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content-hash-cache-pattern

Cache file processing results using SHA-256 content hashes.

2|Updated Mar 21, 2026
Search Tags:#performance#python#cache#file-processing#content-hash#caching-pattern
One-click install
npx skills add https://github.com/Throokie/claude-code-skills --skill content-hash-cache-pattern-throokie
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: content-hash-cache-pattern
Source: https://github.com/Throokie/claude-code-skills/tree/main/skills/content-hash-cache-pattern
Command: npx skills add https://github.com/Throokie/claude-code-skills --skill content-hash-cache-pattern-throokie

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cache expensive file processing results using SHA-256 content hashes as cache keys. Unlike path-based caching, this approach survives file moves/renames and auto-invalidates when content changes.

Core Features & Use Cases

  • Content-hash based cache keys to ensure cache validity across file moves or renames
  • File-based cache storage using {hash}.json for O(1) lookups
  • Service layer wrapper separates processing logic from caching concerns, enabling easy integration

Quick Start

Run a cache-enabled file processing task on a sample file to observe a cache miss on first run and a cache hit on subsequent 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 file processing results in Python so they survive renames and moves?▼

Content-hash caching uses SHA-256 file hashes as cache keys instead of file paths. This ensures cached results remain valid across file moves or renames, auto-invalidating only when the actual file content changes.

What is the best way to cache expensive OCR and PDF parsing results in Python?▼

The best way to cache expensive OCR and PDF parsing results is using content-hash caching. It stores computed outputs in JSON files named by the hash, enabling O(1) lookups and automatic invalidation when file content changes.

How does content-hash caching work for repeated file-processing pipelines?▼

Content-hash caching works by computing a SHA-256 hash for each file, using it as a JSON cache store key. A thin service wrapper separates core processing logic from caching, keeping processing pure and enabling easy integration.

Do I need extra dependencies to use content-hash caching for image analysis?▼

No extra dependencies are required. The content-hash caching pattern implements SHA-256 hashing and a JSON cache store natively, wrapping your image analysis pipeline without external libraries.

When should I not use content-hash caching for file processing?▼

You should not use content-hash caching when files are processed only once or when hashing large files outweighs the processing cost. It benefits pipelines where identical content is processed repeatedly across moves and renames.

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