hyperscan
Python bindings for Hyperscan.
Decision gist · record as of 2026-08-14
Yes, if you need to match many regex patterns against text and performance is a concern. The pre-built wheels make installation straightforward on common platforms. The MIT license and active maintenance are favorable. Install it only if your workload genuinely requires bulk pattern matching; for single-pattern or simple regex tasks, Python's built-in `re` module is sufficient and simpler.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; compiled wheel must match your platform and Python version.
- Medium install friction due to compiled C extension wheels, but pre-built wheels are available for common platforms (macOS, Linux, Windows) and Python versions (3.8–3.14), eliminating the need to build Hyperscan locally.
- Repository is actively maintained with recent commits.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you may use, modify, and distribute this package freely in commercial and open-source projects with minimal restrictions.
last release 2026-03-19 (148 days) · last repo commit 2026-03-19 · 203 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 425,769 downloads/mo, #6,757 on PyPI
Alternatives
Verify before relying
pip install hyperscan
import hyperscan
db = hyperscan.compile([(b"pattern1", 0), (b"pattern2", 0)])
matches = db.scan(b"text to search")- Performance benchmarks or throughput comparisons versus standard Python regex or other high-performance regex libraries.
- Whether stream compression and custom allocator support are planned for future releases.
- Real-world latency or memory overhead for typical pattern sets and text sizes.
What it is and what it does
Hyperscan is a CPython extension that wraps Vectorscan, Intel's high-performance regex engine designed to match many patterns at once. Unlike Python's built-in `re` module, which compiles and tests patterns sequentially, Hyperscan compiles multiple patterns into a single state machine and scans text in a single pass, making it much faster for workloads that need to test dozens or hundreds of patterns simultaneously. The package ships with pre-built wheels that include Vectorscan statically linked, so you don't need to install system libraries separately.
The library exposes most of Vectorscan's C API, including Chimera support for advanced matching modes. It supports Python 3.8 through 3.14 on macOS, Linux, and Windows. The main limitations are lack of stream compression and custom allocator support, and a few specialized C functions not yet exposed to Python.
Use it for
- Intrusion detection or network traffic analysis where you need to match many malicious patterns against packet payloads in real time.
- Log aggregation or security event filtering, scanning incoming logs against a large set of rules or signatures.
- Content scanning or data loss prevention, checking documents or data streams against many forbidden patterns simultaneously.
- Regex-based data extraction or validation at scale, where you need to test many patterns against large text corpora efficiently.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to match many regex patterns against text and performance is a concern.
The pre-built wheels make installation straightforward on common platforms. The MIT license and active maintenance are favorable. Install it only if your workload genuinely requires bulk pattern matching; for single-pattern or simple regex tasks, Python's built-in `re` module is sufficient and simpler.
Install
hyperscan on PyPI
Before you install
Medium install friction due to compiled C extension wheels, but pre-built wheels are available for common platforms (macOS, Linux, Windows) and Python versions (3.8–3.14), eliminating the need to build Hyperscan locally. Repository is actively maintained with recent commits.
Requires Python 3.9 or later; compiled wheel must match your platform and Python version.
License in practice
MIT license is permissive; you may use, modify, and distribute this package freely in commercial and open-source projects with minimal restrictions.
Quickstart
pip install hyperscan
import hyperscan
db = hyperscan.compile([(b"pattern1", 0), (b"pattern2", 0)])
matches = db.scan(b"text to search")Verify before relying
- Performance benchmarks or throughput comparisons versus standard Python regex or other high-performance regex libraries.
- Whether stream compression and custom allocator support are planned for future releases.
- Real-world latency or memory overhead for typical pattern sets and text sizes.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.9 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 148 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 425,769 / month, #6,757 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaEnvironment :: ConsoleIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxOperating System :: UnixProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python ModulesTopic :: Utilities |
Evidence: hyperscan-0.8.2-cp310-cp310-macosx_10_9_x86_64.whl; hyperscan-0.8.2-cp310-cp310-macosx_11_0_arm64.whl; hyperscan-0.8.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; hyperscan-0.8.2-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; hyperscan-0.8.2-cp310-cp310-musllinux_1_2_aarch64.whl; hyperscan-0.8.2-cp310-cp310-musllinux_1_2_x86_64.whl; hyperscan-0.8.2-cp310-cp310-win_amd64.whl; hyperscan-0.8.2-cp311-cp311-macosx_10_9_x86_64.whl; hyperscan-0.8.2-cp311-cp311-macosx_11_0_arm64.whl; hyperscan-0.8.2-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; hyperscan-0.8.2-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; hyperscan-0.8.2-cp311-cp311-musllinux_1_2_aarch64.whl; hyperscan-0.8.2-cp311-cp311-musllinux_1_2_x86_64.whl; hyperscan-0.8.2-cp311-cp311-win_amd64.whl; hyperscan-0.8.2-cp312-cp312-macosx_10_13_x86_64.whl; hyperscan-0.8.2-cp312-cp312-macosx_11_0_arm64.whl; hyperscan-0.8.2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; hyperscan-0.8.2-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl; hyperscan-0.8.2-cp312-cp312-musllinux_1_2_aarch64.whl; hyperscan-0.8.2-cp312-cp312-musllinux_1_2_x86_64.whl
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