PyCon 2016
5 HN recommenders · recommended in 8 months, 2016–2023
32:07 · 49K views · Jun 1, 2016
Larry Hastings explains what Python's GIL is, what problems it solves and how it works, and presents his Gilectomy project to remove it, including the performance and C-extension obstacles.
The default reference in Python performance threads for why removing the GIL is hard.
11 comments from Hacker News
I feel like the GIL is, at this point, Python's most infamous attribute. For a long time I thought it was also the biggest flaw with Python...but over time I care less and less about it. I think the first thing to realize is that single-threaded performance is often significantly better with the GIL than without it. I think Larry Hasting's first Gilectomy talk was extremely insightful (about the GIL in general and about performance when removing the GIL): this video I am not sure I would, personally, trade single-threaded performance for enabling multi-threaded applications. I view Python as a high-level rapid prototyping language that is well suited for business logic and glue code. And for that type of workload I would value single-threaded performance over support for multi-threading. Even now, a year later, the Gilectomy project is still slightly off performance-wise (although it looks really really close :) ): [LINK] As noted elsewhere, multi-processing offers adequate parallelization for this type of logic. Also, coroutines and async libraries such as gevent and asyncio offer easily approachable event loops for maximizing single-threaded resource utilization. It's true that multi-processing is not a replacement for multi-threading. There definitely are tasks and workloads where multi-processing and its inherent overhead make it unsuitable as a solution. But for those tasks, I question whether or not Python itself (as an interpreted, dynamically typed language) is suitable.
this video Or search “gilectomy” on LWN. Or check out stackless etc.; it turns out removing the GIL technically is historically one of the easier parts of removing the GIL entirely. It sounds like your main problem is with python’s GC model. Reference counting doesn’t have to be thread-unsafe, but in scripting/interpreted-ish languages that want their threading story to involve seamless (I.e. no special syntax unless you want it, it’s on you not to blow off your foot) sharing of state between threads at will, like Python and Ruby, a GIL or equivalent is the norm. Sometimes it’s not as intrusive as python’s, but it does seem like a necessary (or at least very likely) implementation pattern for languages that want to provide that seamlessness. You can have thread-safe reference counted GC in a traditional scripting language, but that tends to come with a much less automatic threading/concurrency API. Perl 5 is an example of that category, and it is implemented in C.
There's a great talk by David Beazley (I don't remember which one) that he basically explains that removing the GIL isn't difficult at all. After all, it's just one lock. The issue is all the libraries and packages that were built around it. It's now been YEARS of building on top of the GIL. So anyways, PEP 703 is a a nice effort, but I doubt we (everyday mortals) can enjoy it. Meta, and big companies with a specialized team might be able to exploit it by making sure their entire stack is GIL-free. EDIT: My bad, the talk is from Larry Hastings: this video
See Larry Hastings' talk "Removing Python's GIL: The Gilectomy" from PyCon 2016. this video As well as his earlier talk "Python's Infamous GIL". [LINK] The GIL is a simple design that provides serious benefit to Python (end user) developers. There are plenty of options for working around this for parallelism, such as the built-in module multiprocessing.
Larry Hastings - Removing Python's GIL: The Gilectomy - PyCon 2016 this video (I'm pretty sure this is the video I'm thinking of) It's 30m, but worth it if you're interested. Not sure what progress has been made since then.