Numpy date utilities#

This library provides utility functions to perform conversions and get information about numpy dates quickly.

import datetime
import random

import numpy

import pyinterp


def make_date(samples=10000):
    """Generates random dates."""
    epoch = datetime.datetime(1970, 1, 1)
    delta = datetime.datetime.now() - datetime.datetime(1970, 1, 1)

    pydates = [epoch + random.random() * delta for _ in range(samples)]
    npdates = numpy.array(pydates).astype('datetime64[ns]')

    return npdates
dates = make_date()
dates
array(['1981-06-22T21:20:18.214385000', '2008-11-22T13:16:05.184959000',
       '1975-05-08T08:06:50.950819000', ...,
       '2014-07-09T21:16:17.339595000', '1994-12-06T07:05:40.230832000',
       '1987-10-29T14:14:00.179224000'], dtype='datetime64[ns]')

Get the date part as a structured numpy array of three fields: year, month and day:

pyinterp.dateutils.date(dates)
array([(1981,  6, 22), (2008, 11, 22), (1975,  5,  8), ...,
       (2014,  7,  9), (1994, 12,  6), (1987, 10, 29)],
      dtype=[('year', '<i4'), ('month', '<u4'), ('day', '<u4')])

Get the time part as a structured numpy array of three fields: hour, minute and second:

pyinterp.dateutils.time(dates)
array([(21, 20, 18), (13, 16,  5), ( 8,  6, 50), ..., (21, 16, 17),
       ( 7,  5, 40), (14, 14,  0)],
      dtype=[('hour', '<u4'), ('minute', '<u4'), ('second', '<u4')])

Get the ISO calendar of the date as a structured numpy array of three fields: year, weekday and week:

pyinterp.dateutils.isocalendar(dates)
array([(1981, 26, 1), (2008, 47, 6), (1975, 19, 4), ..., (2014, 28, 3),
       (1994, 49, 2), (1987, 44, 4)],
      dtype=[('year', '<i4'), ('week', '<u4'), ('weekday', '<u4')])

Get the week day of the dates (Sunday is 0 … Saturday is 6):

pyinterp.dateutils.weekday(dates)
array([1, 6, 4, ..., 3, 2, 4], dtype=uint32)

Get the timedelta from since January

pyinterp.dateutils.timedelta_since_january(dates)
array([14937618214385000, 28214165184959000, 11002010950819000, ...,
       16406177339595000, 29315140230832000, 26057640179224000],
      dtype='timedelta64[ns]')

Get the dates as datetime.datetime array

pyinterp.dateutils.datetime(dates)
array([datetime.datetime(1981, 6, 22, 21, 20, 18, 214385),
       datetime.datetime(2008, 11, 22, 13, 16, 5, 184959),
       datetime.datetime(1975, 5, 8, 8, 6, 50, 950819), ...,
       datetime.datetime(2014, 7, 9, 21, 16, 17, 339595),
       datetime.datetime(1994, 12, 6, 7, 5, 40, 230832),
       datetime.datetime(1987, 10, 29, 14, 14, 0, 179224)], dtype=object)

Total running time of the script: (0 minutes 0.041 seconds)

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