zakuro-ai / zakuro-cache

Zakuro module used to keep python scripts execution logs and results in a cached memory.

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ZakuroCache is a Python package that provides two high-level features:

• A simple decorator to identify the pure functions you want to cache.
• A caching system that never repeat twice the same execution and return a cached result instead.

You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend ZakuroCache integration.

ZakuroCache modules

At a granular level, ZakuroCache is a library that consists of the following components:

Component	Description
zakuro_cache	Contains the implementation of the caching sytem.
zakuro_cache.loggers	Keep the print into an array during the fuction execution.
zakuro_cache.function	Pipeline to execute and store.

Installation

Docker

To build the image with docker-compose

sh docker.sh

Local

python setup.py install

Performances

If you are in local env you can run:

python demo.py

You should be able to execute a benchmark:

=====ZAKURO-CACHE=====
0.03user 0.00system 0:00.03elapsed 97%CPU (0avgtext+0avgdata 15444maxresident)k
0inputs+128outputs (0major+2493minor)pagefaults 0swaps


=====NO-CACHE=====
10.18user 0.00system 0:10.18elapsed 99%CPU (0avgtext+0avgdata 15568maxresident)k
496inputs+128outputs (3major+2491minor)pagefaults 0swaps

Getting-started

To apply the cache simply add the decorator to your functions.

from zakuro_cache.function import pure

@pure
def recur_fibo(n):
    if n <= 1:
        return n
    else:
        res1, res2 = recur_fibo(n - 1), recur_fibo(n - 2)
        return res1 + res2


if __name__ == "__main__":
    nterms = 35
    for i in range(nterms):
       print(recur_fibo(i))