Alternatives
Products that do what WASM runtime for sandboxing Python code does
A while ago I started experimenting with compiling the Python interpreter to WASM. To build a secure, fast, and lightweight sandbox for code execution — ideal for running LLM-generated Python code.
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Inspired by Simon Willison's blog post that was catalyzed by this HN post: https://news.ycombinator.com/item?id=34598024 wasm_exec is a Wasm-powered, sandboxed implementation of exec() for safely running dynamic Python code There are number of use-cases emerging that require arbitrary code execution, often code that is generated by LLMs (Large Language Models) like ChatGPT. This can enable some really cool functionality - like generative BI or website generation - but also introduce a massive security flaw if implemented via eval() or exec(). This is because arbitrary code can…
2023 · github.com
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2017 · github.com
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2021 · repl.leaningtech.com
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2020 · blog.yifangu.com
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As developers, we've used StackOverflow, blogs, tutorials, etc to solve our day-to-day code issues and we've been able to find answers to virtually all of our questions. At the same time, CodePen, CodeSandbox, JSFiddle, etc have made it simple to share and execute code for frontend developers but when I look for folks working at the backend side (preferably Python) there is nothing that entices the whole developer community yet. While other Python sandbox solutions are available, they do not provide installation choices or are not intended for embedding and sharing. With this thought, we…
2022 · pythonsandbox.dev
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We made this extension that lets you run any python code on the web by using Pyodide. You can try it by installing this VSCode extension on GitHub.dev / VSCode.dev. Since it is using pyodide to run python code, there are some limitations which we have listed in the extension’s README page. We made this scrappy extension quickly as a POC for Stanford’s Code in Place program. Let us know if this is interesting and what features should we add next!
2022 · marketplace.visualstudio.com
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We combined Stanford's ACE (agents learning from execution feedback) with the Reflective Language Model pattern. Instead of reading traces in a single pass, an LLM writes and runs Python in a sandbox to programmatically explore them - finding cross-trace patterns that single-pass analysis misses. The framework achieved 2x consistency improvement on τ2-bench.
Mar 2026 · github.com
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2016 · github.com
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Hey HN community, I'm excited to share Starfyre, a cutting-edge library that enables you to create front-end applications by leveraging the power of Python. It's perfect for those who love Python and want to extend its capabilities to frontend development. Key Features: * Reactive Frontend Development: Starfyre allows you to build reactive frontends using only Python. This means you can create highly interactive and real-time applications with ease. * Effortless Interactive Application Creation: With Starfyre, the process of creating interactive applications becomes straightforward. You…
2023 · github.com
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Recently, I saw few Python accelerators getting a lot of attention, and I thought it would be a good time to finally present the project that we will make available to test in the upcoming days. Flyable is an ahead-of-time compiler that takes your Python code, analyses it, and outputs very optimized machine code. Micro-benchmarks show that it produces programs that run between 10-70x time faster than Python. Flyable is certainly one of the fastest and easiest ways to accelerate your Python code. It finally allows Python to compete in the ring of fast and efficient languages without having to…
2020
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https://github.com/wandwan/LPY (April Fools)
2024 · github.com
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I've spent the past couple of weeks building a Wasm-to-Go translator. It supports a subset of Wasm useful enough to translate SQLite into 600k LoC (~20 MiB) of Go code. It already passes all of my Go SQLite driver's tests across the 20 platforms I support. Performance compared to https://wazero.io/ is a bit of a mixed bag: code that frequently crosses the Go-Wasm boundary improves, but code that spends most of its time in "Wasm land" doesn't. There's probably room for improvement (I'd love to hear your ideas), but this is also a testament to how good the wazero AOT compiler…
Feb 2026 · github.com
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You write a standard solution, just like on LeetCode, and run it through the CLI. It identifies the problem by ID or title, executes your code against local test cases, and shows the result. It currently supports around 1000 problems and multiple languages, including Python, C++, Rust, Java, Go, TypeScript, Swift, and others. The project is still an MVP. System design, SQL, and concurrency problems are not supported yet, but support for more problem types is planned. Made in Haskell!
25d ago · github.com
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2023 · github.com
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Hi HN, I built ast-visualizer.com because I wanted a way to visualize the architecture/structure of a Python repo before dived into the code. Most tools tell you what the code does; I wanted to see how it's built. The Problem: Onboarding onto a large codebase is a nightmare. LLMs help with single functions, but they struggle to show you the "God Objects," circular dependencies, or high-complexity hotspots across 50+ files. What it does: Dependency Graph: Visualizes imports and file complexity to find architectural bottlenecks. Radial AST Heatmaps: Maps individual files and color-codes…
Feb 2026 · ast-visualizer.com
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I found a serious bottleneck in Python binding of Wasmer and Wasmtime and I found a trick to make 25x faster. Then beat all that using NumPy.
2023 · medium.com
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I'm working on a FOSS project to teach Python Programming by writing code that interacts with a Minecraft world. Full instructions and tutorials are provided in the documentation. Please try out out and give some feedback!
2022 · github.com
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You build LLM applications with YAML files, that define an execution graph. Nodes can be either LLM API calls, regular function executions or other graphs themselves. Because you can nest graphs easily, building complex applications is not an issue, but at the same time you don't lose control. The YAML basically states what are the tasks that need to be done and how they connect. Other than that, you only write individual python functions to be called during the execution. No new classes and abstractions to learn.
2024 · github.com
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