Python Distribution Utilities
Sometimes you write a function over and over again; sometimes you look up at the ceiling and ask “why, Guido, why isn’t this included in the standard library?”
Well, we perhaps can’t answer that question. But we can collect those functions into a centralized place!
Utils is broken up into broad swathes of functionality, to ease the task of remembering where exactly something lives.
Python doesn’t have a built-in way to define an enum, so this module provides (what I think) is a pretty clean way to go about them.
from utils import enum class Colors(enum.Enum): RED = 0 GREEN = 1 # Defining an Enum class allows you to specify a few # things about the way it's going to behave. class Options: frozen = True # can't change attributes strict = True # can only compare to itself; i.e., Colors.RED == Animals.COW # will raise an exception. # or use the enum factory (no Options, though) ColorsAlso = enum.enum("RED", "GREEN")
Once defined, use is straightforward:
>>> Colors <class 'blahblah.Colors'> >>> Colors.RED <EnumItem: RED > >>> Colors.RED == 0 True >>> Colors.RED == Colors.RED True >>> Colors.RED = 2 Traceback (most recent call last): File "<stdin>", line 1, in <module> File "utils/enum.py", line 114, in __setattr__ raise TypeError("can't set attributes on a frozen enum") TypeError: can't set attributes on a frozen enum
Currently only has the multiplicative analogue of the built-in sum.
intersections, differences, winnowing, a few specialized dicts…
flatten and unlisting
currently only provides an xor function.
Mostly cool for the TimePeriod classes:
>>> from datetime import date # will also work with datetimes >>> time_period = TimePeriod(date(2013, 5, 10), date(2013, 8, 11)) >>> time_period <TimePeriod: 2013-05-10 00:00:00-2013-08-11 23:59:59> >>> date(2013, 6, 12) in time_period True >>> other_time_period = TimePeriod(date(2013, 6, 1), date(2013, 6, 30)) >>> other_time_period in time_period True >>> another_time_period = TimePeriod(date(2013, 8, 1), date(2013, 8, 30)) >>> time_period.overlaps(another_time_period) True >>> TimePeriod.get_containing_period(time_period, another_time_period) <TimePeriod: 2013-05-08 00:00:00-2013-08-30 23:59:59>
and so on and so forth. There’s also a DiscontinousTimePeriod class, which stores a collection of TimePeriods.
There’s also helper functions for common operations like days_ahead and days_ago, which pretty much do what they say on the tin.