cachr 0.0.8

Library that allows you to compose your own cache, pre-packaged with many useful caches

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cachr: superfast, composable caching for Python

Testing
Package
Meta

cachr is a Python package that provides superfast, composable caches designed to optimize your applications in an easy and intuitive way. It aims to be the go-to package to use and build caches that make your applications superfast, memory-efficient and user-friendly.

pip install cachr

Table of Contents

• Main Features
• Usage Example
• Installation
• Dependencies
• License
• Documentation
• Development
• Contributing to Cachr

Main Features

• 🐍 Pure Python
• 🖌 Easily extendable
• 👨‍🎨 User-friendly

Usage Example

At the moment there are five caches available for use:

• LFUCache: Removes the least frequently used item in the cache when it overflows
• LRUCache: A Least Recently Used Cache removes the least recently used item when it overflows
• RandomReplaceCache: randomly expells an item from the cache when it overflows
• TTLCache: A Time-To-Live-cache acts like a LRUCache and also removes an entry from the cache after a certain expiration time
• SlidingWindowCache: Like a TTLCache but it renews the expiration date eacht time an item is requested from the cache.

All caches are added to your code in two ways: by decorator or as a regular object. Decorator:

import time
from cachr import LRUCache


# 1. Decorate your function
@LRUCache(capacity=2)
def add(i, y):
    time.sleep(1)
    print("adding..")
    return i + y


print(add(1, 2))    # <-- takes a second to calculate
print(add(1, 2))    # <-- takes value from cache immediately 
print(add(1, 2))    # <-- takes value from cache immediately 

Object:

from cachr import TTLCache

my_cache =  TTLCache(capacity=25, ttl_seconds=60)

def very_expensive_function(number:int) -> int:
    return number * number

for i in [1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 3, 5, 7, 9, 1, 1, 1, 1]:
    value_from_cache = my_cache.get(i)
    if value_from_cache is not None:
        print(f"Answer for {i} is {value_from_cache}")
        continue
    print(f"calculating expensive function for {i}..")
    my_cache.put(key=i, value=very_expensive_function(number=i))

Installation

pip install cachr

The source code is currently hosted on GitHub at: https://github.com/mike-huls/cachr

Binary installers for the latest released version are available at the Python Package Index (PyPI).

Dependencies

Cachr has no Python dependencies

License

MIT

Documentation

🔨 Under construction

Development

Find the changelog and list of upcoming features here.
Contributions are always welcome; feel free to submit bug reports, bug fixes, feature requests, documentation improvements or enhancements!

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