sag_py_cache_decorator

A cache annotation that can be used to cache calls to a method

What it does

• Caches calls to methods if the same parameters are used
• Removes the least recently used cache item if a optional maximum is reached
• Supports sync and async functions
• Possibility to skip the cache by parameter
• Possibility to clear the cache entirely or for one set of parameters

Installation

pip install sag-py-cache-decorator

How to use

from sag_py_cache_decorator.lru_cache import lru_cache

@lru_cache(maxsize=3)
def my_function(str: str, str2: str) -> str:
    return f"{str}-{str2}"

This is the regular use case of the cache.

Available decorator arguments:

from sag_py_cache_decorator.lru_cache import lru_cache

@lru_cache(maxsize=3)
def my_function(
    str: str,
    lru_clear_cache: bool = False,
) -> str:
    return f"{str}-{str2}"

my_function("one")
my_function("two")
# Before executing the next function the cache is cleared and then
# rebuilt with the results of three and four because of lru_clear_cache = True
my_function("three", lru_clear_cache = True)
my_function("four")

Available function arguments:

How to start developing

With vscode

Just install vscode with dev containers extension. All required extensions and configurations are prepared automatically.

With pycharm

• Install latest pycharm
• Install pycharm plugin Mypy
• Configure the python interpreter/venv
• pip install requirements-dev.txt
• Ctl+Alt+S => Click Tools => Actions on save => Reformat code
• Restart pycharm

How to publish

• Update the version in setup.py and commit your change
• Create a tag with the same version number
• Let github do the rest

How to test

To avoid publishing to pypi unnecessarily you can do as follows

• Tag your branch however you like
• Use the chosen tag in the requirements.txt-file of the project you want to test this library in, eg. sag_py_cache_decorator==<your tag>
• Rebuild/redeploy your project