Dev tools · alternatives · 2026

24 alternatives to Pyhoff – Connect Python ML Models to Beckhoff/WAGO IO Hardware

Built this Python package because I wanted to run hardware controlling ML stuff and other control algorithms directly connected to industrial I/O hardware without jumping into annoying PLC toolchains (Windows only, licensing hassle, no editor choice, proprietary version control - you name it). For sure its not for ms‑cycle loops, or uptime critical production stuff, but in applications with relaxed timing it allows for fast iteration on the setup - making prototyping a pleasure. Its easy to use, has no dependencies beside Python, its fully type annotated and MIT licensed. Internal it…

Pyhoff is a Python package that connects machine learning models and control algorithms directly to industrial input/output hardware from Beckhoff and WAGO. It eliminates the need for traditional PLC software chains by… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
I built a hardware processor that runs Python▲983
Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
2025 · runpyxl.com · its alternatives →
2
PyBroker – Algotrading in Python with Machine Learning▲70
Hello, I am excited to share PyBroker with you, a free and open-source Python framework that I developed for creating algorithmic trading strategies, including those that utilize machine learning. With PyBroker, you can easily develop and fine-tune trading rules, build powerful ML models, and gain valuable insights into your strategy's performance. Some of the key features of PyBroker include: - A super-fast backtesting engine built using NumPy and accelerated with Numba. - The ability to create and execute trading rules and models across multiple instruments with ease. - Access to…
2023 · github.com · its alternatives →
3
StackML▲252
Machine Learning platform in-browser, for creators
2019 · its alternatives →
4
Fullstack ML – From Notebooks to Deployment▲198
Contribute to xadrianzetx/fullstack.ai development by creating an account on GitHub.
2019 · github.com · its alternatives →
5
A modular Python TUI framework with a fast and pretty markup language▲114
PyTermGUI is a highly modular framework offering most of the features one would expect from a GUI library, such as a mature and open Widget API, animations, mouse support and other goodies, right inside the terminal! The markup language is another great feature of the library, and is used by practically all elements of it. It is based on Rich's implementation, but uses a more concise and easier to humanly parse syntax, while being over 10 times faster at parsing due to a long list of optimizations. There is a full Window Manager API included as well, allowing the user to move, resize and…
2022 · github.com · its alternatives →
6
Gradio 5.0▲224
connect nodes to build AI pipelines, powered by Hugging Face
2024 · gradio.app · its alternatives →
7
Apple MLX▲138
An array framework for machine learning on Apple silicon
2023 · pypi.org · its alternatives →
8
Xcessiv – Fully managed web application for automated machine learning▲108
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python. - reiinakano/xcessiv
2017 · github.com · its alternatives →
9
AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers▲46
Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
2025 · github.com · its alternatives →
10
GUIs for Faster ML Prototyping and Sharing▲85
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work! - gradio-app/gradio
2020 · github.com · its alternatives →
11PL
Python library to scan ML models for vulnerabilities▲20
Hi! I’ve been working on this automatic scanner for ML models to detect issues like underperforming data slices, overconfidence in predictions, robustness problems, and others. It supports all main Python ML frameworks (sklearn, torch, xgboost, …) and integrates with the quality assurance solution we are building at Giskard AI (https://giskard.ai) to systematically test models before putting them in production. It is still a beta and I would love to hear your feedback if you have the time to try it out. We have quite a few tutorials in the docs with ready-made colab notebooks to…
2023 · docs.giskard.ai · its alternatives →
12
AutoML Python Package for Tabular Data with Automatic Documentation▲67
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation - mljar/mljar-supervised
2022 · github.com · its alternatives →
13
Truss – Serve any ML model without boilerplate code▲68
The simplest way to serve AI/ML models in production - basetenlabs/truss
2022 · github.com · its alternatives →
14
Fritz for Python▲13
Faster mobile machine learning workflows
2019 · fritz.ai · its alternatives →
15
Mljar Studio – local AI data analyst that saves analysis as notebooks▲73
Hi HN, I’ve been working on mljar-supervised (open-source AutoML for tabular data) for a few years. Recently I built a desktop app around it called MLJAR Studio. The idea is simple: you talk to your data in natural language, the AI generates Python code, executes it locally, and the whole conversation becomes a reproducible notebook (*.ipynb file). So instead of just chatting with data, you end up with something you can inspect, modify, and rerun. What MLJAR Studio does: - Sets up a local Python environment automatically, runs on Mac, Windows, and Linux - Installs missing packages during the…
May 2026 · mljar.com · its alternatives →
16
LeanRL: Fast PyTorch RL with Torch.compile and CUDA Graphs▲53
We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
17
OrchestraML▲82
From English prompt to deployed ML model with human approval
Jun 2026 · orchestra-ml.vercel.app · its alternatives →
18
MLConsole – web app to train ML models, for free and client-side▲86
ML Console is a free tool to build an AI model without writing a single line of code. Simply pick a column to predict, and let us handle the rest.
2021 · mlconsole.com · its alternatives →
19
Pykov – a tiny Python module on finite regular Markov chains▲37
Pykov is a Python module on finite regular Markov chains. - riccardoscalco/Pykov
2014 · github.com · its alternatives →
20
Build Machine Learning Web-Service with Python and Django▲67
My Machine Learning Web Service. Contribute to pplonski/my_ml_service development by creating an account on GitHub.
2020 · github.com · its alternatives →
21
Compile ML models into dependency-free source code for easy deployment▲37
I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc... Why do we need all these libraries and runtimes with all the overhead, compatibility issues and other headaches, when it's just some math to be executed? So I made a compiler that simply converts the model into plain source code with no dependencies, and it actually solved all my deployment problems. Now I'm curious if it can help anyone else too. Through the link you can submit your model file (Keras h5, onnx soon to be supported), and I'll…
2023 · waveworks.dk · its alternatives →
22
UnionML▲77
The easiest way to build and deploy ML microservices
2022 · union.ai · its alternatives →
23
Pywebagent – an AI that turns website functionality into Python APIs▲8
Hello everyone! My friend Ori Kabeli and I have been playing around with GPT-4 Vision as a way to control websites and complete complicated tasks online. We created a small proof of concept python package called pywebagent. pywebagent allows performing high level tasks in websites, accessible to developers as simple python functions. It is highly experimental, and only sometimes works, but we think it still might be useful to all you tinkerers out there. Feel free to contribute! Example Use Case: You can order things from amazon with one line of code. pywebagent.act(…
2023 · github.com · its alternatives →
24
My TUI library, PyTermGUI now features an intelligent layout system▲15
This was by far the most common missing feature of the library since my first post, so I'm really happy I managed to figure it out. See the release for some code examples and a detailed changelog, and most importantly, have a great day!
2022 · github.com · its alternatives →

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