PEPit is a Python package aiming at simplifying the access to worst-case analyses of a large family of first-order optimization methods possibly involving gradient, projection, proximal, or linear optimization oracles, along with their approximate, or Bregman variants. In short, PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods. The key underlying idea is to cast the problem of performing a worst-case analysis, often referred to as a performance estimation problem (PEP), as a semidefinite program (SDP) which can be solved numerically. To do that, the package users are only required to write first-order methods nearly as they would have implemented them. The package then takes care of the SDP modeling parts, and the worst-case analysis is performed numerically via a standard solver.

翻译：PEPit是一个Python软件包，旨在简化对涉及梯度、投影、邻近算子或线性优化预言机（包括其近似变体或Bregman变体）的广泛一阶优化方法进行最坏情况分析的过程。简而言之，PEPit是一个支持一阶优化方法计算机辅助最坏情况分析的软件包。其核心思想是将执行最坏情况分析（通常称为性能估计问题，PEP）的问题转化为可通过数值方法求解的半定规划（SDP）。用户只需按照近乎实际实现的方式编写一阶方法代码，该软件包便会自动处理SDP建模部分，并通过标准求解器进行数值化最坏情况分析。