Lazy accessor and other tools for deferred evaluation.
Lazyutils provides a few simple utilities for lazy evaluation of code.
The lazy decorator defines an attribute with deferred initialization:
class Vec: def __init__(self, x, y): self.x, self.y = x, y @lazy def magnitude(self): print('computing...') return math.sqrt(x**2 + y**2)
Now the magnitude attribute is initialized and cached upon first use:
>>> v = Vec(3, 4) >>> v.magnitude computing... 5.0
The attribute is writable and apart from the deferred initialization, it behaves just like any regular Python attribute.
>>> v.magnitude = 42 >>> v.magnitude 42
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:
class Arrow: magnitude = delegate_to('vector') def __init__(self, vector, start=Vec(0, 0)): self.vector = radius 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 magnitude... 10.0
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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