You're right, but it's only an issue when the application programmer is using threads. So basically for anyone that is doing CPU intensive work, that can be bro

You're right, but it's only an issue when the application programmer is using threads. So basically for anyone that is doing CPU intensive work, that can be broken up into chunks, and needs to share memory, and doesn't want to take the time to write their own extension to do that part. Practically speaking, I/O is usually the bigger bottleneck. Or you can change your algorithm to not share memory, then use multiprocessing, or a task scheduler like celery to spread it over multiple machines. There are a ton of people who hear about someone running into GIL issues and they think it is affecting them, when they're not doing anything that would be helped by removing it. A JIT compiler on the other hand, would speed up every Python program.