https://github.com/chr5tphr/funcache

Minimally cache python function outputs on disk!
https://github.com/chr5tphr/funcache

cache disk functions hash memoization metrohash numpy python pytorch

Last synced: 2 months ago
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Minimally cache python function outputs on disk!

• Host: GitHub
• URL: https://github.com/chr5tphr/funcache
• Owner: chr5tphr
• Created: 2019-09-19T12:40:37.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2019-10-15T11:23:35.000Z (over 6 years ago)
• Last Synced: 2025-08-10T04:34:56.805Z (11 months ago)
• Topics: cache, disk, functions, hash, memoization, metrohash, numpy, python, pytorch
• Language: Python
• Homepage:
• Size: 4.88 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Funcache

Caching function outputs by hashing inputs using MetroHash.

## Example

```python

from timeit import timeit

from shutil import rmtree

import numpy as np

from funcache import cache

cache_path = '/tmp/__democache__'

# default path to store cache can be set like the following:

@cache(cache_path)

def linear(data, weight, bias):

    return data @ weight + bias

for size in [1024, 2048, 4096, 8192]:

    data = np.zeros((size, size))

    weight = np.zeros((size, size))

    bias = np.zeros((size,))

    # the original, uncached function can be accessed as linear.__wrapped__

    dtime_u = timeit(

        lambda: linear.__wrapped__(data, weight, bias),

        number=1

    )

    # caching path can also be set using the keyword argument '_cache',

    # and disabled by setting it to None

    dtime_1 = timeit(

        lambda: linear(data, weight, bias, _cache=cache_path),

        number=1

    )

    dtime_2 = timeit(lambda: linear(data, weight, bias), number=1)

    print("Size: {}".format(size))

    print("    Uncached: {:.3f}s".format(dtime_u))

    print("    Cached 1: {:.3f}s".format(dtime_1))

    print("    Cached 2: {:.3f}s".format(dtime_2))

rmtree(cache_path)

```