tempcache 0.0.13

Python library to cache data and function results in temporary files

Python library to cache data and function results in temporary files

This library offers a simple way to cache data and function results using temporary files, including a mechanism for automatic expiration after a certain time.

Dy default, the package uses the pickle module to serialize data. Inputs are first serialized and then hashed to create unique cache file names.

Note For more advanced use cases you may want to look at the Memory class in joblib.

Basic usage

An instance of the TempCache class be used as a decorator to wrap a function and cache its results.

from tempcache import TempCache

CACHE_MAX_AGE = 86_400  # one day
cache = TempCache("mycache", max_age=CACHE_MAX_AGE)

@cache
def long_running(...):
    ...

result = long_running(...)

Caching results at the call site

You can also use a TempCache object to cache a function call directly at the call site with the cache_result method.

from tempcache import TempCache

CACHE_MAX_AGE = 86_400  # one day
cache = TempCache("mycache", max_age=CACHE_MAX_AGE)

def long_running(...):
    ...

result = cache.cache_result(long_running, ...)

Custom serialization

In cases where the inputs or result cannot be serialized by pickle you should use a pickler module like cloupickle.

import cloudpickle

from tempcache import TempCache

CACHE_MAX_AGE = 86_400  # one day
cache = TempCache("mycache",
                    pickler=cloudpickle,
                    max_age=CACHE_MAX_AGE)

Examples

Examples notebooks are in the extras folder.

Installation

You can install this package with pip.

pip install tempcache

Related projects

• joblib Computing with Python functions
• percache Persistently cache results of callables
• disckcache Disk and file backed cache library compatible with Django
• cloudpickle Extended pickling support for Python objects
• cached_path A file utility for accessing both local and remote files through a unified interface