Analysis updated 2026-05-18
Explore an alternative visual programming approach to LabVIEW-style block diagrams.
Review before deciding whether to trust the linked download for instrument control work.
Compare its claimed FPGA and data acquisition features against established open source tools.
| eltohamy932/ni-labview-studio-tools | jasonengcc/keyshot-studio-materials | jhema123/marmoset-pipeline-bundle | |
|---|---|---|---|
| Stars | 57 | 57 | 57 |
| Language | HTML | HTML | HTML |
| Setup difficulty | hard | easy | moderate |
| Complexity | 4/5 | 1/5 | 2/5 |
| Audience | general | designer | general |
Figures from each repo's GitHub metadata at analysis time.
Feature claims are heavy but working code examples are light, and the repo tags reference cracked software.
This repository presents itself as an open-source, community-built alternative to NI LabVIEW, the commercial graphical programming environment used in test, measurement, and control engineering. The authors frame it as a "reconstruction" of LabVIEW's design principles rather than a copy of its proprietary software. According to the README, the project targets engineers who work with data acquisition hardware, laboratory instruments, and FPGA chips but want to avoid the cost of a commercial LabVIEW license. The core idea is a visual, drag-and-drop programming style where you connect blocks on a diagram instead of writing lines of text code. The project claims to ship a custom visual scripting layer called G, which compiles those block diagrams and runs them on top of Python. It also describes a hardware abstraction layer meant to work with NI data acquisition devices, Measurement Computing boards, and even Arduino boards. Four main use areas are described. Data acquisition covers reading sensors and logging voltage signals. Instrument control covers sending commands to oscilloscopes, multimeters, and similar lab equipment over standard interfaces. FPGA targeting covers deploying logic designs to Xilinx hardware using open-source toolchains. Real-time control covers running feedback loops and state machines at deterministic timing rates. The README lists compatibility with Windows 10 and 11, macOS (in beta), several Linux distributions, and Raspberry Pi in a limited form. It also describes integration with OpenAI and Anthropic APIs to let users describe a measurement task in plain language and have the AI generate the corresponding wiring diagram. The project is small, with 57 stars, and the README is heavy on feature claims and light on working code examples. The repository description references "crack" and "pro software" in its tags, which conflicts with the README's claim that no proprietary NI binaries are included. Readers should approach the project with that inconsistency in mind.
A small project pitched as an open source, drag-and-drop alternative to NI LabVIEW for lab instrument control and data acquisition, though its tags reference cracked software.
Mainly HTML. The stack also includes Python, YAML, FPGA toolchain.
Setup difficulty is rated hard, with roughly 1day+ to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.