第十九条 为了免受正在进行的不法侵害而采取的制止行为，造成损害的，不属于违反治安管理行为，不受处罚；制止行为明显超过必要限度，造成较大损害的，依法给予处罚，但是应当减轻处罚；情节较轻的，不予处罚。
Under load, this creates GC pressure that can devastate throughput. The JavaScript engine spends significant time collecting short-lived objects instead of doing useful work. Latency becomes unpredictable as GC pauses interrupt request handling. I've seen SSR workloads where garbage collection accounts for a substantial portion (up to and beyond 50%) of total CPU time per request. That's time that could be spent actually rendering content.
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However, due to modern LLM postraining paradigms, it’s entirely possible that newer LLMs are specifically RLHF-trained to write better code in Rust despite its relative scarcity. I ran more experiments with Opus 4.5 and using LLMs in Rust on some fun pet projects, and my results were far better than I expected. Here are four such projects:
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