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Lazy accessor and other tools for deferred evaluation.

Project description

Lazyutils provides a few simple utilities for lazy evaluation of code.

Lazy attribute

The lazy decorator defines an attribute with deferred initialization::

.. code::python
import math
from lazyutils import lazy

class Vec:
def __init__(self, x, y):
self.x, self.y = x, y

def magnitude(self):
return math.sqrt(self.x**2 + self.y**2)

Now the ``magnitude`` attribute is initialized and cached upon first use:

>>> v = Vec(3, 4)
>>> v.magnitude

The attribute is writable and apart from the deferred initialization, it behaves
just like any regular Python attribute.

>>> v.magnitude = 42
>>> v.magnitude

Lazy attributes can be useful either to simplify the implementation of the
__init__ method of objects that initialize a great number or variables or as an
optimization that delays potentially expensive computations that may not be
necessary in the object's lifecycle.


The delegate_to() function delegates some attribute to an attribute during the
class definition::

.. code::python
from lazyutils import delegate_to

class Arrow:
magnitude = delegate_to('vector')

def __init__(self, vector, start=Vec(0, 0)):
self.vector = vector
self.start = start

Now, the ``.magnitude`` attribute of ``Arrow`` instances is delegated to
``.vector.magnitude``. Delegate fields are useful in class composition when one
wants to expose a few selected attributes from the inner objects. delegate_to()
handles attributes and methods with no distinction.

>>> a = Arrow(Vec(6, 8))
>>> a.magnitude


Aliasing is a very simple form of delegation. We can create simple aliases for
attributes using the alias() and readonly() functions::

class MyArrow(Arrow):
abs_value = readonly('magnitude')
origin = alias('start')

This exposes two additional properties: "abs_value" and "origin". The first is
just a read-only view on the "magnitude" property. The second exposes read and
write access to the "start" attribute.

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