Optimizes expensive file processing by caching results based on SHA-256 content hashes rather than file paths.
This skill provides a robust architectural pattern for caching high-cost file operations, such as PDF parsing, OCR, or image analysis, by using unique content hashes as identifiers. By prioritizing content identity over file paths, it ensures that cache hits survive file renames or moves and automatically invalidates entries the moment file contents change. The implementation follows the Single Responsibility Principle by using a service-layer wrapper, keeping core processing functions pure while providing efficient O(1) file-based storage and memory-safe chunked hashing for large files.
Key Features
01Automatic cache invalidation triggered by file content changes
02O(1) lookup performance using hash-based file storage
03Memory-efficient chunked hashing for processing large assets
04Path-independent caching using SHA-256 content identifiers
05Clean service-layer separation to maintain pure functions
060 GitHub stars
Use Cases
01Reducing processing time and API costs in machine learning or image analysis workflows
02Caching high-latency PDF extraction and OCR processes in document pipelines
03Optimizing CLI tools that perform repetitive analysis on the same local data files
