# mage: Fluid Moves Between Code and Graphical Work in Computational Notebooks

arXiv: https://arxiv.org/abs/2009.10643 · HTML: https://mlsanity.com/paper/2009.10643/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Sep 2020.

## Built on by (most cited first, 13 of 13)

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- [Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Way](https://mlsanity.com/paper/2408.16119/) (2024)
- [Symphony: Composing Interactive Interfaces for Machine Learning](https://mlsanity.com/paper/2202.08946/) (2022)
- [Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels](https://mlsanity.com/paper/2110.12536/) (2021)
- [BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks](https://mlsanity.com/paper/2404.07387/) (2024)
- [StickyLand: Breaking the Linear Presentation of Computational Notebooks](https://mlsanity.com/paper/2202.11086/) (2022)
- [Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference](https://mlsanity.com/paper/2404.03085/) (2024)
- [SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks](https://mlsanity.com/paper/2305.03039/) (2023)
- [MEGAnno: Exploratory Labeling for NLP in Computational Notebooks](https://mlsanity.com/paper/2301.03095/) (2023)
- [Trinary Tools for Continuously Valued Binary Classifiers](https://mlsanity.com/paper/2204.08136/) (2022)
- [Towards Multifaceted Human-Centered AI](https://mlsanity.com/paper/2301.03656/) (2023)

## Abstract (arXiv)

We aim to increase the flexibility at which a data worker can choose the right tool for the job, regardless of whether the tool is a code library or an interactive graphical user interface (GUI). To achieve this flexibility, we extend computational notebooks with a new API mage, which supports tools that can represent themselves as both code and GUI as needed. We discuss the design of mage as well as design opportunities in the space of flexible code/GUI tools for data work. To understand tooling needs, we conduct a study with nine professional practitioners and elicit their feedback on mage and potential areas for flexible code/GUI tooling. We then implement six client tools for mage that illustrate the main themes of our study findings. Finally, we discuss open challenges in providing flexible code/GUI interactions for data workers.
