362 lines
13 KiB
Python
362 lines
13 KiB
Python
"""
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AUTHOR:
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Khushal P Soonderji
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DATE:
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CREATED: Tue, 25th Nov, 2025
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UPDATED: Tue, 25th Nov, 2025
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OBJECTIVE:
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To define a set of functions for caching requirements. We will have caching decorators as well as an abstract
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class that defines the required methods.
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REFERENCES:
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N/A
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DOWNLOADS:
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N/A
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"""
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# *****************************************************************************************************************
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# ***** ****
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# *** IMPORT ***
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# ***** ****
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# *****************************************************************************************************************
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# To make sibling directories accessible for imports:
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import sys
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sys.path.append(".")
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sys.path.append("..")
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# For defining abstract classes:
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from abc import ABC, abstractmethod
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# For debugging:
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from icecream import IceCreamDebugger
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# For hashing and shortening the hash:
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import hashlib
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import base64
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# Other utils:
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from utils_v2.string import json
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# To work with datatypes:
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from typing import List, Any
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# To make decorators:
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from functools import wraps
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# *****************************************************************************************************************
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# ***** ****
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# *** MACROS / ONE-TIME INIT ***
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# ***** ****
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# *****************************************************************************************************************
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# --- Nothing Yet
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# *****************************************************************************************************************
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# ***** ****
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# *** VARIABLES ***
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# ***** ****
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# *****************************************************************************************************************
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# --- Nothing Yet
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# *****************************************************************************************************************
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# ***** ****
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# *** CLASSES ***
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# ***** ****
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# *****************************************************************************************************************
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class AsyncCachingBase(ABC):
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def __init__(
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self,
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debug: bool = True,
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debug_prefix: str = "A-Cache | "
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):
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"""
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The constructor of the caching abstract class
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:param debug: Whether, or not, you would like to print debugging messages.
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:param debug_prefix: The prefix text to show with the debugging messages.
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"""
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# For debugging:
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self.__printer = IceCreamDebugger(prefix = debug_prefix, includeContext = True)
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if not debug: self.__printer.disable()
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# ┳┓ ┓ •
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# ┃┃┏┓┣┓┓┏┏┓┏┓┓┏┓┏┓
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# ┻┛┗ ┗┛┗┻┗┫┗┫┗┛┗┗┫
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# ┛ ┛ ┛
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def enable_debug(self):
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self.__printer.enable()
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def disable_debug(self):
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self.__printer.disable()
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# ┓┏ ┓
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# ┣┫┏┓┃┏┓┏┓┏┓┏
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# ┛┗┗ ┗┣┛┗ ┛ ┛
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# ┛
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@staticmethod
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def make_key(*args, **kwargs) -> str:
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"""
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Generates a key by hashing the args and kwargs sent to it. Can be useful to generate a predictable key. If the
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inputs stay the same, the output stays the same.
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:param args: Any number of args that you would like to use to generate the key.
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:param kwargs: Any number of kwargs that you would like to use to generate the key.
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:return: A string that can be used as a key to store values on Redis.
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"""
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# Take everything into one plain text string:
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plain_text = "".join(str(a) for a in args)
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plain_text += json.to_string(kwargs, no_space = True)
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# Hash the plain text value, and create a key from it:
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sha256_hash = hashlib.sha256()
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sha256_hash.update(plain_text.encode("utf-8"))
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hashed_key = sha256_hash.digest()
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base64_key = base64.b64encode(hashed_key).decode("utf-8")
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# Done here:
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return base64_key
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# ┏┓
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# ┃ ┏┓┏┓┏┓
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# ┗┛┗┛┛ ┗
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@abstractmethod
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async def list_keys(
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self,
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match: str = None,
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raise_exception: bool = False
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) -> List[str] | None:
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"""
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To get a list of all the keys that match the pattern.
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:param match: To match a RegEx pattern.
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:param raise_exception: Whether to raise or suppress exceptions.
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:return: The list of keys if successful, else None.
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"""
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raise NotImplementedError
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@abstractmethod
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async def ttl(
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self,
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key: str | bytes,
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raise_exception: bool = False
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) -> int | float | None:
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"""
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To get the no. of seconds till the expiry of some key.
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:param key: The key to check the expiry of.
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:param raise_exception: Whether to raise or suppress exceptions.
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:return: -1 if the key is persistent (i.e., no expiry time set), -2 if the key does not exist, or the time left
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in seconds if the key exists and is not persistent. If something goes wrong, you will get a null value.
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"""
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raise NotImplementedError
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@abstractmethod
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async def set(
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self,
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key: str | bytes,
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value: Any,
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expiry: float = None,
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raise_exception: bool = False
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) -> bool:
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"""
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Saves some value to the cache. If an expiry is specified, the data will be deleted after that many seconds.
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:param key: The key with which the data will be stored and retrieved.
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:param value: The value to store.
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:param expiry: The time in seconds after which the data will expire. Must be a positive number.
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:param raise_exception: Whether to raise or suppress exceptions.
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:return: True if cached, else False.
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"""
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raise NotImplementedError
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@abstractmethod
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async def get(
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self,
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key: str | bytes,
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raise_exception: bool = False,
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on_fail: Any = None
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) -> Any:
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"""
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Retrieve the cached value.
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:param key: The key with which the data was saved.
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:param raise_exception: Whether to raise or suppress exceptions.
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:param on_fail: What to return if the process fails due to an exception.
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:return: The retrieved data, or null or 'on_fail' if not found.
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"""
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raise NotImplementedError
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@abstractmethod
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async def delete(
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self,
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key: str | bytes,
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raise_exception: bool = False
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) -> bool:
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"""
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Prematurely delete the value from the cache before it expires.
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:param key: The key with which the data was saved.
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:param raise_exception: Whether to raise or suppress exceptions.
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:return: True if deleted, else False.
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"""
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raise NotImplementedError
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@abstractmethod
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async def count(
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self,
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key: str | bytes,
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value: int = 1,
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expiry: float = None,
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raise_exception: bool = False
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) -> int | None:
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"""
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To use simple counters. If the counter (identified by the 'key') exists, it will be incremented, else the
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counter will be created and the value will be incremented from 0.
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:param key: The name of the counter.
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:param value: The amount to increment the value by. Send negative values to count backwards.
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:param expiry: The time (in seconds) in which the counter expires. Starts from the time the counter is created.
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This value has to be an integer. If a float is passed, the value will be rounded off.
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:param raise_exception: Whether to raise or suppress exceptions.
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:return: The latest value of the counter. Will be null if something went wrong and the exception was suppressed.
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"""
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raise NotImplementedError
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# *****************************************************************************************************************
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# ***** ****
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# *** FUNCTIONS ***
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# ***** ****
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# *****************************************************************************************************************
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def cache_it(
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cache: AsyncCachingBase,
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expiry: int | float = 120.0
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):
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"""
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This decorator factory takes an instance of the async caching class 'AsyncCachingBase' and holds your data there.
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If a subsequent call is made to the same decorated function with the same inputs, the result is fetched from the
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cache instead of going through the whole function again.
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:param cache: The instance of 'AsyncCachingBase'.
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:param expiry: The time in seconds after which the cached data must be cleared.
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:return: The decorator that automatically caches your data.
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"""
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def decorator(func):
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@wraps(func)
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async def wrapper(*args, **kwargs):
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# We first use the name of the function and the inputs given to it to generate a key for caching with the
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# simple hashing and shortening by way of base64 strings:
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inputs_given = func.__name__ + str([_ for _ in args]) + str(kwargs)
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base64_key = cache.make_key(inputs_given)
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# Now we check if we have the value in cache:
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try: response = await cache.get(base64_key, raise_exception = True)
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# If the key doesn't exist, we pass through the function and store the results.
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except:
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response = await func(*args, **kwargs)
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await cache.set(key = base64_key, value = response, expiry = expiry)
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# Return the response from the wrapped function.
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return response
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return wrapper
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return decorator
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# ---------------------------------------------------------------------------------------------------------------------
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def cache_class_methods(
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attr_name: str,
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expiry: int | float = 120.0
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):
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"""
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This decorator factory takes an instance of the async caching class 'AsyncCachingBase' and holds your data there.
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If a subsequent call is made to the same decorated function with the same inputs, the result is fetched from the
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cache instead of going through the whole function again.
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:param attr_name: The name of the variable that has an instance of 'AsyncCachingBase'.
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:param expiry: The time in seconds after which the cached data must be cleared.
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:return: The decorator that automatically caches your data.
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"""
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def decorator(func):
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@wraps(func)
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async def wrapper(self, *args, **kwargs):
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# Get the cache object first:
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cache_obj = getattr(self, attr_name)
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# We first use the name of the function and the inputs given to it to generate a key for caching with the
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# simple hashing and shortening by way of base64 strings:
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inputs_given = func.__name__ + str([_ for _ in args]) + str(kwargs)
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base64_key = cache_obj.make_key(inputs_given)
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# Now we check if we have the value in cache:
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try: response = await cache_obj.get(base64_key, raise_exception = True)
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# If the key doesn't exist, we pass through the function and store the results.
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except:
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response = await func(self, *args, **kwargs)
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await cache_obj.set(key = base64_key, value = response, expiry = expiry)
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# Return the response from the wrapped function.
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return response
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return wrapper
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return decorator
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# *****************************************************************************************************************
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# ***** ****
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# *** MAIN PROGRAM ***
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# ***** ****
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# *****************************************************************************************************************
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if __name__ == "__main__":
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pass
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