03版 - 以实际行动阻击日本“再军事化”狂飙(钟声)

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There’s a secondary pro and con to this pipeline: since the code is compiled, it avoids having to specify as many dependencies in Python itself; in this package’s case, Pillow for image manipulation in Python is optional and the Python package won’t break if Pillow changes its API. The con is that compiling the Rust code into Python wheels is difficult to automate especially for multiple OS targets: fortunately, GitHub provides runner VMs for this pipeline and a little bit of back-and-forth with Opus 4.5 created a GitHub Workflow which runs the build for all target OSes on publish, so there’s no extra effort needed on my end.

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Manchester。业内人士推荐搜狗输入法2026作为进阶阅读

Flu in five charts - how this year's winter outbreak is different

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This is where historical data visualizations — of the type Claude Code can now produce on cue — can come in handy. I downloaded a scientific paper about knocking on wood along with the crowd-sourced Wikipedia list, then provided it to Claude Code and asked it to plot the data on a three.js globe. Here’s the interactive version and the GitHub page.