Is SHA-256 hashing efficient for very large files?

Yes, the pattern implements chunked reading (typically in 64KB blocks), allowing you to calculate hashes for multi-gigabyte files without loading the entire file into memory.

Does this pattern require an external database?

No, it utilizes a flat-file structure where the SHA-256 hash serves as the filename (e.g., {hash}.json). This allows for O(1) lookups directly via the filesystem without needing a central index.

How does this improve code maintainability?

By using a service layer wrapper, the core processing logic remains 'pure' and focused on its primary task. Caching is treated as a cross-cutting concern that can be added or removed without modifying the underlying extraction logic.

Why use content hashes instead of file paths for caching?

Content hashes ensure cache hits even if files are renamed or moved. Because the key is derived from the content itself, the cache automatically invalidates if the file is modified, preventing stale data.

Content-Hash Cache Pattern

Name: Content-Hash Cache Pattern
Author: saar120

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Optimizes expensive file processing pipelines by implementing content-based, path-independent SHA-256 caching.

This skill provides a standardized architectural pattern for caching the results of computationally expensive file operations, such as PDF parsing, OCR, or image analysis. By using SHA-256 content hashes as cache keys rather than file paths, it ensures that cached results remain valid even if files are renamed or moved, while providing automatic invalidation the moment content changes. The pattern emphasizes a service-layer approach that keeps core processing functions pure and decoupled from caching logic, enabling robust, O(1) lookup performance for high-volume data pipelines.

主な機能

010 GitHub stars

02Automatic cache invalidation upon any change to file content

03Memory-efficient chunked hashing for large file support

04O(1) lookup performance using hash-based file storage without an index

05Service layer separation to maintain pure, testable processing functions

06Path-independent caching using SHA-256 content fingerprinting

ユースケース

01Developing high-performance PDF parsing or OCR extraction pipelines

02Optimizing batch processing tasks where identical files appear across multiple runs

03Building CLI tools that require efficient result caching and invalidation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add saar120/skillgate-registry content-hash-cache-pattern

For use in Claude.ai and ChatGPT

主な機能

010 GitHub stars

02Automatic cache invalidation upon any change to file content

03Memory-efficient chunked hashing for large file support

04O(1) lookup performance using hash-based file storage without an index

05Service layer separation to maintain pure, testable processing functions

06Path-independent caching using SHA-256 content fingerprinting

ユースケース

01Developing high-performance PDF parsing or OCR extraction pipelines

02Optimizing batch processing tasks where identical files appear across multiple runs

03Building CLI tools that require efficient result caching and invalidation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add saar120/skillgate-registry content-hash-cache-pattern

For use in Claude.ai and ChatGPT