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Iterating through a range of dates in Python

I have the following code to do this, but how can I do it better? Right now I think it's better than nested loops, but it starts to get Perl-one-linerish when you have a generator in a list comprehension.

day_count = (end_date - start_date).days + 1
for single_date in [d for d in (start_date + timedelta(n) for n in range(day_count)) if d <= end_date]:
    print strftime("%Y-%m-%d", single_date.timetuple())

Notes

  • I'm not actually using this to print. That's just for demo purposes.
  • The start_date and end_date variables are datetime.date objects because I don't need the timestamps. (They're going to be used to generate a report).

Sample Output

For a start date of 2009-05-30 and an end date of 2009-06-09:

2009-05-30
2009-05-31
2009-06-01
2009-06-02
2009-06-03
2009-06-04
2009-06-05
2009-06-06
2009-06-07
2009-06-08
2009-06-09
like image 221
ShawnMilo Avatar asked Jun 29 '09 20:06

ShawnMilo


People also ask

How do I iterate through a date range in Python?

We can use the date_range() function method that is available in pandas. It is used to return a fixed frequency DatetimeIndex. We can iterate to get the date using date() function.

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Method 2: rrule rrule is a package present in dateutil library and this package consists of a method also rrule which takes dtstart, until and specific time period as parameters which are start date, end date, and time period based on iteration respectively. Specific time periods are WEEKLY, MONTHLY, YEARLY, etc.


4 Answers

Why are there two nested iterations? For me it produces the same list of data with only one iteration:

for single_date in (start_date + timedelta(n) for n in range(day_count)):
    print ...

And no list gets stored, only one generator is iterated over. Also the "if" in the generator seems to be unnecessary.

After all, a linear sequence should only require one iterator, not two.

Update after discussion with John Machin:

Maybe the most elegant solution is using a generator function to completely hide/abstract the iteration over the range of dates:

from datetime import date, timedelta

def daterange(start_date, end_date):
    for n in range(int((end_date - start_date).days)):
        yield start_date + timedelta(n)

start_date = date(2013, 1, 1)
end_date = date(2015, 6, 2)
for single_date in daterange(start_date, end_date):
    print(single_date.strftime("%Y-%m-%d"))

NB: For consistency with the built-in range() function this iteration stops before reaching the end_date. So for inclusive iteration use the next day, as you would with range().

like image 111
Ber Avatar answered Oct 23 '22 20:10

Ber


This might be more clear:

from datetime import date, timedelta

start_date = date(2019, 1, 1)
end_date = date(2020, 1, 1)
delta = timedelta(days=1)
while start_date <= end_date:
    print(start_date.strftime("%Y-%m-%d"))
    start_date += delta
like image 37
Sean Cavanagh Avatar answered Oct 23 '22 19:10

Sean Cavanagh


Use the dateutil library:

from datetime import date
from dateutil.rrule import rrule, DAILY

a = date(2009, 5, 30)
b = date(2009, 6, 9)

for dt in rrule(DAILY, dtstart=a, until=b):
    print dt.strftime("%Y-%m-%d")

This python library has many more advanced features, some very useful, like relative deltas—and is implemented as a single file (module) that's easily included into a project.

like image 192
nosklo Avatar answered Oct 23 '22 19:10

nosklo


Pandas is great for time series in general, and has direct support for date ranges.

import pandas as pd
daterange = pd.date_range(start_date, end_date)

You can then loop over the daterange to print the date:

for single_date in daterange:
    print (single_date.strftime("%Y-%m-%d"))

It also has lots of options to make life easier. For example if you only wanted weekdays, you would just swap in bdate_range. See http://pandas.pydata.org/pandas-docs/stable/timeseries.html#generating-ranges-of-timestamps

The power of Pandas is really its dataframes, which support vectorized operations (much like numpy) that make operations across large quantities of data very fast and easy.

EDIT: You could also completely skip the for loop and just print it directly, which is easier and more efficient:

print(daterange)
like image 115
fantabolous Avatar answered Oct 23 '22 21:10

fantabolous