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A large scale collection of both semantic and natural language resources isessential to leverage active Software Engineering research areas such as codereuse and code comprehensibility. Existing machine learning models ingest datafrom Open Source repositories (like GitHub projects) and forum discussions(like Stackoverflow.com), whereas, in this showcase, we took a step backward toorchestrate a corpus titled PyTorrent that contains 218,814 Python packagelibraries from PyPI and Anaconda environment. This is because earlier studieshave shown that much of the code is redundant and Python packages from theseenvironments are better in quality and are well-documented. PyTorrent enablesusers (such as data scientists, students, etc.) to build off the shelf machinelearning models directly without spending months of effort on largeinfrastructure. The dataset, schema and a pretrained language model isavailable at: https://github.com/fla-sil/PyTorrent

PyTorrent: A Python Library Corpus for Large-scale Language Models