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Store function results across executions using cache files

Project description

File Memoizer

license PyPi:version Tests Release

This Python package makes it easy to store function results across executions using cache files. Underlying functionality is provided by cachier, but this package adds a few conveniences, such as being able to ignore parameters that won't serialize.

Installation

Installation is via pip:

pip install file-memoizer

Usage

To cache a function's value, annotate it by calling the memoize function as follows. Note that all function arguments must be hashable for it to be cached else a TypeError will be thrown.

import file_memoizer

@file_memoizer.memoize()
def double(n):
    return 2 * n

By default the cached values remain valid for a day. This can be changed with the cache_ttl parameter:

import datetime
import file_memoizer

seven_days = cache_ttl=datetime.timedelta(days=7)

@file_memoizer.memoize(cache_ttl=seven_days)
def triple(n):
    return 3 * n

Cache files are stored in $HOME/.file-memoizer, with one file per combination of input parameters. An alternate location can be specified with the cache_directory parameter:

import datetime
import file_memoizer

custom_path = '/path/to/store/files'

@file_memoizer.memoize(cache_directory=custom_path)
def quadruple(n):
    return 4 * n

The memoizer will automatically ignore a function's first parameter if named self, so that instance methods can be cached. It is the caller's responsibility to ensure the result of the method does not depend on the state of the object's internals. This is most useful when the object is being used to call an external service.

import requests

class ExampleAPIClient():

    @file_memoizer.memoize()
    def get(self, url):
        return self.session.get(url)
    
    def __init__(self):
        self.session = requests.Session()

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