Ondřej Vostál - Async Python modules in Rust [PyData Prague 2022-12-13]

Rust Python

Discover how to utilize Rust to improve the performance of Python modules, leveraging async processing and efficient error handling to boost application speed and scalability.

Key takeaways

Python has a performance penalty due to abstraction and exceptions, costing around 5 nanoseconds for basic timings.
Rust is a modern C++ replacement, efficient and fast, potentially even faster than C++.
Async processing in Rust uses the Tokio framework, which is a popular choice for writing async code in Rust.
Rust’s error-handling model is different from Python’s, with functions returning result objects instead of throwing exceptions.
Pyo3 is used to create Python extensions in Rust, which provides macros and other helpful tools.
Python modules can be consumed from Rust using async I/O, allowing for efficient communication between the two languages.
Rust’s move semantics and ownership system are important to consider when working with Python objects.
Jill is a framework that provides a Python-like experience in Rust, allowing for easier implementation of Python-like code in Rust.
Errors in Rust can be handled using the ? operator, which allows a function to return early if an error is encountered.
Rust’s async I/O model is designed to be efficient and scalable, making it suitable for high-performance applications.
Chainkeepers, the company where the speaker works, uses Rust and Python for their blockchain analysis and trading bot development.
The speaker’s company is looking for people to work together and learn more about their projects.

Ondřej Vostál - Async Python modules in Rust [PyData Prague 2022-12-13]

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