Ashwa 🐎
Hardware accelerated routines for single substring search
💡 TIP:
ashwaprovides native CPython extension bindings powered by Rust and SIMD vectorization.
ℹ️ NOTE: The best available SIMD instruction set (AVX-512BW, AVX2, SSE4.2, SSSE3, SSE2, ARM NEON) is detected automatically at runtime on the host CPU with seamless fallback to SWAR routines.
Index
Supported Platforms
| Architecture | Target Platform | Target ISA | Fallback |
|---|---|---|---|
| x86_64 | Linux, macOS, Windows | AVX-512BW, AVX2, SSE4.2, SSSE3, SSE2 | 64-bit SWAR |
| i686 (x86) | Linux, Windows | SSE2 | 32-bit SWAR |
| AArch64 (ARM64) | Apple Silicon, Linux ARM64, Android, FreeBSD | 128-bit ARM NEON | 64-bit SWAR |
| ARMv7 | Linux ARM, Android | 128-bit ARM NEON | 32-bit SWAR |
Installation
Install ashwa using your preferred Python package manager:
pip install ashwa
API Reference
search_one(haystack, needle)
def search_one(
haystack: bytes | bytearray | memoryview,
needle: int,
) -> int | None:
...
Searches for the first occurrence of needle (an int 0–255) within haystack.
- Parameters:
haystack:bytes | bytearray | memoryview— The bytes-like object to search in.needle:int— The target byte value (0–255) to locate.
- Returns:
- The 0-based byte index (
int) of the first occurrence ofneedle, orNoneif not found.
- The 0-based byte index (
search_two(haystack, needle)
def search_two(
haystack: bytes | bytearray | memoryview,
needle: bytes | bytearray | memoryview | tuple[int, int] | list[int] | Sequence[int],
) -> int | None:
...
Searches for the first occurrence of a two-byte needle within haystack.
- Parameters:
haystack:bytes | bytearray | memoryview— The bytes-like object to search in.needle:bytes | bytearray | memoryview | tuple[int, int] | list[int] | Sequence[int]— A 2-byte sequence to locate.
- Returns:
- The 0-based byte index (
int) of the first occurrence ofneedle, orNoneif not found.
- The 0-based byte index (
Benchmarks
Benchmarks are evaluated across dedicated AWS EC2 hardware environments on Python
3.12.3,
x86_64 (x64)
- Instance: Intel(R) Xeon(R) Platinum 8488C (8C/16T)
- ISA: AVX-512BW
- Cache: L1d: 384 KiB · L1i: 256 KiB · L2: 16 MiB · L3: 105 MiB
- STREAM Triad: 25.76 GiB/s
AArch64 (arm64)
- Instance: AWS Graviton3 ARM Neoverse-V1 (16C/16T)
- ISA: NEON
- Cache: L1d: 1 MiB · L1i: 1 MiB · L2: 16 MiB · L3: 32 MiB
- STREAM Triad: 75.48 GiB/s
search_one
| Level | Payload | Latency (x64) | Latency (arm64) | Throughput (x64) | Throughput (arm64) |
|---|---|---|---|---|---|
| L1 Cache | 32 KiB | 304.09 ns | 864.09 ns | 100.36 GiB/s | 35.32 GiB/s |
| L2 Cache | 512 KiB | 6.89 µs | 11.93 µs | 70.82 GiB/s | 40.94 GiB/s |
| L3 Cache | 16 MiB | 488.96 µs | 397.55 µs | 31.96 GiB/s | 39.30 GiB/s |
| RAM | 256 MiB | 20.35 ms | 10.33 ms | 12.28 GiB/s | 24.21 GiB/s |
| RAM | 512 MiB | 41.72 ms | 20.94 ms | 11.98 GiB/s | 23.88 GiB/s |
| RAM | 1 GiB | 83.63 ms | 39.15 ms | 11.96 GiB/s | 25.54 GiB/s |
search_two
| Level | Payload | Latency (x64) | Latency (arm64) | Throughput (x64) | Throughput (arm64) |
|---|---|---|---|---|---|
| L1 Cache | 32 KiB | 611.86 ns | 1.67 µs | 49.88 GiB/s | 18.31 GiB/s |
| L2 Cache | 512 KiB | 10.77 µs | 24.31 µs | 45.33 GiB/s | 20.08 GiB/s |
| L3 Cache | 16 MiB | 558.87 µs | 768.98 µs | 27.96 GiB/s | 20.32 GiB/s |
| RAM | 256 MiB | 19.94 ms | 13.03 ms | 12.54 GiB/s | 19.18 GiB/s |
| RAM | 512 MiB | 41.67 ms | 26.06 ms | 12.00 GiB/s | 19.18 GiB/s |
| RAM | 1 GiB | 83.56 ms | 52.04 ms | 11.97 GiB/s | 19.22 GiB/s |
1 maintainer
Metadata
1 maintainer
Release files for ashwa 0.2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ashwa-0.2.4.tar.gz | 31.4 kB | Details |
Built distributions (wheels)
Total release size: 6.2 MB
Release files / ashwa-0.2.4.tar.gz
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| Tags | Linux glibc 2.17+ x86-32 PyPy 3.11 PyPy 3.11 7.3 |
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