supycache 0.1

Simple yet capable caching decorator for python

Simple yet capable caching decorator for python Source code: https://github.com/lonetwin/supycache

What is supycache ?

supycache is a decorator that enables caching of return values of time-consuming functions, either in memory or on a cache server such as memcached or redis.

The cache keys can either be indedependent or dependent (completely or partially) of the arguments passed to the function.

This is different from other similar caching decorators, for instance, functools.lru_cache which is dependent on all the arguments passed to the function and requires the arguments to be hashable.

Here’s an example of how you might use supycache

import time
import supycache

@supycache.supycache(cache_key='result')
def execute_expensive():
    time.sleep(15)
    return 42

print execute_expensive()  # This will take 15 seconds to execute ...
42
print execute_expensive()  # ...not this tho', because the value is cached ...
42
print supycache.default_backend.get('result') # ..keyed as `result`
42

However, you might want to be aware of the arguments that are passed to the function:

@supycache(cache_key='sum_of_{0}_and_{1}')   # Cache the sum of x and y creating a
def cached_sum(x, y):                        # key based on the arguments passed
    return x + y

You can also create the key based on partial arguments or on the attributes/items within the arguments.

class User:
    def __init__(self, name, session_key):
        self.name = name
        self.session_key = session_key

@supycache(cache_key='{user_obj.name}')   # build the cache key dependent on *just*
def get_username(user_obj):               # the `.name` attribute
    time.sleep(15)
    return user_obj.name

a = User(name='steve', session_key='0123456789')
b = User(name='steve', session_key='9876543210') # same name, different session

print get_username(user_obj=a)   # This will take 15 seconds to execute ...
steve
print get_username(user_obj=a)   # ...not this tho'...
steve
print get_username(user_obj=b)   # ...and neither will this !
steve


@supycache(cache_key='{choices[0]}_{menu[lunch]}')         # build the cache
def supersized_lunch(ignored, choices=None, menu=None):    # key dependent on
    time.sleep(15)                                         # partial arguments
    return 'You get a %s %s' % (choices[-1], menu['lunch'])

menu = {'breakfast' : 'eggs',
        'lunch'     : 'pizza',
        'dinner'    : 'steak'}

sizes = ['small', 'medium', 'large', 'supersize']

print supersized_lunch('ignored', choices=sizes, menu=menu)
You get a supersize pizza       # This will take 15 seconds to execute ...

print supersized_lunch('changed', choices=sizes, menu=menu)
You get a supersize pizza       # ...not this tho'...

If that format specification for the cache_key looks familiar, you’ve discovered the secret of supycache !

@supycache(backend=memcached_backend, cache_key='{0}_{kw[foo]}_{obj.x}')
def custom_key_built_from_args(positional, kw=None, obj=None):
    # now, supycache will build the `cache_key` from the arguments passed and
    # use the memcached_backend instance to `set` the key with the return value
    # of this function
    return 'cached'

The secret of supycache is quite simple – it calls .format() on the cache_key/expire_key with the passed args and kwargs to build the actual key. Additionaly the backend interface is abstarcted out neatly so that backends can be swapped out without too much hassle …and yeah, the decorator accepts more than just cache_key.

Right now though, this project has only the code and tests, no docs (barring a couple of docstrings !). I’ll be adding them soon. If interested take a look at the tests to see the typical usage and try it out. Feedback, bug reports and pull requests would be great !

Help required

I would really appreciate any help you could offer in validating the packaging and distribution of this module via pypi since I’ve not distributed any packages before.

Besides that I plan on adding a few more things:

• Ability to specify a max_age for the cache key.

• I’m not sure not the packaging for the dependency would work, but I’d like to automatically include the support for memcached or redis backends if the python memcached or redis modules are installed.

• logging support