A decorator for caching properties in classes.
- Makes caching of time or computational expensive properties quick and easy.
- Because I got tired of copy/pasting this code from non-web project to non-web project.
- I needed something really simple that worked in Python 2 and 3.
Let's define a class with an expensive property. Every time you stay there the price goes up by $50!
class Monopoly(object):
def __init__(self):
self.boardwalk_price = 500
@property
def boardwalk(self):
# In reality, this might represent a database call or time
# intensive task like calling a third-party API.
self.boardwalk_price += 50
return self.boardwalk_price
Now run it:
>>> monopoly = Monopoly()
>>> monopoly.boardwalk
550
>>> monopoly.boardwalk
600
Let's convert the boardwalk property into a cached_property
.
from cached_property import cached_property
class Monopoly(object):
def __init__(self):
self.boardwalk_price = 500
@cached_property
def boardwalk(self):
# Again, this is a silly example. Don't worry about it, this is
# just an example for clarity.
self.boardwalk_price += 50
return self.boardwalk_price
Now when we run it the price stays at $550.
>>> monopoly = Monopoly()
>>> monopoly.boardwalk
550
>>> monopoly.boardwalk
550
>>> monopoly.boardwalk
550
Why doesn't the value of monopoly.boardwalk
change? Because it's a cached property!
Results of cached functions can be invalidated by outside forces. Let's demonstrate how to force the cache to invalidate:
>>> monopoly = Monopoly()
>>> monopoly.boardwalk
550
>>> monopoly.boardwalk
550
>>> # invalidate the cache
>>> del monopoly.__dict__['boardwalk']
>>> # request the boardwalk property again
>>> monopoly.boardwalk
600
>>> monopoly.boardwalk
600
What if a whole bunch of people want to stay at Boardwalk all at once? This means using threads, which
unfortunately causes problems with the standard cached_property
. In this case, switch to using the
threaded_cached_property
:
from cached_property import threaded_cached_property
class Monopoly(object):
def __init__(self):
self.boardwalk_price = 500
@threaded_cached_property
def boardwalk(self):
"""threaded_cached_property is really nice for when no one waits
for other people to finish their turn and rudely start rolling
dice and moving their pieces."""
sleep(1)
self.boardwalk_price += 50
return self.boardwalk_price
Now use it:
>>> from threading import Thread
>>> from monopoly import Monopoly
>>> monopoly = Monopoly()
>>> threads = []
>>> for x in range(10):
>>> thread = Thread(target=lambda: monopoly.boardwalk)
>>> thread.start()
>>> threads.append(thread)
>>> for thread in threads:
>>> thread.join()
>>> self.assertEqual(m.boardwalk, 550)
Sometimes you want the price of things to reset after a time. Use the ttl
versions of cached_property
and threaded_cached_property
.
import random
from cached_property import cached_property_with_ttl
class Monopoly(object):
@cached_property_with_ttl(ttl=5) # cache invalidates after 5 seconds
def dice(self):
# I dare the reader to implement a game using this method of 'rolling dice'.
return random.randint(2,12)
Now use it:
>>> monopoly = Monopoly()
>>> monopoly.dice
10
>>> monopoly.dice
10
>>> from time import sleep
>>> sleep(6) # Sleeps long enough to expire the cache
>>> monopoly.dice
3
>>> monopoly.dice
3
Note: The ttl
tools do not reliably allow the clearing of the cache. This
is why they are broken out into seperate tools. See pydanny#16.
What if you want to cache a property accross different instances, you can use
cached_classproperty
. Note that cached_classproperty cannot be invalidated.
from cached_property import cached_classproperty
class Monopoly(object):
boardwalk_price = 500
@cached_classproperty
def boardwalk(cls):
cls.boardwalk_price += 50
return cls.boardwalk_price
Now use it:
>>> Monopoly().boardwalk
550
>>> Monopoly().boardwalk
550
- Pip, Django, Werkzueg, Bottle, Pyramid, and Zope for having their own implementations. This package originally used an implementation that matched the Bottle version.
- Reinout Van Rees for pointing out the cached_property decorator to me.
- My awesome wife @audreyr who created cookiecutter, which meant rolling this out took me just 15 minutes.
- @tinche for pointing out the threading issue and providing a solution.
- @bcho for providing the time-to-expire feature
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