Maya: Datetimes for Humans™
Datetimes are very frustrating to work with in Python, especially when dealing with different locales on different systems. This library exists to make the simple things much easier, while admitting that time is an illusion (timezones doubly so).
Datetimes should be interacted with via an API written for humans.
Maya is mostly built around the headaches and use-cases around parsing datetime data from websites.
☤ Basic Usage of Maya
Behold, datetimes for humans!
>>> now = maya.now() <MayaDT epoch=1481850660.9> >>> tomorrow = maya.when('tomorrow') <MayaDT epoch=1481919067.23> >>> tomorrow.slang_date() 'tomorrow' >>> tomorrow.slang_time() '23 hours from now' # Also: MayaDT.from_iso8601(...) >>> tomorrow.iso8601() '2017-02-10T22:17:01.445418Z' # Also: MayaDT.from_rfc2822(...) >>> tomorrow.rfc2822() 'Fri, 10 Feb 2017 22:17:01 GMT' # Also: MayaDT.from_rfc3339(...) >>> tomorrow.rfc3339() '2017-02-10T22:17:01.44Z' >>> tomorrow.datetime() datetime.datetime(2016, 12, 16, 15, 11, 30, 263350, tzinfo=<UTC>) # Automatically parse datetime strings and generate naive datetimes. >>> scraped = '2016-12-16 18:23:45.423992+00:00' >>> maya.parse(scraped).datetime(to_timezone='US/Eastern', naive=True) datetime.datetime(2016, 12, 16, 13, 23, 45, 423992) >>> rand_day = maya.when('2011-02-07', timezone='US/Eastern') <MayaDT epoch=1297036800.0> # Maya speaks Python. >>> m = maya.MayaDT.from_datetime(datetime.utcnow()) >>> print(m) Wed, 20 Sep 2017 17:24:32 GMT >>> m = maya.MayaDT.from_struct(time.gmtime()) >>> print(m) Wed, 20 Sep 2017 17:24:32 GMT >>> m = maya.MayaDT(time.time()) >>> print(m) Wed, 20 Sep 2017 17:24:32 GMT >>> rand_day.day 7 >>> rand_day.add(days=10).day 17 # Always. >>> rand_day.timezone UTC # Range of hours in a day: >>> maya.intervals(start=maya.now(), end=maya.now().add(days=1), interval=60*60) <generator object intervals at 0x105ba5820> # snap modifiers >>> dt = maya.when('Mon, 21 Feb 1994 21:21:42 GMT') >>> dt.snap('@d+3h').rfc2822() 'Mon, 21 Feb 1994 03:00:00 GMT'
☤ Advanced Usage of Maya
In addition to timestamps, Maya also includes a wonderfully powerful
MayaInterval class, which represents a range of time (e.g. an event). With this class, you can perform a multitude of advanced calendar calculations with finesse and ease.
>>> from maya import MayaInterval # Create an event that is one hour long, starting now. >>> event_start = maya.now() >>> event_end = event_start.add(hours=1) >>> event = MayaInterval(start=event_start, end=event_end)
From here, there are a number of methods available to you, which you can use to compare this event to another event.
☤ Why is this useful?
- All timezone algebra will behave identically on all machines, regardless of system locale.
- Complete symmetric import and export of both ISO 8601 and RFC 2822 datetime stamps.
- Fantastic parsing of both dates written for/by humans and machines (
- Support for human slang, both import and export (e.g. an hour ago).
- Datetimes can very easily be generated, with or without tzinfo attached.
- This library is based around epoch time, but dates before Jan 1 1970 are indeed supported, via negative integers.
- Maya never panics, and always carries a towel.
☤ What about Delorean, Arrow, & Pendulum?
All these project complement each other, and are friends. Pendulum, for example, helps power Maya's parsing.
Arrow, for example, is a fantastic library, but isn't what I wanted in a datetime library. In many ways, it's better than Maya for certain things. In some ways, in my opinion, it's not.
I simply desire a sane API for datetimes that made sense to me for all the things I'd ever want to do—especially when dealing with timezone algebra. Arrow doesn't do all of the things I need (but it does a lot more!). Maya does do exactly what I need.
I think these projects complement each-other, personally. Maya is great for parsing websites, and dealing with calendar events!
☤ Installing Maya
Installation is easy, with pipenv:
$ pipenv install maya
☤ Like it?
How to Contribute
- Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug.
- Fork the repository on GitHub to start making your changes to the master branch (or branch off of it).
- Write a test which shows that the bug was fixed or that the feature works as expected.
- Send a pull request and bug the maintainer until it gets merged and published. :) Make sure to add yourself to AUTHORS.