I am much impressed by Python’s expressiveness, ease of programming and development speed. However, as a dynamically typed language pure Python suffers from poor performance, which heavily impacts the numerical algorithms. Therefore, many of the computational tasks are often dispatched to binary Python extensions implemented in C, C++ or other languages. Indeed, the ease of interfacing with external languages is another of Python’s super powers, which also led to its reputation as the glue language 1.
Recently, I have been experimenting with developing Python extensions in Rust, using the amazing pyo32 library (“crate” in Rust world). Although the learning curve is steep at times (hello borrow checker and lifetime annotations), the official Rust book3 does great job in explaining complex topics.
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