Date and Time Utilities#

The pyinterp.dateutils module provides a set of utility functions for working with dates and times in NumPy arrays. These functions are designed to be fast and efficient, making it easy to perform common date and time calculations.

This example will walk you through the various functions available in the pyinterp.dateutils module.

Generating Sample Data#

First, let’s create a set of random dates that we can use to demonstrate the functionality of the dateutils module.

import datetime
import random

import numpy

import pyinterp


def make_date(samples: int = 10) -> numpy.ndarray:
    """Generate 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()
print("Sample dates:")
print(dates)
Sample dates:
['1973-08-07T14:59:56.293246000' '1976-01-12T18:32:41.054560000'
 '1979-03-15T22:33:03.822478000' '2002-05-24T14:05:54.794883000'
 '2016-07-01T16:44:52.396694000' '2013-08-23T00:20:23.289158000'
 '1993-03-19T00:49:44.751458000' '1999-12-22T11:42:08.064675000'
 '1988-10-09T21:19:07.400945000' '1984-04-20T18:28:31.620244000']

Extracting Date Components#

You can extract the date components (year, month, and day) from a NumPy array of dates using the pyinterp.dateutils.date function. This returns a structured NumPy array.

date_components = pyinterp.dateutils.date(dates)
print("Date components:")
print(date_components)
Date components:
(array([1973, 1976, 1979, 2002, 2016, 2013, 1993, 1999, 1988, 1984],
      dtype=int32), array([ 8,  1,  3,  5,  7,  8,  3, 12, 10,  4], dtype=uint8), array([ 7, 12, 15, 24,  1, 23, 19, 22,  9, 20], dtype=uint8))

Extracting Time Components#

Similarly, you can extract the time components (hour, minute, and second) using the pyinterp.dateutils.time function.

time_components = pyinterp.dateutils.time(dates)
print("Time components:")
print(time_components)
Time components:
(array([14, 18, 22, 14, 16,  0,  0, 11, 21, 18], dtype=uint8), array([59, 32, 33,  5, 44, 20, 49, 42, 19, 28], dtype=uint8), array([56, 41,  3, 54, 52, 23, 44,  8,  7, 31], dtype=uint8))

ISO Calendar Information#

The pyinterp.dateutils.isocalendar function returns the ISO calendar information (year, week number, and weekday) for each date.

iso_calendar = pyinterp.dateutils.isocalendar(dates)
print("ISO calendar:")
print(iso_calendar)
ISO calendar:
(array([1973, 1976, 1979, 2002, 2016, 2013, 1993, 1999, 1988, 1984],
      dtype=int32), array([32,  3, 11, 21, 26, 34, 11, 51, 40, 16], dtype=uint8), array([2, 1, 4, 5, 5, 5, 5, 3, 7, 5], dtype=uint8))

Weekday#

You can get the day of the week (where Sunday is 0 and Saturday is 6) using the pyinterp.dateutils.weekday function.

weekday = pyinterp.dateutils.weekday(dates)
print("Weekday (Sunday=0):")
print(weekday)
Weekday (Sunday=0):
[2 1 4 5 5 5 5 3 0 5]

Time Since January 1st#

The pyinterp.dateutils.timedelta_since_january function calculates the time difference between each date and the first day of its corresponding year.

timedelta = pyinterp.dateutils.timedelta_since_january(dates)
print("Time since January 1st:")
print(timedelta)
Time since January 1st:
[18889196293246000  1017161054560000  6388383822478000 12405954794883000
 15785092396694000 20218823289158000  6655784751458000 30714128064675000
 24441547400945000  9570511620244000]

Total running time of the script: (0 minutes 0.003 seconds)

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