content-hash-cache-pattern

Cache file processing results using SHA-256 content hashes as keys.

Updated Mar 20, 2026
One-click install
npx skills add https://github.com/KanakMalpani/General-Private-Skills --skill content-hash-cache-pattern-kanakmalpani
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: content-hash-cache-pattern
Source: https://github.com/KanakMalpani/General-Private-Skills/tree/main/skills/content-hash-cache-pattern
Command: npx skills add https://github.com/KanakMalpani/General-Private-Skills --skill content-hash-cache-pattern-kanakmalpani

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cache expensive file processing results using SHA-256 content hashes as cache keys. This approach ensures path-independence, automatically invalidates on content changes, and speeds up repeated processing.

Core Features & Use Cases

  • Content-hash based caching for file processing (PDFs, images, text)
  • Separate service layer for caching to keep core functions pure
  • Automatic invalidation on content changes without relying on file paths

Quick Start

Run the extraction with caching enabled (e.g., extract_with_cache(file_path)) to automatically store and reuse results across runs.

Frequently Asked Questions about content-hash-cache-pattern

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I cache expensive file processing results in Python without relying on file paths?

Cache file processing results by computing SHA-256 content hashes to use as cache keys. This approach ensures path-independence and automatically invalidates the cache when file content changes, speeding up repeated processing runs.

What is content-hash based caching and when should I use it for file processing?

Content-hash based caching stores processing results using a file's SHA-256 hash as the key. Use it for pipelines processing PDFs, images, or text where identical inputs reappear across runs, ensuring automatic invalidation on content changes.

How do I set up a content hash cache for my file processing pipeline?

Provide a pure extraction function, create a separate cache service layer, and configure a file-based cache directory. Call the extraction with caching enabled, like extract_with_cache(file_path), to automatically compute hashes and store or retrieve results.

Does content hash caching work with PDF, image, and text processing pipelines?

Yes, content hash caching works with PDFs, images, and text files. It uses SHA-256 hashes of the file contents as keys, making it applicable to any pipeline where the same file inputs reappear across multiple runs.

Why does my file processing cache return stale data after moving files to a new directory?

Path-based caches return stale data when directories change. Content-hash caching solves this by using SHA-256 content hashes as cache keys, ensuring path-independence and automatically retrieving valid cached results regardless of file location.

Do I need a separate service layer to implement content hash caching?

Yes, a separate cache service layer is required to handle hash computation and read or write operations to the file-based cache directory. This separation keeps your core extraction functions pure and maintainable.