Constant-factor differences are frequently ignored when analyzing the complexity of algorithms and implementations, as they appear to be insignificant in practice. In this paper, we demonstrate that this assumption can in fact have far more profound implications on time complexity than is obvious at first glance, and that a poor consideration of trade-offs can result in polynomially slower algorithms whose roots can be deeply and fundamentally ingrained into a programming language itself. While the general observation may not be novel from a theoretical standpoint, it is rarely (if ever) presented in traditional computer science curricula or other settings, and appears to be far from common knowledge in practical software engineering. We thus hope bring awareness to this issue and urge careful consideration of significant trade-offs that can result from trivial decisions made while programming.

中文翻译：

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通货膨胀常数因素以及为什么 Python 比 C++ 快

在分析算法和实现的复杂性时，常数因子差异经常被忽略，因为它们在实践中似乎微不足道。在本文中，我们证明了这一假设实际上对时间复杂度的影响远比乍一看的明显，并且权衡考虑不当可能会导致多项式较慢的算法，其根源可以从根本上根深蒂固变成一种编程语言本身。虽然从理论的角度来看，一般观察可能并不新颖，但它很少（如果有的话）出现在传统的计算机科学课程或其他设置中，并且似乎与实际软件工程中的常识相去甚远。