Skip to main content

Build Status PyPI version Supported Python versions

PyTime is an easy-use Python module which aims to operate date/time/datetime by string.

PyTime allows you using nonregular datetime string to generate and calculate datetime at most situation.

It Also provides you some simple useful methods for getting datetime you want.

Install

pip install pytime

Sample Usage

Calculate datetime all by string, accept unit for short or overall length, support out of order or in capital unit:

>>>from pytime import pytime
>>>
>>>pytime.before('2015.5.17', '2years 3mon 23week 3d 2hr')     # 2years 3months 23weeks 3days 2hours before 2015.5.17
datetime.datetime(2012, 9, 5, 22, 0)
>>>
>>>pytime.after(pytime.tomorrow('15.5.17'), '23month3dy29minu')   # 23months 3days 29minutes after 2015-5-17's next day
datetime.datetime(2017, 4, 21, 0, 29)

Parse nonregular datetime string to datetime:

>>>pytime.parse('April 3rd 2015')
datetime.date(2015, 4, 3)
>>>pytime.parse('Oct, 1st. 2015')
datetime.date(2015, 10, 1)
>>>pytime.parse('NOV21th2015')
datetime.date(2015, 11, 21)
>>>
>>>pytime.parse('2015517')
datetime.date(2015, 5, 17)
>>>
>>>pytime.parse('5/17/15')
datetime.date(2015, 5, 17)
>>>
>>>pytime.parse('92-11-2')
datetime.date(1992, 11, 2)
>>>
>>>pytime.parse(1432310400)          # support datetimestamp for all function
datetime.datetime(2015, 5, 23, 0, 0)

Calculate week and month in a easy way. Normally we want to use these binate date in script, from Monday to next Monday which means 00:00:00-23:59:59, and Month from 1st to next 1st in the same way, but if you want clean date interval, you could set pytime.next_week(clean=True) to get the clean date for next week etc.

>>>pytime.this_week()
(datetime.date(2015, 5, 11), datetime.date(2015, 5, 18))

>>>pytime.next_week('2015-6-14')                         # 2015-6-14's next week for script
(datetime.date(2015, 6, 15), datetime.date(2015, 6, 23))

>>>pytime.last_week(pytime.mother(2013), True)           # 2013 Mother's Day's last week
(datetime.date(2013, 5, 13), datetime.date(2013, 5, 20))

>>>pytime.next_month('2015-10-1')
(datetime.date(2015, 11, 1), datetime.date(2015, 12, 1))

Pytime support calculate timedelta by string even between date and datetime, merely set the date to that day’s midnight:

>>>pytime.count('2015-5-17 23:23:23', pytime.tomorrow())
datetime.timedelta(1, 84203)

Get common festivals for designated year:

>>>pytime.father()              # Father's Day
datetime.date(2015, 6, 21)
>>>
>>>pytime.mother(2016)          # 2016 Mother's Day
datetime.date(2016, 5, 8)
>>>
>>>pytime.easter(1999)          # 1999 Easter
datetime.date(1999, 4, 4)
>>>pytime.vatertag(2020)        # Fater's Day in Germany
datetime.date(2020, 5, 21)

Get days between two date.

>>>pytime.days_range('2015-5-17', '2015-5-23')
[datetime.date(2015, 5, 23),
 datetime.date(2015, 5, 22),
 datetime.date(2015, 5, 21),
 datetime.date(2015, 5, 20),
 datetime.date(2015, 5, 19),
 datetime.date(2015, 5, 18),
 datetime.date(2015, 5, 17)]

…

and other useful methods.

Contributors

License

MIT

Metadata

Release files for pytime 0.2.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pytime 0.2.3
File Size Uploaded
pytime-0.2.3.tar.gz 9.3 kB Details

Release files / pytime-0.2.3.tar.gz

Download URL pytime-0.2.3.tar.gz
Size 9.3 kB
Tags Source
SHA-256 checksum
How to use checksums
fc8e24ee82776621241618ba9c616e4a8b6045c9d6e5a0278fe096325c8432d2
BLAKE2b-256 checksum
How to use checksums
865a6e84a2cb32f17d7863406ee320cf71cb7df91f7f76864310943c3071e232
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.6

Release history Release notifications | RSS feed

This release

0.2.3 This release

1 release file

0.2.2

2 release files

0.2.1

2 release files

0.2.0

1 release file

0.1.8

1 release file

0.1.7

1 release file

0.1.6

1 release file

0.1.5

1 release file

0.1.3

1 release file

0.1.2

1 release file

0.1.1

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page