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Tools for caching and memoization in python.

Project description


The ox_cache package is a collection of tools for fast, thread-safe, and flexible caching or memoizing of results. In particular, ox_cache is designed to make it easy to implement the quirks of your particular caching needs.

For example, if you want to repopulate the entire cache when you get a single cache miss, you can include the RefreshDictMixin. Or if you want to include least-recently-used semantics, you can include the LRUReplacementMixin. Or if you want a timed expiration, you can use the TimedExpiryMixin.

The basic structure is that you create a sub-class of OxCacheBase, include appropriate mixins, and then define a way to get a new value on a cache miss.


Some of the interesting features of ox_cache include:

  1. Flexible: You can mix and match mixins and overrides to easily get desired caching behavior.
  2. Memoization: Built-in decorators for function memoization.
  3. Dict-like: Dictionary methods such as __setitem__, __getitem__, __delitem__, __contains__, __iter__, and items are provided.
  4. Thread-safe: All of the basic operations use threading.Lock().
  5. Thread-smart: Hooks and overridable methods are structured so that you can ignore threads in your customization but stay thread safe.
  6. Docs: Python docstrings are provided for every class and method.
  7. Unit tests: Source code comes with unit tests with very high code coverage.

Quick Start


Install with the usual

$ pip install ox_cache


The simplest way to use the cache is to create an instance of OxCacheBase and use it like a dict as shown below but to really get the power of ox_cache, you will want to use mixins or overrides as shown later.

>>> from ox_cache import OxCacheBase
>>> c = OxCacheBase()  # trivial example of a cache
>>> c['foo'] = 5  # alternative:'foo', 5, **options)
>>> c['foo']

Of course, with the usage above you don’t really get any benefits beyond a standard dict. One convenient feature of ox_cache is that you can override the make_value method to get a “smart cache”. With make_value, when there is no value for a key, your cache will no how to make that value.

To get a “smart cache” you simply sub-class OxCacheBase and then override desired methods. The only required method you must override is the make_value method to make the value when a key is not in the cache. The following illustrates the simplest use case:

>>> from ox_cache import OxCacheBase
>>> class BasicCache(OxCacheBase):
...     def make_value(self, key, **opts):
...         'Simple function to create value for requested key.'
...         print('Calling refresh for key="%s"' % key)
...         return 'x' * key  # create a bunch of x's
>>> cache = BasicCache()
>>> cache.get(5)  # Will call make_value to generate 1st value.
Calling refresh for key="5"
>>> cache.get(5)  # Will get value from cache without calling make_value

You can get more interesting cache features by including mixins. The following illustrate a simple example where we include the TimedExpiryMixin so that cache entries expire after a set amount of time.

>>> from ox_cache import OxCacheBase, TimedExpiryMixin
>>> class TimedCache(TimedExpiryMixin, OxCacheBase):
...     'Cache which expires items after after self.expiry_seconds.'
...     def make_value(self, key, **opts):
...         'Simple function to create value for requested key.'
...         print('Calling refresh for key="%s"' % key)
...         return 'key="%s" is fun!' % key
>>> cache = TimedCache(expiry_seconds=100) # expires after 100 seconds
>>> cache.get('test')  # Will call make_value to generate value.
Calling refresh for key="test"
'key="test" is fun!'
>>> cache.ttl('test') > 60  # Check time to live is pretty long
>>> cache.get('test')  # If called immediately, will use cached item
'key="test" is fun!'
>>> cache.expiry_seconds = 1     # Change expiration time to be much faster
>>> import time; time.sleep(1.1) # Wait a few seconds for cache item to expire
>>> cache.get('test')  # Will generate a new value since time limit expired
Calling refresh for key="test"
'key="test" is fun!'

In addition to the get method illustrated above, a few other methods you may find useful include:

  1. ttl: Return the time-to-live for a key.
  2. expired: Return whether the cache entry for a key has expired.
  3. delete: Remove an entry from the cache.
  4. clean: Go through the entire cache and remove expired elements.
  5. exists: Check if an element is in the cache (possibly expired).

For more sophisticated caching you can use more mix-ins or override the desired functions. See the docs for the OxCacheBase class in the source code or in the following documentation sections.

Note that if you want to keep things as simple as possible, you don’t have to override make_value if using the TimedExpiryMixin but can just use the store method as shown below:

Keeping it Simple

>>> import time
>>> from ox_cache import OxCacheBase, TimedExpiryMixin
>>> class MyCache(TimedExpiryMixin, OxCacheBase):
...     'Cache with timed expiry'
>>> cache = MyCache()  # Create an instance
>>> cache.expiry_seconds = 1  # make refresh time very short
>>>'foo', 'blah')
>>> cache.get('foo')
>>> time.sleep(1.5)       # sleep so that cache becomes stale
>>> try:                  # Attempt to get stale item 'foo'
...     cache.get('foo')  # will cause an exception
... except:               # since make_value not defined
...     print("unable to get 'foo'")
unable to get 'foo'


To memoize (cache) function calls you can use something like the OxMemoizer as a function decorator as shown in the example below:

>>> from ox_cache import OxMemoizer
>>> @OxMemoizer
... def my_func(x, y):
...     'Add two inputs'
...     z = x + y
...     print('called my_func(%s, %s) = %s' % (x, y, z))
...     return z
>>> my_func(1, 2)  # This will actually call the function.
called my_func(1, 2) = 3
>>> my_func(1, 2)  # This will use a cached value.

Since OxMemoizer is just a sub-class of OxCacheBase you can use one of the provided mixins to control expiration or just use something like the LRUReplacementMemoizer. As shown below, setting the max_size property of an instance of LRUReplacementMemoizer will automatically kick out least recently used cache entries when the cache gets too large.

>>> from ox_cache import LRUReplacementMemoizer
>>> @LRUReplacementMemoizer
... def my_func(x, y):
...     'Add two inputs'
...     z = x + y
...     print('called my_func(%s, %s) = %s' % (x, y, z))
...     return z
>>> my_func(1, 2)
called my_func(1, 2) = 3
>>> my_func.max_size = 3
>>> data = [my_func(1, i) for i in range(4)]
called my_func(1, 0) = 1
called my_func(1, 1) = 2
called my_func(1, 3) = 4
>>> len(my_func), my_func.exists(1, 0)  # Verify least recent item kicked out
(3, False)

If you wanted time based expiration, you could use TimedMemoizer or simply subclass OxMemoizer and include mixins like LRUReplacementMixin and/or TimedExpiryMixin.

Note that since our memoizers are sub-classes of OxCacheBase, you can use any of the methods from OxCacheBase as shown below:

>>> my_func.exists(1, 3)
>>> my_func.delete(1, 3)
>>> my_func.exists(1, 3)


The ox_cache package provides tools to build your own simple caching system. The core class is OxCacheBase which everything inherits from. The only function which you must provide when you sub-class OxCacheBase is make_value which defines how to create a value which is not in the cache.

You can further customize how the cache works either by overriding appropriate methods or by using one of the many mixins provided. For example, the following illustrates how you can use the TimedExpiryMixin and the RefreshDictMixin to create a BatchCache which updates the whole cache any time there is a cache miss:

>>> from ox_cache import OxCacheBase, TimedExpiryMixin, RefreshDictMixin
>>> class BatchCache(TimedExpiryMixin, RefreshDictMixin, OxCacheBase):
...     'Simple cache with time-based refresh via a function that gives dict'
...     def make_dict(self, key):
...         "Function to make dict to use to refresh cache."
...         return {k: str(k) for k in ([key] + list(range(10)))}
>>> cache = BatchCache()
>>> = '5'
>>> cache.get(2) # will auto-refresh using make_dict
>>> cache.ttl(2) > 0
>>> = '6'
>>> cache.get(2) # cache has not been marked as stale so no refresh
>>> cache.expiry_seconds = 1  # make refresh time very short
>>> time.sleep(1.5)  # sleep so that cache becomes stale
>>> cache.ttl(2)
>>> cache.get(2)     # check cache to see that we auto-refresh
>>> cache.expiry_seconds = 1000  # slow down auto refresh for other examples
>>>, 5)
>>> cache.get(800)
>>>'800', 'a string')
>>> cache.get('800')
'a string'
>>> cache.delete(800)
>>> cache.get(800, allow_refresh=False) is None

Additional Information

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