Abstract
The Python programming language has been picking up traction in Industry for the past few years in virtually all application domains. Python is known for its high calibre and passionate community of developers. Empirical research on Python systems has potential to promote a healthy environment, where claims and beliefs held by the community are supported by data. To facilitate such research, a corpus of 132 open source python projects have been identified, basic information, quality as well as complexity metrics has been collected and organized into CSV files. Collectively, the list consists of 36, 635 python modules, 59, 532 classes, 253, 954 methods and 84, 892 functions. Projects in the selected list span various application domains including Web/APIs, Scientific Computing, Security and more.
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Omari, S., Martinez, G. (2020). Enabling Empirical Research: A Corpus of Large-Scale Python Systems. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Proceedings of the Future Technologies Conference (FTC) 2019. FTC 2019. Advances in Intelligent Systems and Computing, vol 1070. Springer, Cham. https://doi.org/10.1007/978-3-030-32523-7_49
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DOI: https://doi.org/10.1007/978-3-030-32523-7_49
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