The advent of modern data processing has led to an increasing tendency towards interdisciplinarity, which frequently involves the importation of different technical approaches. Consequently, there is an urgent need for a unified data control system to facilitate the integration of varying libraries. This integration is of profound significance in accelerating prototype verification, optimising algorithm performance and minimising maintenance costs. This paper presents a novel functional programming (FP) paradigm based on the Python architecture and associated suites in programming practice, designed for the integration of pipelines of different data mapping operations. In particular, the solution is intended for the integration of scientific computation flows, which affords a robust yet flexible solution for the aforementioned challenges.

翻译：现代数据处理的发展日益呈现出跨学科趋势，这常常涉及引入不同的技术方法。因此，亟需一种统一的数据控制系统以促进不同库的集成。这种集成对于加速原型验证、优化算法性能以及降低维护成本具有深远意义。本文提出了一种基于 Python 架构及其相关套件的新型函数式编程范式，旨在集成不同数据映射操作的流水线。该方案特别针对科学计算流程的集成设计，为上述挑战提供了一个稳健而灵活的解决方案。