content-hash-cache-pattern

Caching expensive file processing like PDF parsing or OCR uses a content hash as the cache key to identify files. This approach enables path-independent caching that survives file moves or renames across different processing sessions.

Using a content-hash-based cache key is the best way to cache file processing results when files are moved or renamed. The cache entries are stored as individual JSON files named by hash, providing O(1) lookups without needing an index file.

Yes, this content-hash caching approach uses a service-layer design that requires a separate cache service to handle reads, writes, and invalidations. This design keeps your file processing functions pure and separate from cache management logic.

You implement a content hash cache for batch text extraction pipelines by pairing a pure processing function with a separate cache service. The service computes the file's content hash, checks for a matching JSON file, and handles cache hits or misses accordingly.

Yes, you can use file-based JSON storage for caching image analysis results. The system stores each cache entry as a JSON file named by the content hash, enabling O(1) lookups for your image processing pipelines without requiring an index file.

Your file cache misses when processing the same file from a new directory path because path-based cache keys become invalidated upon moving files. Using a content-hash-based cache key solves this by identifying files solely by their content, ensuring cache hits regardless of location.