推荐一篇博客，作者介绍在 DS 项目中写测试。毕竟 ML 的项目测试起来和传统的程序不是太一样，除了最基础的 assert

Data Science Archive

推荐一篇博客，作者介绍在 DS 项目中写测试。毕竟 ML 的项目测试起来和传统的程序不是太一样，除了最基础的 assert, pytest 这些之外对数据的分布和数据一些统计指标也需要做测试。文中提到的几个工具 Hypothesis 和 Pandera 我都是用过的，Pandera 很好用，也可以原生集成给 Pandas/Koalas（Koalas 也是我配合 PySpark 最常用的 DataFrame 工具）。https://www.peterbaumgartner.com/blog/testing-for-data-science/

Peterbaumgartner

Ways I Use Testing as a Data Scientist

In my work, writing tests serves three purposes: making sure things work, documenting my understanding, preventing future errors. When I was starting out with testing, I had a hard time understanding what I should be writing tests for. As a beginner, I just…

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