hyperscan-java provides Java bindings for Vectorscan, a high-performance multiple regex matching library (fork of Intel's Hyperscan). It allows simultaneous matching of thousands of regular expressions against input streams with exceptional throughput. The library offers two usage modes: a direct Vectorscan API for maximum performance (with limited regex syntax) and a PatternFilter utility that combines Vectorscan pre-filtering with Java's full regex engine for complete PCRE support. Key features include UTF-8 handling with byte-to-character mapping, database serialization for avoiding recompilation, callback-based scanning for efficient match processing, and support for both string and byte-oriented scanning. The architecture is a clean wrapper around the native library via JavaCPP, with well-separated concerns: Expression (pattern definition), Database (compiled pattern set), Scanner (matching engine), and utility classes. The codebase demonstrates strong engineering practices with comprehensive test coverage, including regression tests for upstream bugs and a JMH benchmark. It is actively maintained with recent releases and CI across Linux and macOS (x86_64 and arm64).
python-hyperscan is a CPython extension providing Python bindings for Vectorscan (a fork of Intel's Hyperscan), a high-performance multiple regex matching library. The library enables efficient pattern matching with statically linked binaries and cross-platform support. It exposes most of the Hyperscan C API through Python classes including Database for pattern compilation, Scan for text scanning, Stream for streaming processing, and Scratch for thread-safe scratch space management. The implementation features proper buffer protocol support, sophisticated GIL handling for both traditional and free-threaded Python models, and careful resource management. The build system uses scikit-build-core with CMake to statically link Hyperscan/Vectorscan along with dependencies like PCRE and Boost, producing binary wheels for multiple platforms.