sag-py-cache-decorator 0.0.3253

A decorator to cache method call results with similar parameters

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:

Argument	Description	Default
maxsize	If this size is reached, the least recently used cache item will be removed. Can be set to None to have a unlimited cache.	128

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:

Argument	Description	Default
lru_use_cache	If set to false, the function call skips the cache. Existing cached items are ignored and new ones are not written for that call.	True
lru_clear_cache	If set to true, the cache is cleared entirely before executing the method. The result of the call is then cached again.	False
lru_clear_arg_cache	If set to true, the result for this set of parameters is removed from cache(if present). The result of the call is then cached again.	False

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 BlackConnect
• Install pycharm plugin Mypy
• Configure the python interpreter/venv
• pip install requirements-dev.txt
• pip install black[d]
• Ctl+Alt+S => Check Tools => BlackConnect => Trigger when saving changed files
• Ctl+Alt+S => Check Tools => BlackConnect => Trigger on code reformat
• Ctl+Alt+S => Click Tools => BlackConnect => "Load from pyproject.yaml" (ensure line length is 120)
• Ctl+Alt+S => Click Tools => BlackConnect => Configure path to the blackd.exe at the "local instance" config (e.g. C:\Python310\Scripts\blackd.exe)
• 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