Lazy Descriptors in Python
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Today I had a need to create a property on an object "lazily." The Python builtin property does a great job of this, but it calls the getter function every time you access the property. Here is how I ended up solving the problem:
First of all, I had (almost) the behavior I wanted by using the following pattern:
class Foo(object): def __init__(self): self._bar = None @property def bar(self): if self._bar is None: print 'Calculating self._bar' self._bar = 42 return self._bar
There are a couple of problems with this, however. First of all, I'm polluting my object's namespace with a _bar attribute that I don't want. Secondly, I'm using this pattern all over my codebase, and it's quite an eyesore.
Both problems can be fixed by using a descriptor. Basically, a descriptor is an object with a __get__ method which is called when the descriptor is accessed as a property of a class. The descriptor I created is below:
class LazyProperty(object): def __init__(self, func): self._func = func self.__name__ = func.__name__ self.__doc__ = func.__doc__ def __get__(self, obj, klass=None): if obj is None: return None result = obj.__dict__[self.__name__] = self._func(obj) return result
The descriptor is designed to be used as a decorator, and will save the decorated function and its name. When the descriptor is accessed, it will calculate the value by calling the function and save the calculated value back to the object's dict. Saving back to the object's dict has the additional benefit of preventing the descriptor from being called the next time the property is accessed. So I can now use it in the class above:
class Foo(object): @LazyProperty def bar(self): print 'Calculating self._bar' return 42
So I get a nice lazily calculated property that doesn't recalculate bar every time it's accessed and doesn't bother with any memoization itself. What do you think about it? Is this a patten you use in your code?
Source: http://blog.pythonisito.com/2008/08/lazy-descriptors.html
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Comments
Ask Solem replied on Sat, 2012/01/21 - 10:44am
Rick Copeland replied on Sat, 2012/01/21 - 9:17pm