Python的语法设计如同一份清晰的“待办事项清单”，这本身就是一种极佳的思维减负。你将复杂问题拆解成“先做什么、再判断什么、最后输出什么”的清晰步骤，这个过程本身就将模糊的焦虑转化为具体的路径。当你用代码描述清楚这个过程后，这个“思维模型”就得以固化，从此无需再为同类问题消耗任何决策精力。这好比为你常用的大脑路径修建了一条自动化高速公路。

北航、人大和九坤投资共同撰写的论文 《Scaling Laws for Code: Every Programming Language Matters》 整理而成。 在代码大模型（Code LLMs）的预训练中，行业内长期存在一种惯性思维，即把所有编程语言的代码都视为同质化的文本数据，主要关注数据总量的堆叠。然而，现代软件开发本质上是多语言混合的，不同语言的语法特性、语料规模和应用场景差异巨大。

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