The Future of Notebook Programming Is Fluid
The Future of Notebook Programming Is Fluid
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笔记本编程的未来是不稳定的
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Kayur Patel
中科院分区：
文献类型：
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作者：
Mary Beth Kery;Donghao Ren;Kanit Wongsuphasawat;Fred Hohman;Kayur Patel
数据科学笔记本编程社区已经开始出现一种新的小部件，它可以在两种表示之间流畅地切换自己的外观：图形用户界面（GUI）工具和纯文本代码。所有专业水平的数据科学家都经常使用可视化GUI（数据可视化或电子表格）和明文代码（数字，数据操作或机器学习库）。这些作业机具通常是分开的。在这里，我们认为流体GUI/文本编程的独特作用和潜力，以服务于数据工作的做法。我们贡献了一个通用的方法和API强大的流体GUI/文本编码的笔记本电脑，解决关键问题的代码生成和用户交互。最后，我们在两个笔记本工具示例和专业数据科学和机器学习从业者的可用性研究中展示了我们方法的潜力。
A new kind of widget has begun appearing in the data science notebook programming community that can fluidly switch its own appearance between two representations: a graphical user interface (GUI) tool and plain textual code. Data scientists of all expertise levels routinely work in both visual GUIs (data visualizations or spreadsheets) and plaintext code (numerical, data manipulation, or machine learning libraries). These work tools have typically been separate. Here, we argue for the unique role and potential of fluid GUI/text programming to serve data work practices. We contribute a generalized method and API for robust fluid GUI/text coding in notebooks that addresses key questions in code generation and user interactions. Finally, we demonstrate the potential of our method in two notebook tool examples and a usability study with professional data science and machine learning practitioners.