Xpandas – running Pandas-style computation directly in pure C++
Hi HN, I’ve been exploring whether pandas can be used as a computation description, rather than a runtime. The idea is to write data logic in pandas / NumPy, then freeze that logic into a static compute graph and execute it in pure C++, without embedding Python. This is not about reimplementing pandas or speeding up Python. It’s about situations where pandas-style logic is useful, but Python itself becomes a liability (latency, embedding, deployment). The project is still small and experimental, but it already works for a restricted subset of pandas-like operations and runs…
What it does
In the maker’s words, at launch
Hi HN, I’ve been exploring whether pandas can be used as a computation description, rather than a runtime. The idea is to write data logic in pandas / NumPy, then freeze that logic into a static compute graph and execute it in pure C++, without embedding Python. This is not about reimplementing pandas or speeding up Python. It’s about situations where pandas-style logic is useful, but Python itself becomes a liability (latency, embedding, deployment). The project is still small and experimental, but it already works for a restricted subset of pandas-like operations and runs deterministically in C++. Repo: https://github.com/CVPaul/xpandas I’d love feedback on whether this direction makes sense, and where people think it would break down.
Does the same job
all alternatives →- PSProbly – Spreadsheets, Python, and AI in the browser2025 · github.com · ▲171
Probly was built to reduce context-switching between spreadsheet applications, Python notebooks, and AI tools. It’s a simple spreadsheet that lets you talk to your data. Need pandas analysis? Just ask in plain English, and the code runs right in your browser. Want a chart? Just ask. While there are tools available in this space like TheBricks, Probly is a minimalist, open-source solution built with React, TypeScript, Next.js, Handsontable, Hyperformula, Apache Echarts, OpenAI, and Pyodide. It's still a work in progress, but it's already useful for my daily tasks.
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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…
- WAW++ – A Python-style scripting language for .NET with NuGet support2025 · github.com · ▲98
Hey HN I’ve been building *W++*, a scripting language that looks like Python but runs on the .NET runtime. It started as a fun side project, but it evolved into something surprisingly powerful — and potentially useful: Key Features: - Python-style syntax with semicolon-based simplicity - Compiles to .NET IL with experimental JIT support - Can run interpreted or compiled - Built-in CLI for managing projects, running, and building - Supports importing NuGet packages and converts them to .ingot modules automatically - MIT licensed and fully open-source You can even do things like: wpp import…
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Just wanted to share with HN a simple/minimal open source Python library that generates SVG files visualizing two dimensional data and distributions, in case others find it useful or interesting. I wrote it as a fun project, mostly because I found that the standard libraries in Python generated unnecessarily large SVG files. One nice property is that I can configure the visuals through CSS, which allows me to support dark/light mode browser settings. The graphs are specified as JSON files (the repository includes a few examples). It supports scatterplots, line plots, histograms,…
- ALA local Python prototyping tool for Jupyter and Streamlit2023 · github.com · ▲65
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…
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