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In 2018, the Economist published an in-depth piece on the programming language Python. “In the past 12 months,” the article said, “Google users in America have searched for Python more often than for Kim Kardashian.” Reality TV stars, be wary.
The high-level language has earned its popularity, too, with legions of users flocking daily to the language for its ease of use due in part to its simple and easy-to-learn syntax. This led researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and elsewhere to make a tool to help run Python code more efficiently and effectively while allowing for customization and adaptation to different needs and contexts. The compiler, which is a software tool that translates source code into machine code that can be executed by a computer’s processor, lets developers create new domain-specific languages (DSLs) within Python — which is typically orders of magnitude slower than languages like C or C++ — while still getting the performance benefits of those other languages.
DSLs are specialized languages tailored to specific tasks that can be much easier to work with than general-purpose programming languages. However, creating a new DSL from scratch can be a bit of a headache.