Alternatives
Products that do what GoTorch – A Go Implementation of PyTorch does
I'm starting to implement a barebones version of pytorch in Go. The primary motivation is: 1. I want to better learn Pytorch and how it works so what better way than to just re-implement some of its core features. 2. I write mainly in Go and haven't come across a lot of ML support in Go 3. I'd rather have a Go ML service instead of spinning up additional infrastructure to just support a python ML service in my Go projects 4. Go's static typing, native concurrency (avoid GIL problem in python), efficient memory management, single binary deployment and more make it a better interface compared…
- 1IS
2022 · github.com
- 2IP
This started as a hard requirement for my TUI-based editor application, it ended up going in a few different directions. A suite of tools that help with semantic code entities: https://github.com/odvcencio/gts-suite A next-gen version control system called Got: https://github.com/odvcencio/got I think this has some pretty big potential! I think there's many classes of application (particularly legacy architecture) that can benefit from these kinds of analysis tooling. My next post will be about composing all these together, an exciting project I call…
Feb 2026 · github.com
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- 4GA
Recently, I write an interpreter for subset of Python using Go. I haven't seen source code of CPython, all is just written according to my understanding of Python so there may be some unusual things. Hope you can play fun with it. Any suggestion is welcome, glad to get some feedback.
2023 · github.com
- 5AN
No gc, No goroutines, Produces small binaries while using the unmodified official go toolchain, and comes with complete Web SDK (generated from w3c/webref). We are building `pcz` to provide a reimagination of Go the language, in an effort to make it suitable for all kinds of programming tasks, and currently you can use it to build efficient web applications in Go using the generated Web SDK (as shown with the live web demo[1]). The journey is just starting, any suggestions? or any critics? [1]: https://primecitizens.github.io/livedemos/10-plat-web/
2023 · github.com
- 6GT
2017 · golangbot.com
- 7GI
2018 · github.com
- 8AA
I spent the past 2 weeks making this toy programming language. I basically forked the Go scanner/parser, and changed the syntax to have functions return a single value. This enable proper Result/Option type to be used as well as propagating errors with an operator. I also wanted to have short "type inferred" anonymous functions to be able to use functions like Map/Reduce/Filter, without having to use 100 characters to specify the types.
2025 · github.com
- 9KY
2025 · github.com
- 10PA
I’m sure many of you are familiar, but there’s a treacherous gap between finding (or building) a model that works in PyTorch, and getting that deployed into your application, especially in consumer-facing applications. I’ve been very interested in solving this problem with a great developer experience. Over time, I gradually realized that the highest-impact thing to have was a way to go from existing Python code to a self-contained native binary—in other words, a Python compiler. I was already pretty familiar with a successful attempt: when Apple introduced armv8 on the iPhone 5s, they…
2025 · blog.fxn.ai
- 11GB
Hey HN, I just published v0.1.0 of go-bt and would love some feedback from the Go veterans here. Thanks in advance!
Apr 2026 · github.com
- 12GI
2019 · gocode.io
- 13IW
Hi HN! During the last few years, I worked on a few applications built with Go, running on AWS Lambda. As I got to know the platform better, I started to find Go & Lambda to be a really productive combination. The applications were fast, and they ended up being much cheaper to run than what my team & I had built before. It’s probably not the best platform for _every_ application, but I was surprised at how much of our workload worked well on it. As we brought new engineers on to our team and helped them get up to speed with the stack, I found that we were covering a lot of the same topics…
2021
- 14LF
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
- 15GA
Hey folks, wanted to show this off and get feedback. Still early/experimental but there are quite a few concepts I'm excited about here. This project came about while writing a program in Go and loving its approach to concurrency. Being a long-time Rubyist I immediately started to think about what similar concepts might look like in Ruby. I set out with two main design constraints: 1. Lightweight: I didn't want routines to be backed by fibers or threads. Having been involved some in the async project (https://github.com/socketry/async), I had some experience using…
2023 · github.com
- 16GV
2018 · made2591.github.io
- 17IC
A friend and I wrote a book on how to build and train Deep Learning models in Go. We wanted it to be a useful reference for deep learning basics for Go programmers. Deep Learning is slowly seeping into everything we use every day and we thought it would be great if more people could do it in Go. The book is available here and on Amazon as well. https://www.packtpub.com/big-data-and-business-intelligence/hands-deep-learning-go We would appreciate any feedback and we're always looking to improve.
2019
- 18IB
Hello, I'm the author of the nature programming language, which has reached an early usable version since its first commit in 2021 until today. --- Why implement such a programming language? go is a programming language that I use for my daily work, and the first time I used golang, I was amazed by its simple syntax, freedom of programming ideas, ease of cross-compilation and deployment, excellent and high-performance runtime implementations, and advanced concurrency style design based on goroutine, etc. But, golang also has some inconveniences - The syntax is too concise, resulting in a…
2025 · github.com
- 19
Learn PyTorch from scratch with simple examples.
Aug 2026 · khayyamshah2007.blogspot.com
- 20PC
Hi HN!I built *pyproc* to let Go services call Python like a local function — *no CGO and no separate microservice*. It runs a pool of Python worker processes and talks over *Unix Domain Sockets* on the same host/pod, so you get low overhead, process isolation, and parallelism beyond the GIL. *Why this exists* * Keep your Go service, reuse Python/NumPy/pandas/PyTorch/scikit-learn. * Avoid network hops, service discovery, and ops burden of a separate Python service. *Quick try (\~5 minutes)* Go (app): ``` go get github.com/YuminosukeSato/pyproc@latest ```…
Sep 2025 · github.com
- 21OS
We're a group of engineers, AI/ML enthusiasts, and author of this paper https://openreview.net/forum?id=0pxiMpCyBtr who saw a closed door in AI/ML and decided to open it. This project is a PyTorch reimagining of Google's TensorFlow Lattice models, which despite being labeled open-source, were previously open in name only (you have to be a Googler to contribute). Also, side point…TensorFlow is dying https://thenextweb.com/news/why-tensorflow-for-python-is-dyi... Here's the deal: Lattice models excel in making AI interpretable—key for sectors where…
2023 · github.com
- 22MA
I built a neural network library in golang on an autograd engine. Faster and easy to use like PyTorch. Please give it a try and share your feedback. if you like it, a github star will be appreciated.
2024 · github.com
- 23PK
I built a small, self-contained K-Means implementation in pure PyTorch: https://gitlab.com/hassonofer/pt_kmeans I was working on dataset sampling and approximate nearest neighbor search, and tried several existing libraries for large-scale K-Means. I couldn't find something that was fast, simple, and would run comfortably on my own workstation without hitting memory limits. Maybe I missed an existing solution, but I ended up writing one that fit my needs. The core insight: Keep your data on CPU (where you have more RAM) and intelligently move only the necessary chunks to…
2025
- 24OA
https://github.com/gugarosa/opytimizer Did you ever reach a bottleneck in your computational experiments? Are you tired of selecting suitable parameters for a chosen technique? If yes, Opytimizer is the real deal! This package provides an easy-to-go implementation of meta-heuristic optimizations. From agents to search space, from internal functions to external communication, we will foster all research related to optimizing stuff. Use Opytimizer if you need a library or wish to: - Create your optimization algorithm; - Design or use pre-loaded optimization tasks; -…
2021
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