Caching results of functions in Python
Project description
Caching results of functions in Python.
Features
Storing cached data either on disk or in memory
Setting up time-to-live and the number of function calls for your cache
Encryption of cached data (symmetric encryption (RSA) algorithm is used)
Note
Encryption functionality requires pycrypto package to be installed
When using cache-to-file functionality you have to to clean up (if needed) created file(s) manually
Examples
from cachepy import * mycache = Cache() # cache to memory without encryption @mycache def my_heavy_function(x): """Performs heavy computations""" print('Hi, I am called...') return x**2 my_heavy_function(2) # "Hi, I am called..." will be printed to stdout only once my_heavy_function(2)
To store data to file, you need to create decorator as follows:
# create cache-to-file decorator filecache = Cache('mycache.dat')
Its behaviour is the same as a memory-based one.
One can set up time-to-live and/or maximum number of retrievals for cached data when a decorator is created:
import time from cachepy import * # or from cachepy import Cache cache_with_ttl = Cache(ttl=2) # ttl given in seconds @cache_with_ttl def my_heavy_function(x): """Performs heavy computations""" print('Hi, I am called...') return x**2 my_heavy_function(3) my_heavy_function(3) # This will not print 'Hi, I am called ...' time.sleep(2) my_heavy_function(3) # 'Hi, I am called ...' will be printed again cache_with_noc = Cache(noc=2) # Number-of-calls = 2 @cache_with_noc def my_heavy_function(x): """Performs heavy computations""" print('Hi, I am called...') return x**2 my_heavy_function(3) my_heavy_function(3) # This will not print 'Hi, I am called ...' my_heavy_function(3) # 'Hi, I am called ...' will be printed again
It is easy to use both noc and ttl arguments on a cache decorator:
cache_with_noc_ttl = Cache(noc=2, ttl=1) @cache_with_noc_ttl def my_heavy_function(x): """Performs heavy computations""" print('Hi, I am called...') return x**2 my_heavy_function(3) my_heavy_function(3) # This will not print 'Hi, I am called ...' my_heavy_function(3) # This will print 'Hi, I am called ...' time.sleep(2) # get ttl to be expired my_heavy_function(3) # This will print 'Hi, I am called ...'
One can encrypt cached data by providing non-empty key argument as a password (RSA algo is used):
cache_to_file_ttl_noc = Cache('mycache.dat', noc=2, ttl = 2, key='mypassword') @cache_to_file_ttl_noc def my_heavy_function(x): """Performs heavy computations""" print('Hi, I am called...') return x**2 my_heavy_function(2) # Will print 'Hi, I am called...' my_heavy_function(2) # Will not print 'Hi, I am called...'
Calling the my_heavy_function function being decorated by cache_to_file_ttl_noc will store 4 (result of computations) in the file mycache.dat; along with the result of computations, additional info will be stored (these all will be encrypted by the RSA algo with the password mypassword): result expiration time (computed from ttl), noc and the number of performed calls of the decorated function (my_heavy_function). Data will not be encrypted, if pycrypto package isn’t installed. If you pass non- empty key parameter to the Cache constructor, the warning will occurred (“Pycrypto not installed. Data isn’t encrypted”); In this case, the cache will work without encryption functionality.
Testing
The code tested (and works as expected) in Python > 2.7.x and Python > 3.4.x.
python -m cachepy.tests
TODO
Writing backend for redis server
Testing in Python 3.x causes Error 11?!
Log list
Version 0.1
initial release
Code author: Dmitry Kislov <kislov@easydan.com>
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.