Python descriptors allow you to create properties on python objects that are the result of executing some code. One of the simplest ways of doing that is using the @property decorator. Here, accessing the myprop will call the method and return the resulting "data".

    class MyClass(object):
        @property
        def myprop(self):
            return "data"

One variant of this is the cached_property pattern. There are many implementations floating around. There is a package on pypi. Werkzeug, and by extension Flask, has one. Django has one. These implementations all rely on the fact that if you add a value to the __dict__ of an object, that value has precedence over descriptors and so you can use it as a quickly accessable place to store cached data.

This has a downside however in that this cached data will be pickled along with your object when serializing it to disk or to a caching layer like memcached. In extreme cases this can lead to your pickled binary data exceeding the memcached per-key space limits.

I came up with a way to avoid this by adding a mixin to classes but it’s not terribly clean and seems like it would be brittle.

    class CachedPropertyMixin(object):
        def __getstate__(self):
            state = self.__dict__.copy()
            for key in state:
                if (hasattr(self.__class__, key) and
                        isinstance(getattr(self.__class__, key), cached_property)):
                    del state[key]
            return state


    class MyClass(CachedPropertyMixin, object):
        @cached_property
        def myprop(self):
            return "data"

I’m not really satisfied with this solution so I’d be interested in hearing if there are any other ideas about how to do avoid pickling cached data.