Libraries Run Rust Inside Python (With PyO3)
This article explains how to integrate Rust code into Python applications using the PyO3 toolchain and Maturin. It demonstrates how to build high-performance extensions, such as a JSON parser, to improve execution speed.
Why it matters
Bridging Rust and Python allows developers to combine Python's ease of use with Rust's memory safety and performance, a critical trend in modern software engineering.
Every time you validate data with Pydantic v2, the data-validation library most Python apps reach for, a Rust extension does the work. Its core, pydantic-core, is built with PyO3, the same toolchain we'll use here.
This post builds that same kind of bridge, small enough to read in one sitting: a JSON parser written in Rust, exposed to Python, so you can import it like any other package. The last step, turning the Rust result into Python objects, is the one to understand before you port anything: for a parser like this, it can cost more than the parsing itself.
Getting Rust code into Python takes four steps:
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