Data Analytics with Blockly and Unix Tools

Presenter: Pantelis Kakavas and Vagelis Tsipis
Date: 29 April 2024

Abstract

We introduce a new approach to integrating Unix command-line tools with visual programming, aiming to enhance accessibility and usability in data processing pipelines. Leveraging Blockly, a visual programming language, Unix commands are represented as graphical blocks, removing the need for advanced programming skills and making them more accessible to a broader audience. The creation of a visual programming environment enables users to construct data processing pipelines through drag-and-drop actions, facilitated by JSON definition files that create Unix command line tool abstractions linking visual blocks to Unix commands. The design is user friendly and deepens users' comprehension of Unix commands, improving accessibility for difficult data manipulation tasks. The project highlights the importance of visual programming in bridging the gap between complex command-line operations and user-friendly interfaces, thereby expanding the toolkit available for data scientists and researchers of various fields, while also offering new opportunities for interactive educational tools in command-line interface learning.