Get fiscal year based on current timestamp-python

Question

I am trying get the start date of the financial year based on today’s date.

So after a little research, I found this package called fiscalyear where you can modify the start date of the fiscal year. In my case i wanted 01-07-year to be the start date of my fiscal year so i set fiscalyear.START_MONTH = 7

I have tried the below(reproducible example if you pip install fiscalyear):

import datetime
import fiscalyear
fiscalyear.START_MONTH = 7
a = fiscalyear.FiscalYear(datetime.datetime.now().year).start.date()
a.strftime('%Y-%m-%d')

Which outputs correctly:

'2018-07-01'

However, this would not work when the month turns to August, since the datetime.datetime.now().year doesnot change. So i tried doing something like:

if (datetime.datetime.now()-pd.to_datetime('2018-07-01')).days < 365:
    a = fiscalyear.FiscalYear(datetime.datetime.now().year).start.date()
    print(a.strftime('%Y-%m-%d'))
else:
    a = fiscalyear.FiscalYear(datetime.datetime.now().year+1).start.date()
    print(a.strftime('%Y-%m-%d'))

I have a bad feeling about what I am doing since this might now work for leap years too.

Is there some better way to do this in python which will detect the start date of the fiscal year based on current timestamp?

py version: 3.6.7

Asked By: anky

||

Source

Answer 1

I think you need searchsorted with helper DatetimeIndex:

r = pd.to_datetime([f'{x}-06-30' for x in range(1970, 2021)])
#print (r)

for x in ['2017-07-01','2017-07-02','2018-06-30','2019-02-19','2019-08-19']:
    out = (r[r.searchsorted(pd.Timestamp(x))] + pd.Timedelta(1, 'd')).year
    print (out)
2018
2018
2018
2019
2020

Answered By: jezrael

Answer 2

Taking a sample dataframe:

pd.DataFrame(dict(
    dates=[pd.datetime(2018, 6, 1), pd.datetime(2018, 7, 1), pd.datetime(2018, 7, 2)],
    values=[0]*3
))

       dates  values
0 2018-06-01       0
1 2018-07-01       0
2 2018-07-02       0

… I have used pd.Grouper() to group these down to date starting July 1st, where the key is AS-JUL i.e. ‘annual-starting July’

df.groupby(pd.Grouper(freq='AS-JUL', key='dates')).count()
            values
            values
dates             
2017-07-01       1
2018-07-01       2

You can see here that 2018-07-01 remains as 2018-07-01 after the operation

Answered By: Dillon

Answer 3

My knowledge in the fiscal area is somewhere close to Zero, but according to [ReadTheDocs.FiscalYear]: Basic Usage:

The FiscalYear class provides an object for storing information about the start and end of a particular fiscal year.

…

The start and end of each of the above objects are stored as instances of the FiscalDateTime class. This class provides all of the same features as the datetime class, with the addition of the ability to query the fiscal year, fiscal quarter, fiscal month, and fiscal day.

So, FiscalYear isn’t to be used with dates, but FiscalDateTime (or its simpler sibling: FiscalDate) instead.

>>> import fiscalyear
>>> fiscalyear.START_MONTH = 7
>>>
>>> cur_y = fiscalyear.FiscalYear(datetime.datetime.now().year)
>>> cur_y.start.date()
datetime.date(2018, 7, 1)
>>> cur_y.end.date()
datetime.date(2019, 6, 30)
>>>
>>> cur_dt = fiscalyear.FiscalDate(2019, 2, 19)  # Current date (at answer time)
>>> cur_dt.fiscal_year
2019
>>>
>>> jul_dt = fiscalyear.FiscalDate(2019, 7, 19)  # A date past July 1st (when the fiscal year should change)
>>> jul_dt.fiscal_year
2020

Answered By: CristiFati

Answer 4

You can try following code, It worked for me:

>>> import fiscalyear
>>> fiscalyear.START_MONTH = 4
>>> fiscalyear.FiscalYear.current()
FiscalYear(2021)
>>>

Answered By: Vinod Singh

Get fiscal year based on current timestamp-python

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