Curio

• a small and unusual object that is considered interesting or attractive
• A Python library for concurrent I/O and systems programming.

Curio is a library for performing concurrent I/O and common system programming tasks such as launching subprocesses and farming work out to thread and process pools. It uses Python coroutines and the explicit async/await syntax introduced in Python 3.5. Its programming model is based on cooperative multitasking and existing programming abstractions such as threads, sockets, files, subprocesses, locks, and queues. You’ll find it to be small and fast.

Conclusion

The key takeaway from this investigation is that GCs are either optimized for lower latency or higher throughput. They might also perform better or worse at these depending on the heap usage of your program. (Are there a lot of objects? Do they have long or short lifetimes?)

It is important to understand the underlying GC algorithm in order to decide whether it is appropriate for your use-case. It’s also important to test the GC implementation in practice. Your benchmark should exhibit the same heap usage as the program you intend to implement. This will check the effectiveness of the GC implementation in practice. As we saw, the Go implementation is not without faults, but in our case the issues were acceptable. I would love to see the same benchmark in more languages if you would like to contribute :)

Despite some issues, Go’s GC performs well compared to other GCed languages. The Go team have been improving the latency, and continue to do so. We’re happy with Go’s GC, in theory and practice.