Is this skill suitable for all types of functions?

It is best suited for pure functions where the output is determined solely by the input arguments and there are no external side effects.

Can I set the cache to expire after a certain time?

Yes, the @diskcache_decorator accepts an optional duration in seconds. Common settings include one hour, one day, or one week.

How do I skip the cache for unit tests?

You can pass ignore_cache=True to any decorated function to bypass the cache and force the function to execute its internal logic.

Where are the cached results stored on my system?

By default, results are stored in a project-specific subdirectory within the ~/.cache/ directory on your local machine.

What library powers the caching mechanism?

This skill utilizes the robust diskcache Python package for persistent, disk-backed storage that survives script restarts.

Python Function Caching

Name: Python Function Caching
Author: gordonwatts

bygordonwatts

•

開発者ツール

Implements persistent disk-based memoization for Python functions to optimize performance and reduce redundant computations.

概要

This skill provides a reusable pattern for caching the results of deterministic Python functions using the diskcache package. By storing results on disk based on function arguments, it significantly reduces latency for expensive operations such as complex calculations or external API calls like LLM requests. The skill automates the setup of a project-specific cache directory, provides a customizable decorator with expiration support, and includes a built-in mechanism to bypass the cache during testing, making it an essential utility for developers building performance-sensitive Python applications.

主な機能

Automatic hash-based key generation from function arguments
Persistent disk-based storage using the Python diskcache package
Cache-bypass mechanism via ignore_cache parameter for unit testing
Configurable project-specific cache directories in the user home folder
Easy-to-use decorator pattern with support for custom expiration times
1 GitHub stars

ユースケース

Caching expensive LLM API calls to save costs and reduce latency during development
Storing results of heavy data processing tasks or complex mathematical computations
Optimizing repeated database queries or external service lookups in CLI tools

概要

主な機能

Automatic hash-based key generation from function arguments
Persistent disk-based storage using the Python diskcache package
Cache-bypass mechanism via ignore_cache parameter for unit testing
Configurable project-specific cache directories in the user home folder
Easy-to-use decorator pattern with support for custom expiration times
1 GitHub stars

ユースケース

Caching expensive LLM API calls to save costs and reduce latency during development
Storing results of heavy data processing tasks or complex mathematical computations
Optimizing repeated database queries or external service lookups in CLI tools