惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
T
Troy Hunt's Blog
Scott Helme
Scott Helme
T
Threat Research - Cisco Blogs
T
Tenable Blog
L
LINUX DO - 热门话题
V
Visual Studio Blog
I
Intezer
Blog — PlanetScale
Blog — PlanetScale
Cisco Talos Blog
Cisco Talos Blog
A
Arctic Wolf
C
Cyber Attacks, Cyber Crime and Cyber Security
F
Fortinet All Blogs
aimingoo的专栏
aimingoo的专栏
Know Your Adversary
Know Your Adversary
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
N
Netflix TechBlog - Medium
SecWiki News
SecWiki News
I
InfoQ
Microsoft Security Blog
Microsoft Security Blog
Project Zero
Project Zero
W
WeLiveSecurity
Microsoft Azure Blog
Microsoft Azure Blog
A
About on SuperTechFans
Recorded Future
Recorded Future
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Vercel News
Vercel News
S
Securelist
Spread Privacy
Spread Privacy
L
LangChain Blog
云风的 BLOG
云风的 BLOG
G
Google Developers Blog
MongoDB | Blog
MongoDB | Blog
Google DeepMind News
Google DeepMind News
Recent Commits to openclaw:main
Recent Commits to openclaw:main
D
Darknet – Hacking Tools, Hacker News & Cyber Security
C
CERT Recently Published Vulnerability Notes
罗磊的独立博客
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
The Last Watchdog
The Last Watchdog
Attack and Defense Labs
Attack and Defense Labs
博客园 - 司徒正美
Help Net Security
Help Net Security
L
Lohrmann on Cybersecurity
人人都是产品经理
人人都是产品经理
Forbes - Security
Forbes - Security
Hacker News - Newest:
Hacker News - Newest: "LLM"
PCI Perspectives
PCI Perspectives
博客园 - 【当耐特】
T
Tor Project blog

Hacker News: Show HN

PurrrrrFocus: Pomodoro Timer App - App Store Workflow Engine — Multi-Step Orchestration for Bun RapidPhoto: Pro Photo Editor App - App Store GitHub - DheerG/swarms: Achieve extraordinary results with claude code across a variety of tasks SPICE simulation → oscilloscope → verification with Claude Code — Lucas Gerads Show HN: VCoding – A 5 MB native Windows IDE with no dynamic dependencies Show HN: LLMs don't hallucinate because they're bad at math, it's the format GitHub - Agent-FM/agentfm-core: AgentFM is a peer-to-peer network that turns everyday computers into a decentralized AI supercomputer. AgentFM lets you run massive AI workloads directly across a global mesh of idle CPUs and GPUs. Show HN: Tracking Top US Science Olympiad Alumni over Last 25 Years GitHub - Potarix/agent-hub: One place to talk to all your agents Show HN: Runtime security for AI agents(injection,tool abuse, data exfiltration) GitHub - dubeyKartikay/lazyspotify: Terminal Spotify client for macOS and Linux GitHub - the-banana-tool/king-louie: Easy to use GUI Personal AI Assistant. Win/Linux/Mac. Show HN I made my vacation rental bookable by AI agents–no Airbnb, 0% commission GitHub - basteez/jsf-autoreload: maven plugin to enable hot reload on jsf projects uvm32/hosts/host-gdbstub at main · ringtailsoftware/uvm32 GitHub - labsai/EDDI: Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus. GitHub - glitchnsec/fortyone-oss: AI Executive Assistant Platform Quickstart | Alien GitHub - muxshed/shed: One stream in, or many. Every destination, simultaneously. No cloud middleman, no per-channel fees, no limits. GitHub - ocrbase-hq/ocrbase: 📄 PDF/IMG ->.MD/JSON Document OCR API for PaddleOCR and GLMOCR. Self-hostable. GitHub - impactjo/home-memory: MCP server that lets your AI assistant remember everything about your home. GitHub - Sets88/dbcls: DbCls is a powerful terminal database client that supports various databases GitHub - neptun2000/heor-agent-mcp GitHub - SeanFDZ/macmind: Single-layer transformer in HyperTalk for the classic Macintosh RollQuation: Math Puzzles - Apps on Google Play GitHub - dropbox/witchcraft Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis GitHub - opentalon/opentalon: OpenTalon is an open-source platform built from the ground up in Go as a robust alternative to OpenClaw LinkedIn™ 职位抓取工具 - Chrome 应用商店 GitHub - EdoardoBambini/Agent-Armor-Iaga: AI agents are getting tool access — shell, file system, databases, APIs, secrets. But **nobody is governing what they actually do with it**. Frameworks like LangChain, CrewAI, AutoGen, and Claude Code give agents the power to execute. Agent Armor gives you the power to control, audit, and approve every single action before it happens. HN Vibes — Week 15, Apr 7–13 2026 GitHub - chojs23/ec: Easy terminal-native 3-way git mergetool vim-like workflow GitHub - SethPyle376/hiraeth: Local AWS emulator focused on fast integration testing, with SQS support, SQLite-backed state, and a debug-friendly web UI. GitHub - JakOb-dotcom/cloud-sandbox-security-analysis: Technical analysis and Proof of Concept (PoC) regarding environment variable exfiltration in containerized cloud sandboxes via side-channel data leaks. Springboards - Flint Alpha Show HN: A simpler coding agent harness GitHub - audiodude/sudomake-friends GitHub - 256thFission/mini-mythos: OSS clone of Anthropic’s Mythos harness to locate C/C++ memory vulnerabilities Show HN: OpenParallax: OS-level privilege separation for AI agent execution Hacker News Sorted - Chrome 应用商店 Show HN: How to Install Docker on Ubuntu 24.04 LTS: Complete 2026 Guide GitHub - himanshudongre/smriti GitHub - sverrirsig/claude-control: macOS desktop dashboard for monitoring and managing multiple Claude Code sessions GitHub - ory/dockertest: Write better integration tests! Dockertest helps you boot up ephermal docker images for your Go tests with minimal work. Chiral - Chrome 应用商店 Show HN: Two Claudes collaborating through shared memory on a $100 mini-PC GitHub - pmichaillat/latex-cv: Minimalist LaTeX template for academic CVs GitHub - oguzbilgic/posse: A web UI for Anthropic Managed Agents. GitHub - sshiraz/depsly: Dependency risk analysis tool for npm packages ABI Add safari/agent-harness — Safari browser automation via safari-mcp by achiya-automation · Pull Request #212 · HKUDS/CLI-Anything GitHub - Halfblood-Prince/trustcheck: Verify PyPI package attestations and improve Python supply-chain security GitHub - oguzbilgic/kern-ai: Agents that do the work and show it. GitHub - bruits/satteri: High-performance Markdown and MDX processing for the JavaScript ecosystem GitHub - tylergibbs1/feedstock: High-performance web crawler and scraper for TypeScript, powered by Bun and Playwright GitHub - Grimm67123/grimmbot: The self-improving sandboxed and open-source AI agent. With persistent memory and scheduling. GitHub - whitevanillaskies/whitebloom: Local whiteboard that blooms. GitHub - hwdsl2/docker-whisper: Docker image for a self-hosted Whisper speech-to-text server with speaker diarization and OpenAI-compatible transcription and translation APIs. Powered by faster-whisper. Supports all Whisper models, NVIDIA GPU (CUDA) acceleration, JSON/SRT/VTT output, SSE streaming, offline mode, and multi-arch (amd64, arm64). GitHub - yisding/reviewwiggum GitHub - MarwanAlsoltany/serrors: Structured errors for Go: sentinel hierarchies, typed data, custom formatting, and slog integration. GitHub - soatok/age-php GitHub - Luthiraa/markitme GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits GitHub - tombedor/excalicharts GitHub - wh1le/excalidraw-edit: Open and edit .excalidraw files from the terminal. Offline, auto-saves to disk. MalExt Sentry - Malicious Extension Scanner - Chrome 应用商店 GitHub - syi0808/asciianimesvg: Generate animated ASCII art SVGs from text. CLI, Rust library, WASM, and web editor. GitHub - zaina-ml/ml_forge: A visual-based graph node editor for training computer vision models. GitHub - anakin87/llm-rl-environments-lil-course: 🌱 A little course on Reinforcement Learning Environments for evaluating and training Language Models GitHub - takaakit/superpowers-uml: Superpowers-UML modifies Superpowers to ensure a software development workflow in which AI agents design through UML modeling. AdriByte Studio - Sviluppo Web e Soluzioni Digitali GitHub - chouligi/angel-copilot: Your personalized Angel Investment Advisor Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 GitHub - agenteractai/lodmem: Level Of Detail Context Management for Agents GitHub - ostefani/subnetlens: A fast, concurrent network scanner with a TUI and plain-text CLI, built in Go. It discovers live hosts on your network, scans their open ports, resolves hostnames, and fingerprints operating systems—delivered. Cyber Pulse: Agentic Intel - Apps on Google Play Whisper API: Self-Hostable Speech to Text Transcription The Agent-Web Protocol Stack: A Research Thesis GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Show HN: Provepy – A Python decorator that proves your code using Lean and LLMs Show HN: Pardonned.com – A searchable database of US Pardons GitHub - patrickdappollonio/dux: Dux is a terminal UI that lets you run multiple AI coding agents side by side, each in its own git worktree, with full companion terminals, macros, commit generation, and a command palette that knows more tricks than you do. kMC Crystal Simulator Show HN: HyperFlow – A self-improving agent framework built on LangGraph GitHub - stef41/vibescore: 🎵 Grade your vibe-coded project. One command, instant letter grade across security, quality, dependencies, and testing. GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. imgur.com GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. GitHub - nowork-studio/toprank: Open-source Claude Code skills for SEO, SEM, Google Ads GitHub - tacomanator/sash: Lightweight macOS menu bar app for reliably cycling through windows of the current application. Appents | Social Media Management for Product-First Teams GitHub - pnhoang/youtube-spam-blocker: Automatically detects and hides spam messages in YouTube Live chat. Set rate limits, keyword filters, and block repeat offenders. GitHub - decisionnode/DecisionNode: CLI + Local MCP - A shared structured memory store across Claude Code, Cursor, Windsurf, Antigravity, and every MCP client. Semantically queryable. GitHub - AvaCodeSolutions/django-email-learning: An open source Django app for creating email-based learning platforms with IMAP integration and React frontend components. The $100K Gap in Kubernetes Security Tooling Function Calling Harness: From 6.75% to 100%
GitHub - SGavrl/WfmOxide: A zero-copy, high-performance Rust parser for proprietary oscilloscope binary files (Rigol/Tektronix) with PyO3 Python bindings.
Galo43 · 2026-05-10 · via Hacker News: Show HN

PyPI version License: MIT CI

WfmOxide is a zero-copy parser for proprietary oscilloscope binary files (e.g., Rigol .wfm, Tektronix). Written in Rust with PyO3 bindings, it provides a high-performance backend alternative to pure-Python implementations like RigolWFM, optimized for deep-memory data pipelines.

Performance Benchmark Comparison Figure 1: End-to-end execution latency across supported hardware families.

Architecture & Performance

  • Zero-Copy I/O: Utilizes memmap2 to map files directly into virtual memory. It avoids allocating memory for the raw binary payload, scaling efficiently across thousands of files.
  • Direct Array Construction: De-interleaves ADC bytes and applies voltage conversion mathematics in a single Rust pass, writing directly to a contiguous NumPy float32 array.
  • Parallel Execution: Employs multi-threaded iteration during channel extraction via rayon, maximizing core utilization while the Python Global Interpreter Lock (GIL) is released.
  • Throughput: For metadata and raw byte extraction, the pure Rust core executes in sub-millisecond timeframes (e.g., ~90µs for DS1000Z payloads), representing a multi-order-of-magnitude reduction in latency compared to standard interpreter overhead.

Empirical Benchmarks

The following data details total end-to-end extraction latency, encompassing file I/O, metadata parsing, hardware-specific voltage scaling, and zero-copy transfer into the Python memory space.

To establish a conservative baseline, tests were conducted on resource-constrained hardware (Intel Core i5-6300U, 2 Physical Cores, Arch Linux). Deployments utilizing modern multi-core workstations will observe proportionally higher parallel scaling.

Oscilloscope Family Payload Size Data Points Reference Python Parser WfmOxide (Rust) Relative Speedup
Rigol DS1000Z 12.0 MB 3.0 M 375.2 ms 53.5 ms 7.0x
Rigol DS1000E 1.0 MB 1.0 M 13.1 ms 2.7 ms 4.8x
Rigol DS2000 14.0 MB 7.0 M 153.7 ms 22.6 ms 6.8x
Tektronix (WFM) 6.0 MB 6.0 M 136.7 ms 24.1 ms 5.6x

Support Matrix

Binary formats vary heavily by manufacturer and firmware version. Support is implemented on a per-family basis. The "Time axis" column tracks whether WfmFile::time_axis() (and the Python sample_rate / x_origin / x_increment / get_time_axis() accessors) returns a value for that family.

Manufacturer Family Decode Time axis Per-channel metadata
Rigol DS1000Z (e.g., DS1054Z) scale, offset, coupling, probe, inverted
Rigol DS1000E/D scale, offset, probe, inverted
Rigol DS2000 scale, offset, coupling, probe, inverted
Rigol DS4000 ✓ (origin approximate) scale, offset, coupling, probe, inverted
Rigol DHO800 / DHO1000 (12-bit, ZLib metadata) scale, offset
Tektronix TDS/DPO/MSO (WFM#001-003) scale, offset
Tektronix TDS 210, TDS 1000, TPS 2024 (ISF) scale, offset

Installation & Setup

WfmOxide is distributed as pre-compiled wheels via PyPI. For standard usage, no local Rust toolchain is required.

Standard Installation (Recommended)

pip install wfm-oxide

Building from Source

For development purposes or deployment on unsupported architectures, WfmOxide can be compiled directly from source using maturin.

git clone https://github.com/SGavrl/WfmOxide.git
cd WfmOxide

python3 -m venv .venv
source .venv/bin/activate

pip install maturin numpy
maturin develop --release

Reproducible Environment (Nix)

For environments utilizing the Nix package manager, a shell.nix is provided in the repository root to lock the exact Rust toolchain and Python dependencies required for compilation.

# Enter the isolated build environment
nix-shell 

# Build the Rust extension
maturin develop --release

Python API

The Python interface returns standard NumPy arrays and exposes both the voltage data and the surrounding capture metadata.

import numpy as np
from wfm_oxide import WfmOxide

# Memory-map the file
wfm = WfmOxide("DS1054Z-Capture.wfm")

print(f"Model: {wfm.model}")
print(f"Firmware: {wfm.firmware}")
print(f"Enabled Channels: {wfm.enabled_channels}")

# --- Voltage data --------------------------------------------------
# Whole channel:
ch1_volts = wfm.get_channel_data(1)

# Or a slice (useful on deep-memory captures):
ch1_slice = wfm.get_channel_data(1, start=5000, length=10000)

# All channels at once. Disabled channels come back as None.
all_channels = wfm.get_all_channels()

# --- Time axis -----------------------------------------------------
# Returns None for formats that do not expose a time axis (DS1000E, Tek WFM).
print(f"Sample rate: {wfm.sample_rate} Hz")
print(f"x_origin: {wfm.x_origin} s, x_increment: {wfm.x_increment} s")

times = wfm.get_time_axis()  # NumPy float64, same length as channel data
times_slice = wfm.get_time_axis(start=5000, length=10000)

# --- Per-channel acquisition settings -----------------------------
print(wfm.channel_metadata(1))
# {'channel': 1, 'vertical_scale': 1.0, 'vertical_offset': -0.5,
#  'inverted': False, 'coupling': 'DC', 'probe_ratio': 10.0}

Properties and methods that may return None do so when the underlying format does not record that information; never as a soft error.

Command-Line Interface

WfmOxide also ships a wfm-oxide binary in the crates/wfm_oxide_cli crate for shell pipelines and one-off conversions, with no Python dependency.

# Build the CLI (release):
cargo build --release -p wfm_oxide_cli

# Or install on PATH:
cargo install --path crates/wfm_oxide_cli

info — capture metadata

$ wfm-oxide info DS1054Z-Capture.wfm
File:     DS1054Z-Capture.wfm
Model:    DS1104Z
Firmware: 00.04.04.SP3
Channels: 2 enabled (CH1, CH2)
Sample rate: 25.0000 MSa/s
Sample step: 40.0000 ns
Capture:     2.4102 ms (60256 samples)
Time origin: -1.2051 ms
  CH1: 60256 samples, 1.0000 V/div, offset -500.0000 mV, coupling DC, probe 10x
  CH2: 60256 samples, 1.0000 V/div, offset -1.4600 V, coupling DC, probe 10x

info reads only the file header — sub-millisecond even on multi-million-sample captures. Pass --json to emit a machine-readable summary suitable for piping into jq or downstream tooling.

convert — CSV / NPY export

# Single file → time-stamped CSV (one column per enabled channel)
wfm-oxide convert capture.wfm -o capture.csv

# Single channel → 1-D NPY
wfm-oxide convert capture.wfm -o ch1.npy --channel 1

# All channels → structured NPY (np.load(...)['time'], np.load(...)['CH1'], ...)
wfm-oxide convert capture.wfm -o capture.npy

# Slice a region without decoding the rest
wfm-oxide convert capture.wfm -o slice.csv --start 1000 --length 50000

# Batch: convert many captures into a directory
wfm-oxide convert *.wfm --out-dir converted/ --format csv

By default convert writes a leading time column (CSV) or a structured ('time', 'CH1', ...) dtype (NPY) when the format exposes a time axis. Pass --no-time to omit it.

Repository Layout

The crate is organised as a Cargo workspace so the CLI's dependencies (clap, serde, ...) do not leak into the Python wheel.

WfmOxide/
├── crates/
│   ├── wfm_oxide/          # Rust library (cdylib + rlib); feeds the Python wheel via maturin
│   │   └── src/            # mmap.rs, parser.rs, sample.rs, dho.rs, structs.rs, lib.rs
│   └── wfm_oxide_cli/      # `wfm-oxide` binary, depends on wfm_oxide as a path dependency
├── python/wfm_oxide/       # Python wrapper around the compiled extension
├── tests/                  # pytest suite, validated against RigolWFM as the reference
└── test_data/              # sample captures used by the test suite

Extending Device Support

The architecture is modular to allow for the rapid addition of new oscilloscope models. To contribute support for a new device:

  1. Define the Header: Map the byte layout using the reference .ksy files in the RigolWFM repository. Implement the equivalent Rust struct in crates/wfm_oxide/src/structs.rs using binrw (or — for formats that need runtime work like ZLib decompression — a dedicated module such as dho.rs).
  2. Update Detection: Register the model's magic bytes or header string in the WfmFile::open matcher within crates/wfm_oxide/src/mmap.rs.
  3. Implement Parser Logic: Add a model-specific parsing routine (e.g., get_channel_data_2000) to crates/wfm_oxide/src/parser.rs. The shared Affine + SampleType machinery in sample.rs handles the inner byte-to-volts loop for variable bit-depth ADCs, so each new format only needs to derive the per-channel transform.
  4. Route the API: Add the new variant to the WfmHeader enum and extend the dispatch in WfmFile::extract_channel, time_axis, channel_metadata, and channel_sample_count. Re-exports in crates/wfm_oxide/src/lib.rs flow through to both the Python bindings and the CLI without further work.

License & Acknowledgements

WfmOxide is released under the MIT License.

This project relies on the extensive reverse-engineering documentation compiled by the open-source community. The binary format specifications, memory offsets, and mathematical models used to build the Rust structs are ported from the RigolWFM project.

RigolWFM License (BSD 3-Clause): Copyright (c) 2020-23, Scott Prahl. All rights reserved.