libaaron 1.1.0

trivial functions I like to pack along for various things

libaaron
========

Just my library of handy functions I like to bring along.

.. contents::

``reify``
----------
``reify`` is a decorator I stole from the Pylons project that I like to
use frequently.

from the docstring:

Use as a class method decorator. It operates almost exactly like the
Python ``@property`` decorator, but it puts the result of the method it
decorates into the instance dict after the first call, effectively
replacing the function it decorates with an instance variable. It is, in
Python parlance, a non-data descriptor.

``cached``
----------

``cached`` is a decorator that makes a property but caches its results.
It's functionally similar to reify, but it dynamically creates a
"private" attribute to cache the result instead of messing with
descriptors. This approach is comppatible with slots. I love slots.

``w``
-----
``w`` is a function that takes an iterable with a context manager (like
a file object) and yields from that iterable inside its context manager.

.. code:: python

>>> # instead of this:
>>> with open('myfile.txt') as mf:
... for line in mf:
... # do something
...
>>> # you can do this:
>>> for line in w(open('myfile.txt')):
... # do something
...
``flatten``
-----------
``flatten`` is a function that takes an iterable as an arguments and
recursively yields all contents from nested iterables (except strings,
which are yielded as strings). The optional second argument is a
function that will be used to convert any mappings into iterables before
yielding from them (in the event you want to yield from their values or
something else).

``quiteinterrupt``
------------------
``quiteinterrupt`` is a function that adds a signal handler which
silences the stacktrace when the a script is stopped with a keyboard
interrupt. It can optionally print a message on interrupt.

``DotDict``
-----------
``DotDict`` is a subclass of dict which allows fetching items with dot
syntax. Useful as an ``object_hook`` when deserializing JSON, perhaps.

``PBytes``
----------
``PBytes`` is a subclass of ``int`` which has a ``__str__`` that shows
interprets it as a number of bytes and make a human readable format. It
can also parse a number of bytes from a string.

.. code:: python

>>> print(PBytes(2134963))
2.0 MiB
>>> PBytes.from_str('35.8 KB')
PBytes(36659)
>>> PBytes.from_str('35.8 KB', decimal=True)
PBytes(35800)

Internally, it's just an integer, so you can do any integer operations
with it. Note that ``from_str`` does not attempt to determine whether it
is a binary or decimal format. Default is binary. Use ``decimal=True``
to explicitely change the behavior.

It also has a ``human_readable`` method which returns a number and the
units for easily constructing alterative representations:

.. code:: python

>>> PBytes(83629).human_readable()
(81.6689453125, 'K')
>>> '%d%s' % PBytes(83629).human_readable()
'81K'
>>> '%d%s' % PBytes(83629).human_readable(decimal=True)
'83K'


``Enum``
________
Make enum.Enum_ objects, but with nicer syntax.

.. code:: Python

>>> class var(libaaron.Enum):
... foo
... bar
... baz
...
>>> var.foo
<var.foo: 1>
>>> var.bar
<var.bar: 2>
>>> var.baz
<var.baz: 3>
>>> type(var)
<class 'enum.EnumMeta'>

Note that the resulting object is the same type as those created with
enum.Enum_, not a work-alike object.


.. _enum.Enum:
https://docs.python.org/3/library/enum.html#creating-an-enum