CO₂/CH₄ competitive adsorption in MOFs: high-throughput screening and molecular simulation

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When we run timeTravel(checkoutFlow, traceLog), it will actually exercise our checkout workflow, and produce the following output. With that, we’ve successfully executed a production execution trace locally, all without touching any database or external service:

增值税法第三条所称个人,包括个体工商户和自然人。,详情可参考heLLoword翻译官方下载

德黑兰警告华盛顿必须,这一点在im钱包官方下载中也有详细论述

Scan — Discovers all JSONL session files under ~/.claude/projects/ and parses them in parallel using a thread pool. A fast-reject byte check skips progress and history-snapshot lines (~77% of all lines) before touching the JSON parser.,推荐阅读safew官方版本下载获取更多信息

In the months since, I continued my real-life work as a Data Scientist while keeping up-to-date on the latest LLMs popping up on OpenRouter. In August, Google announced the release of their Nano Banana generative image AI with a corresponding API that’s difficult to use, so I open-sourced the gemimg Python package that serves as an API wrapper. It’s not a thrilling project: there’s little room or need for creative implementation and my satisfaction with it was the net present value with what it enabled rather than writing the tool itself. Therefore as an experiment, I plopped the feature-complete code into various up-and-coming LLMs on OpenRouter and prompted the models to identify and fix any issues with the Python code: if it failed, it’s a good test for the current capabilities of LLMs, if it succeeded, then it’s a software quality increase for potential users of the package and I have no moral objection to it. The LLMs actually were helpful: in addition to adding good function docstrings and type hints, it identified more Pythonic implementations of various code blocks.

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