Python is known to be used by beginners to professional programmers. Python provides functionality to its community of users through PyPI libraries, which allows developers to reuse functionalities to an application. However, it is unknown the extent to which these PyPI libraries require proficient code in their implementation. We conjecture that PyPI contributors may decide to implement more advanced Pythonic code, or stick with more basic Python code. Are complex codes only committed by few contributors, or only to specific files? The new idea in this paper is to confirm who and where complex code is implemented. Hence, we present a visualization to show the relationship between proficient code, contributors, and files. Analyzing four PyPI projects, we are able to explore which files contain more elegant code, and which contributors committed to these files. Our results show that most files contain more basic competency files, and that not every contributor contributes competent code. We show how~our visualization is able to summarize such information, and opens up different possibilities for understanding how to make elegant contributions.
翻译:Python 通过 PyPI 图书馆为用户群提供功能,让开发者可以对应用程序重新使用功能。 然而,尚不清楚这些 PyPI 图书馆在执行过程中需要精密代码的程度。 我们推测Python 用户可能决定执行更先进的 Python 代码, 或用更基本的 Python 代码粘贴。 复杂代码仅由少数贡献者实施, 或只对特定文件实施? 本文的新想法是确认谁和在哪里实施了复杂的代码。 因此, 我们展示了一种视觉化, 以显示熟练代码、 贡献者和文件之间的关系。 分析四个 PyPI 项目, 我们能够探索哪些文件包含更优雅的代码, 以及哪些贡献者致力于这些文档。 我们的结果表明, 大多数文件包含更基本的能力文件, 并不是每个贡献者都贡献了有效的代码。 我们展示了 ~ 我们的视觉化如何能够总结这些信息, 并打开不同的理解如何做出优美贡献的可能性 。