trio
Trio – a friendly Python library for async concurrency and I/O
Trio is a Python library for running multiple tasks at once, like fetching many web pages simultaneously, using a simpler and safer approach to async programming than Python's built-in asyncio.
Trio is a Python library for writing programs that handle multiple tasks at the same time, specifically when those tasks involve waiting for things like network responses, file reads, or other input and output operations. Python has a built-in system for this kind of programming called asyncio, but Trio is a separate, independent alternative that was designed with a different philosophy: make it as simple and hard to misuse as possible.
The core idea behind Trio is something called structured concurrency. In most async systems, you can start tasks running in the background and they can outlive the code that created them, which makes it difficult to reason about when things finish or what happens if something goes wrong. Trio enforces a rule that tasks must finish before the code that launched them exits. This constraint, similar to how a normal function call works, makes programs much easier to follow and debug. The README links to a longer article explaining the reasoning if you want the deeper background.
In practical terms, Trio is useful for writing web scrapers that fetch many pages at once, servers that handle many simultaneous connections, or any program that would otherwise spend most of its time waiting. It supports working with sockets, subprocesses, and similar low-level operations. The library runs on Python 3.10 and newer on Linux, macOS, Windows, and FreeBSD.
Trio is described as mature and production-ready. Breaking changes are rare, and the existing features are fully documented. Installation is straightforward because all dependencies are written in pure Python except for one Windows-specific component that comes as a pre-built package, meaning you do not need a C compiler.
The project is open source under your choice of MIT or Apache 2 licenses. A beginner-friendly tutorial is available in the documentation for people with no prior experience writing async Python code.
Where it fits
- Build a web scraper that fetches dozens of pages simultaneously without waiting for each one to finish before starting the next.
- Write a TCP server that handles many simultaneous client connections without spawning a thread per connection.
- Replace asyncio in an existing Python project to get cleaner task lifecycle management and easier error propagation.