest_date))
10    closest_date = closest_date.strftime("%Y-%m-%d")
11    return closest_date

Below is the call,

1print('timedelta =',dt.datetime.today() - dt.timedelta(days=69))
2#timedelta = 2020-02-10 12:45:21.150761
3
4print(get_next_available_date(test_dates, 69))
5# Base date = 2020-02-10 12:47:05.276859 Type = <class 'datetime.datetime'>
6# Next available date = 2020-02-16 00:00:00 Type = <class 'datetime.datetime'>
7#2020-02-16

Below is the logic used to generate the dates for initialization,

1start = dt.datetime.strptime("01-02-2020", "%d-%m-%Y")
2end = dt.datetime.strptime("29-02-2020", "%d-%m-%Y")
3date_generated = [start + dt.timedelta(days=x) for x in range(0, (end-start).days+1)]
4
5test_dates = []
6for date in date_generated:
7    test_dates.append(date.strftime("%d-%m-%Y"))

Other concepts used

1. map

map(func, *iterables)

Where func is the function on which each element in iterables (as many as they are) would be applied on.

Example 1

1my_pets = ['alfred', 'tabitha', 'william', 'arla']
2uppered_pets = list(map(str.upper, my_pets))
3print(uppered_pets)
4# Output : ['ALFRED', 'TABITHA', 'WILLIAM', 'ARLA']

Example 2

1circle_areas = [3.56773, 5.57668, 4.00914, 56.24241, 9.01344, 32.00013]
2result = list(map(round, circle_areas, range(1,7)))
3print(result)
4# Output : [3.6, 5.58, 4.009, 56.2424, 9.01344, 32.00013]

Example 3 ( using repeat to have same value repeated for round() )

1circle_areas = [3.56773, 5.57668, 4.00914, 56.24241, 9.01344, 32.00013]
2result = list(map(round, circle_areas, np.repeat(2,6)))
3print(result)
4# Output : [3.57, 5.58, 4.01, 56.24, 9.01, 32.0]

2. filter

filter(func, iterable)

Filter passes each element in the iterable through func and returns only the ones that evaluate to true.

Example 1

1scores = [66, 90, 68, 59, 76, 60, 88, 74, 81, 65]
2def is_A_student(score):
3    return score > 75
4
5over_75 = list(filter(is_A_student, scores))
6print(over_75)
7# Output : [90, 76, 88, 81]

Example 2

1dromes = ("demigod", "rewire", "madam", "freer", "anutforajaroftuna", "kiosk")
2palindromes = list(filter(lambda word: word == word[::-1], dromes))
3print(palindromes)
4# Output : ['madam', 'anutforajaroftuna']