Work

Dynamic pattern matching with Python

Year: 2020

Type: conference-paper

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.

Source: Symposium on Dynamic Languages (DLS)

DOI: 10.1145/3426422.3426983

Authors: Tobias Kohn, Guido van Rossum, Gary Brandt Bucher II, Talin, Ivan Levkivskyi

Institutions: University of Cambridge, Python Software Foundation, Dropbox (United States)

Language: English

Topic: Logic, programming, and type systems

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: Engineering and Physical Sciences Research Council

Awards: M3: Managing Many-Cores for the Masses, Automatic Binary Parallelisation, G7278708347