On Thu, Nov 15, 2012 at 12:33 PM, Andriy Kornatskyy
<andriy.kornats...@live.com> wrote:
>
> A lazy attribute is an attribute that is calculated on demand and only once.
>
> The post below shows how you can use lazy attribute in your Python class:
>
> http://mindref.blogspot.com/2012/11/python-lazy-attribute.html
>
> Comments or suggestions are welcome.
I should add that I like the approach you're taking here. Usually
when I want a lazy property I just make an ordinary property of a
memoized function call:
def memoize(func):
cache = {}
@functools.wraps(func)
def wrapper(*args, **kwargs):
kwset = frozenset(kwargs.items())
try:
return cache[args, kwset]
except KeyError:
result = cache[args, kwset] = func(*args, **kwargs)
return result
return wrapper
class Foo:
def __init__(self):
self.times_called = 0
@property
@memoize # Alternatively, use functools.lru_cache
def forty_two(self):
self.times_called += 1
return 6 * 9
>>> foo = Foo()
>>> foo.times_called
0
>>> foo.forty_two
54
>>> foo.times_called
1
>>> foo.forty_two
54
>>> foo.times_called
1
Although you don't go into it in the blog entry, what I like about
your approach of replacing the descriptor with an attribute is that,
in addition to being faster, it makes it easy to force the object to
lazily reevaluate the attribute, just by deleting it. Using the
Person example from your blog post:
>>> p = Person('John', 'Smith')
>>> p.display_name
'John Smith'
>>> p.display_name
'John Smith'
>>> p.calls_count
1
>>> p.first_name = 'Eliza'
>>> del p.display_name
>>> p.display_name
'Eliza Smith'
>>> p.calls_count
2
Although in general it's probably better to use some form of reactive
programming for that.
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