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both of these approaches use NFAs under the hood, which means O(m * n) matching. our approach is fundamentally different: we encode lookaround information directly in the automaton via derivatives, which gives us O(n) matching with a small constant. the trade-off is that we restrict lookarounds to a normalized form (?<=R1)R2(?=R3) where R1/R2/R3 themselves don’t contain lookarounds. the oracle-based approaches support more general nesting, but pay for it in the matching loop. one open question i have is how they handle memory for the oracle table - if you read a gigabyte of text, do you keep a gigabyte-sized table in memory for each lookaround in the pattern?
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随着2025年四季度外卖平台补贴力度收紧，行业逐渐向理性竞争回归，瑞幸也在主动调整策略以缓解盈利压力。事实上，瑞幸早在2024年就开始收紧9.9元低价活动覆盖范围，2025年进一步限制于少量基础款，多数产品回升至10.9-13.9元区间，通过优化定价策略平衡营收增长与盈利水平。这种调整背后，是瑞幸对“规模+盈利”双重目标的追求，也是行业从价格战向价值竞争转型的缩影。
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