Skip to main content

DateTimeRange is a Python library to handle a time range. e.g. check whether a time is within the time range, get the intersection of time ranges, truncate a time range, iterate through a time range, and so forth.

Project description

Summary

DateTimeRange is a Python library to handle a time range. e.g. check whether a time is within the time range, get the intersection of time ranges, truncate a time range, iterate through a time range, and so forth.

PyPI package version conda-forge package version Supported Python versions Test result of Linux/macOS/Windows Test coverage CodeQL GitHub stars

Examples

Create a DateTimeRange instance from start and end datetime

Sample Code:
from datetimerange import DateTimeRange
time_range = DateTimeRange("2015-03-22T10:00:00+0900", "2015-03-22T10:10:00+0900")
str(time_range)
Output:
'2015-03-22T10:00:00+0900 - 2015-03-22T10:10:00+0900'

Create a DateTimeRange instance from a range text

Sample Code:
from datetimerange import DateTimeRange
time_range = DateTimeRange.from_range_text("2015-03-22T10:00:00+0900 - 2015-03-22T10:10:00+0900")
str(time_range)
Output:
'2015-03-22T10:00:00+0900 - 2015-03-22T10:10:00+0900'

Get an iterator

Sample Code 1:
import datetime
from datetimerange import DateTimeRange

time_range = DateTimeRange("2015-01-01T00:00:00+0900", "2015-01-04T00:00:00+0900")
for value in time_range.range(datetime.timedelta(days=1)):
    print(value)
Output 1:
2015-01-01 00:00:00+09:00
2015-01-02 00:00:00+09:00
2015-01-03 00:00:00+09:00
2015-01-04 00:00:00+09:00
Sample Code 2:
from datetimerange import DateTimeRange
from dateutil.relativedelta import relativedelta

time_range = DateTimeRange("2015-01-01T00:00:00+0900", "2016-01-01T00:00:00+0900")
for value in time_range.range(relativedelta(months=+4)):
    print(value)
Output 2:
2015-01-01 00:00:00+09:00
2015-05-01 00:00:00+09:00
2015-09-01 00:00:00+09:00
2016-01-01 00:00:00+09:00

Test whether a value within the time range

Sample Code:
from datetimerange import DateTimeRange

time_range = DateTimeRange("2015-03-22T10:00:00+0900", "2015-03-22T10:10:00+0900")
print("2015-03-22T10:05:00+0900" in time_range)
print("2015-03-22T10:15:00+0900" in time_range)

time_range_smaller = DateTimeRange("2015-03-22T10:03:00+0900", "2015-03-22T10:07:00+0900")
print(time_range_smaller in time_range)
Output:
True
False
True

Test whether a value intersects the time range

Sample Code:
from datetimerange import DateTimeRange
time_range = DateTimeRange("2015-03-22T10:00:00+0900", "2015-03-22T10:10:00+0900")
x = DateTimeRange("2015-03-22T10:05:00+0900", "2015-03-22T10:15:00+0900")
time_range.is_intersection(x)
Output:
True

Make an intersected time range

Sample Code:
from datetimerange import DateTimeRange
time_range = DateTimeRange("2015-03-22T10:00:00+0900", "2015-03-22T10:10:00+0900")
x = DateTimeRange("2015-03-22T10:05:00+0900", "2015-03-22T10:15:00+0900")
time_range.intersection(x)
Output:
2015-03-22T10:05:00+0900 - 2015-03-22T10:10:00+0900

Make an encompassed time range

Sample Code:
from datetimerange import DateTimeRange
time_range = DateTimeRange("2015-03-22T10:00:00+0900", "2015-03-22T10:10:00+0900")
x = DateTimeRange("2015-03-22T10:05:00+0900", "2015-03-22T10:15:00+0900")
time_range.encompass(x)
Output:
2015-03-22T10:00:00+0900 - 2015-03-22T10:15:00+0900

Truncate time range

Sample Code:
from datetimerange import DateTimeRange

time_range = DateTimeRange("2015-03-22T10:00:00+0900", "2015-03-22T10:10:00+0900")
time_range.is_output_elapse = True
print("before truncate: ", time_range)

time_range.truncate(10)
print("after truncate:  ", time_range)
Output:
before truncate:  2015-03-22T10:00:00+0900 - 2015-03-22T10:10:00+0900 (0:10:00)
after truncate:   2015-03-22T10:00:30+0900 - 2015-03-22T10:09:30+0900 (0:09:00)

For more information

More examples are available at https://datetimerange.rtfd.io/en/latest/pages/examples/index.html

Examples with Jupyter Notebook are also available at DateTimeRange.ipynb

Installation

Installation: pip

pip install DateTimeRange

Installation: conda

conda install -c conda-forge datetimerange

Dependencies

Documentation

https://datetimerange.rtfd.io/

Sponsors

Dmitry Belyaev (b4tman) Charles Becker (chasbecker) Arturi0

Become a sponsor

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DateTimeRange-2.0.0.tar.gz (14.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

DateTimeRange-2.0.0-py3-none-any.whl (8.9 kB view details)

Uploaded Python 3

File details

Details for the file DateTimeRange-2.0.0.tar.gz.

File metadata

  • Download URL: DateTimeRange-2.0.0.tar.gz
  • Upload date:
  • Size: 14.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.9

File hashes

Hashes for DateTimeRange-2.0.0.tar.gz
Algorithm Hash digest
SHA256 2aa7bc652ed2dbe0750860c564a79f930c6e3337f937eeee428884130aeff262
MD5 4e1bcd5dcc47876a2321566296d0303d
BLAKE2b-256 7083c8ce0fd619ed0d692762ea095e3bcba42f997bf08384cc37dd58b19048bc

See more details on using hashes here.

File details

Details for the file DateTimeRange-2.0.0-py3-none-any.whl.

File metadata

  • Download URL: DateTimeRange-2.0.0-py3-none-any.whl
  • Upload date:
  • Size: 8.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.9

File hashes

Hashes for DateTimeRange-2.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 11cdf58f8bf0acc1969eb525cab88c0e7f68e0f9e1ee69e651be38e6ecdd0dbb
MD5 ce50f6e3740dc53c5d4ed9a2f96698ca
BLAKE2b-256 b472b32611afebc95626f59100278a6110a1f2169764436c1e3fa517653f94ab

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page