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…
Xpandas – running Pandas-style computation directly in pure C++ launched on March 2, 2026 with 6 votes, #1,631 of 23,380 launches that month and more than 75% of that year's launches.
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…
Does a similar job
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Sketch – AI code-writing assistant that understands data content2023 · github.com · ▲252Hey HN! I’m excited to share sketch: a tool to help anyone who uses python and pandas quickly iterate and get to answers for their data questions. Sketch installs as a pandas extension that offers utility functions that operate on natural language prompts. Using the `ask` interface you can get answers in natural language. Using the `howto` interface you can get get python and pandas code directly. The primary benefit of this over copilot and chatGPT is that this adds data-content based context so that the generated answers are much more accurate and relevant to the data problem at hand.…
Probly – Spreadsheets, Python, and AI in the browser2025 · github.com · ▲171Probly 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.
I built a tensor library from scratch in C++/CUDA2025 · github.com · ▲119Hi 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…
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Source: Show HN post ↗ · launch text quoted in part
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