Boa Meets Python: A Boa Dataset of Data Science Software in Python Language

The popularity of Python programming language has surged in recent years due to its increasing usage in Data Science. The availability of Python repositories in Github presents an opportunity for mining software repository research, e.g., suggesting the best practices in developing Data Science applications, identifying bug-patterns, recommending code enhancements, etc. To enable this research, we have created a new dataset that includes 1,558 mature Github projects that develop Python software for Data Science tasks. By analyzing the metadata and code, we have included the projects in our dataset which use a diverse set of machine learning libraries and managed by a variety of users and organizations. The dataset is made publicly available through Boa infrastructure both as a collection of raw projects as well as in a processed form that could be used for performing large scale analysis using Boa language. We also present two initial applications to demonstrate the potential of the dataset that could be leveraged by the community.

I. Introduction

Machine learning tools and techniques are becoming prevalent in data-intensive software projects. Among various languages used for Data Science, Python has become one of the most popular languages because of its large collection of libraries to organize and analyze data. Mining such Python projects would be helpful to improve language design, library enhancements, bug detection as well as open new research directions. For example, by analyzing programs from thousands of Data Science projects, we can suggest the best library for performing specific tasks, find recurrent bugs, improve certain APIs, etc.