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- 1OP
Hey HN, I just launched this online Python compiler which lets you use popular Python libraries like requests, Matplotlib, Plotly, Pandas, NumPy etc. online. It uses Pyodide to execute Python in the browser using WebAssembly.
2025 · cliprun.com
- 2AS
Hi all! A little background: I've been working on natto.dev, a spatial environment for JavaScript. I'm really excited about new interfaces for code (leveraging metaphors we're good at, spatial reasoning, making state visible, design tools, etc). With all the buzz around PyScript, I discovered Pyodide and got it working inside natto. This Python version is a stripped down version of https://natto.dev (eg interactive outputs, multiplayer) so please check that out if this interests you. I'm excited to share this spatial environment for Python. Imagine Jupyter cells arranged on a 2D…
2022 · python.natto.dev
- 3IB
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
- 4PT
2024 · pykidos.github.io
- 5RT
I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files. Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as…
Apr 2026 · github.com
- 6AP
2020 · github.com
- 7PA
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
- 8SP
Hey HN, Scripton (https://scripton.dev) is a Python IDE built for fast, interactive visualizations and exploratory programming — without the constraints of notebooks. Why another Python IDE? Scripton hopes to fill a gap in the Python development ecosystem by being an IDE that: 1. Focuses on easy, fast, and interactive visualizations (and exposes rich JS plotting libraries like Observable Plot and Plotly directly to Python) 2. Provides a tightly integrated REPL for rapid prototyping and exploration 3. Is script-centric (as opposed to, say, notebook-style) A historical detour for why…
2025 · scripton.dev
- 9FA
Some highlights: - 100% free and open source (https://github.com/alexmojaki/futurecoder), no ads or paid content. - No account required at any point. You can start instantly. (You can create an account if you want to save your progress online and across devices. Your email is only used for password resets) - 3 integrated debuggers can be started with one click to show what your code is doing in different ways. - Enhanced tracebacks make errors easy to understand. - Useful for anyone: You can have the above without having to look at the course. IDE mode…
2023 · futurecoder.io
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- 11GA
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
- 12ET
We (me and @aarondia) built a tool to help you turn psuedo-software Excel files into real-software Python. Ideally, Pyoneer helps you automate your manual Excel processes. You can try it today here: https://pyoneer.ai. How it works: 1. You upload an Excel file 2. We statically parse the Excel file and build a dependency graph of all the cells, tables, formulas, and pivots. 3. We do a graph traversal, and translate nodes as we hit them. We use OpenAI APIs to translate formulas. There’s a bunch of extra work here — because even with the best prompt engineering a fella like me can do,…
2024 · pyoneer.ai
- 13PC
Hello and happy new year! We're excited to introduce the Pyper package for concurrency & parallelism in Python. Pyper is a flexible framework for concurrent / parallel data processing, following the functional paradigm. Source code can be found on [github](https://github.com/pyper-dev/pyper) Key features: Intuitive API: Easy to learn, easy to think about. Implements clean abstractions to seamlessly unify threaded, multiprocessed, and asynchronous work. Functional Paradigm: Python functions are the building blocks of data pipelines. Let's you write clean, reusable…
2025 · github.com
- 14IB
Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com
- 15PA
2025 · github.com
- 16MM
2021 · everydayanchovies.github.io
- 17P5
- 18
Save 30% of dev time - generate tests without writing code
2023
- 19PD
2017 · github.com
- 20GI
2018 · github.com
- 21AT
A bunch of developers and myself have created RepliByte - an open-source tool to seed a development database from a production database. Features: - Support data backup and restore for PostgreSQL, MySQL and MongoDB - Replace sensitive data with fake data - Works on large database (> 10GB) (read Design) - Database Subsetting: Scale down a production database to a more reasonable size - Start a local database with the prod data in a single command - On-the-fly data (de)compression (Zlib) - On-the-fly data de/encryption (AES-256) - Fully stateless (no server, no daemon) and lightweight…
2022
- 22PT
2017 · github.com
- 23AL
Hey HN! I built a local Python prototyping tool that is finally the Python development environment I've always wanted. It has a Jupyter notebook for data crunching, a database of your choice (Python or MongoDB), and a Streamlit app for building a frontend visualization. You can edit the Streamlit backend via an embedded VSCode editor, or locally on your own IDE. The best part for me is that the database connectors within Jupyter and Streamlit are configured out-of-the-box, so you don't need to spend time thinking about how to tie all that together - you can just pick the database you want to…
2023 · github.com
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