A decorator for caching properties in classes.
Project description
A decorator for caching properties in classes.
Why?
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.
How to use it
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!
Invalidating the Cache
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['boardwalk']
>>> # request the boardwalk property again
>>> monopoly.boardwalk
600
>>> monopoly.boardwalk
600
Working with Threads
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:
import threading
from cached_property import threaded_cached_property
class Monopoly(object):
def __init__(self):
self.boardwalk_price = 500
self.lock = threading.Lock()
@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)
# Need to guard this since += isn't atomic.
with self.lock:
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)
Timing out the cache
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 https://github.com/pydanny/cached-property/issues/16.
Credits
Pip, Django, Werkzueg, Bottle, Pyramid, and Zope for having their own implementations. This package uses an implementation that matches 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
History
1.2.0 (2015-04-28)
Overall code and test refactoring, thanks to @gsakkis
Allow the del statement for resetting cached properties with ttl instead of del obj._cache[attr], thanks to @gsakkis.
Uncovered a bug in PyPy, https://bitbucket.org/pypy/pypy/issue/2033/attributeerror-object-attribute-is-read, thanks to @gsakkis
Fixed threaded_cached_property_with_ttl to actually be thread-safe, thanks to @gsakkis
1.1.0 (2015-04-04)
Regression: As the cache was not always clearing, we’ve broken out the time to expire feature to it’s own set of specific tools, thanks to @pydanny
Fixed typo in README, thanks to @zoidbergwill
1.0.0 (2015-02-13)
Added timed to expire feature to cached_property decorator.
Backwards incompatiblity: Changed del monopoly.boardwalk to del monopoly['boardwalk'] in order to support the new TTL feature.
0.1.5 (2014-05-20)
Added threading support with new threaded_cached_property decorator
Documented cache invalidation
Updated credits
Sourced the bottle implementation
0.1.4 (2014-05-17)
Fix the dang-blarged py_modules argument.
0.1.3 (2014-05-17)
Removed import of package into setup.py
0.1.2 (2014-05-17)
Documentation fixes. Not opening up a RTFD instance for this because it’s so simple to use.
0.1.1 (2014-05-17)
setup.py fix. Whoops!
0.1.0 (2014-05-17)
First release on PyPI.
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