Abstract
Pattern matching allows programs both to extract specific information from complex data types, as well as to branch on the structure of data and thus apply specialized actions to different forms of data. Originally designed for strongly typed functional languages with algebraic data types, pattern matching has since been adapted for object-oriented and even dynamic languages. This paper discusses how pattern matching can be included in the dynamically typed language Python in line with existing features that support extracting values from sequential data structures.
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Kohn, T., Van Rossum, G., Bucher, G. B., Talin, & Levkivskyi, I. (2020). Dynamic pattern matching with Python. In DLS 2020 - Proceedings of the 16th ACM SIGPLAN International Symposium on Dynamic Languages - Co-located with SPLASH 2020 (pp. 85–98). Association for Computing Machinery, Inc. https://doi.org/10.1145/3426422.3426983
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