Persistent caching for python functions

Related tags

Cachingpythoncachefunctionspython3persistentpython2python-functionscashier
Overview

Cashier

Persistent caching for python functions

Simply add a decorator to a python function and cache the results for future use. Extremely handy when you are dealing with I/O heavy operations which seldom changes or CPU intensive functions as well.

Anatomically, once a function is called, result from the function is cached into an SQLite3 database locally, with an expiry time. There is a maximum length for the cache to prevent cache flooding the file system.

Installation

pip install cashier

Or you can clone the source and run setup.py

git clone [email protected]:atmb4u/cashier.git
cd cashier
python setup.py install

Usage

from cashier import cache

@cache()
def complex_function(a,b,c,d):
    return complex_calculation(a,b,c,d)

If you go ahead on the above configuration, following are the default values

  • cache_file : .cache

  • cache_time : 84600

  • cache_length : 10000

  • retry_if_blank : False

Advanced Usage

from cashier import cache

@cache(cache_file="sample.db", cache_time=7200, cache_length=1000, 
       retry_if_blank=True)
def complex_function(a, b, c, d):
    return complex_calculation(a, b, c, d)

cache_file : SQLite3 file name to which cached data should be written into (defaults to .cache)

cache_time : how long should the data be cached in seconds (defaults to 1 day)

cache_length : how many different arguments and corresponding data should be cached (defaults to 10000)

retry_if_blank : If True, will retry for the data if blank data is cached ( default is False)

Performance Benchmark

For reproducing results, run python test.py from the project root.

No Cache Run: 9.932126 seconds

First Caching Run: 9.484081 seconds

Cached Run: 0.606016 seconds (16 x faster)

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Comments
  • feature request: profiler/stats on cache usage

    feature request: profiler/stats on cache usage

    Would be great to be able to run a report that would show how many times each cache was hit, how many were hits or missed, and how long it took to complete the non-cached calls. This would help tune how cachier is configured.

    opened by nima 0
  • kwargs are ignored when making a hash key

    kwargs are ignored when making a hash key 

    >>> @cache(cache_file="/tmp/cache.db")
... def fn(a=1):
...     print(a)
...     return a
...
>>>
>>> fn(a=1)
1
1
>>> fn(a=2)
1
>>>

    https://github.com/atmb4u/cashier/blob/master/cashier/init.py#L130

    opened by bofm 0
  • Support for SQLite 'in memory' mode

    Support for SQLite 'in memory' mode

    Sorry if this is already supported, but it wasn't clear from the docs or the tests, if this library supports using the sqlite in memory operation mode to avoid unnecessary file system access if you don't need a persistent cache across process restarts.

    opened by techdragon 0
Releases(v1.2.0)
Owner
Anoop Thomas Mathew
Anoop Thomas Mathew
GitHub Repository https://atmb4u.github.io/cashier
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