content-hash-cache-pattern

Cache file processing results using SHA-256 content hashes.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/giuseppecutuli/speakdoc --skill content-hash-cache-pattern-giuseppecutuli
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: content-hash-cache-pattern
Source: https://github.com/giuseppecutuli/speakdoc/tree/main/.claude/skills/content-hash-cache-pattern
Command: npx skills add https://github.com/giuseppecutuli/speakdoc --skill content-hash-cache-pattern-giuseppecutuli

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

  • Path-independence: cache keys are content hashes, so moves/renames don't invalidate hits.
  • Auto-invalidations: content change invalidates existing cache entries automatically.
  • Service-layer separation: keeps processing functions pure and caches accessed via a separate layer; supports pipelines for PDF parsing, OCR, and image analysis tasks.

Quick Start

Process a file with caching enabled to automatically reuse results keyed by its content hash.

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 without invalidating them when files are moved or renamed?

You can cache file processing results using SHA-256 content hashes as cache keys instead of file paths. This approach ensures that moves or renames do not invalidate cache hits, keeping the cached results stable across file system changes.

Why does path-based caching fail when processing PDFs and images in automated pipelines?

Path-based caching fails because moving or renaming a file changes its path, causing cache misses even if the content is identical. Content-hash caching solves this by keying the cache with the file's SHA-256 hash, making it completely path-independent.

How do I auto-invalidate cached data when file contents change in a Python pipeline?

Auto-invalidation happens automatically when caching with content hashes. Because the cache key is the SHA-256 of the file contents, any modification changes the hash, ensuring the cache reads and writes only match unchanged file data.

Does content-hash caching work with a service layer for parsing text, PDFs, and images?

Yes, it supports a service-layer separation by keeping file processing functions pure while the caching logic reads and writes from a separate file-based cache. It handles pipelines for PDF parsing, OCR, and image analysis tasks effectively.

What is the best way to cache expensive file processing results in Python data pipelines?

The best way is using a content-hash cache pattern that keys results by SHA-256 hashes. It avoids redundant processing of unchanged files and automatically invalidates entries when content changes, optimizing expensive parsing operations.