cacheing 0.1.1

a performant python cacheing library

cacheing - Pure Python Cacheing Library

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Motivation

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The initial motivation behind this package was twofold: fix the long insertion/eviction times in cachetools.LFUCache and provide an alternative to the cachetools.TTLCache offering variable per-key TTL's.

Installation

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pip install -U cacheing

And then in your python interpreter:

import cacheing

Updating

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Usage

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>>> from cacheing import LFUCache

>>> cache = LFUCache(capacity=2)

>>> cache[1] = 2
>>> cache[2] = 3
>>> cache[3] = 4

>>> cache
LFUCache{2: 3, 3: 4}

Benchmark

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cacheing has an included benchmarking library found in ./benchmark.

$ python3 ./benchmark.py --help

usage: benchmark [-h] [--cache [CACHE [CACHE ...]]] [--method [{get,set,delete} [{get,set,delete} ...]]]

arguments:
  -h, --help            show this help message and exit
  --cache [CACHE [CACHE ...]], -c [CACHE [CACHE ...]]
                        cache(s) to benchmark. example: cacheing.LRUCache.
  --method [{get,set,delete} [{get,set,delete} ...]], -m [{get,set,delete} [{get,set,delete} ...]]
                        method(s) to benchmark.

Run the Benchmarks:

$ cd benchmark

$ python3 ./benchmark.py --cache cachetools.LRUCache cacheing.LRUCache --method set get delete

Performance

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All benchmark times were measured using the provided benchmark library. See the benchmark section for details. The default benchmarking configuration executes 100,000 get operations, 20,000 set operations and n = cache_size delete operations. The median, p90, and p99 times for each operation, measured in microseconds, or 1e-6, are displayed in the figures below.

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Get (LFU Cache)             Delete (LFU Cache)

Set (LFU Cache)             Set - Cross Section (LFU Cache)

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Set (LRU Cache)             Get (LRU Cache)

Delete (LRU Cache)