Hi. I hear a confusion that is annoying me a bit in some of the discussions on concurrency, and I thought I'd flush my thoughts here to help me clarify some of that stuff, because some people on the list appear to discuss generators as a concurrency scheme, and as far as I know (and please correct me if I'm wrong) they really are not adressing that at all (full explanation below). Before I go on, I must say that I am not in any way an authority on concurrent programming, I'm just a guy who happens to have done a fair amount of threaded programming, so if any of the smart people on the list notice something completely stupid and off the mark that I might be saying here, please feel free to bang on it with the thousand-pound hammer of your hacker-fu and put me to shame (I love to learn).
As far as I understand, generators are just a convenient way to program apparently "independent" control flows (which are not the same as "concurrent" control flows) in a constrained, structured way, a way that is more powerful than what is allowed by using a stack. By giving up using the stack concept as a fast way to allocate local function variables, it becomes possible to exit and enter chunks of code multiple times, at specific points, within an automatically restored local context (i.e. the local variables, stored on the heap). Generators make it more convenient to do just that: enter and re-enter some code that is expressed as if it would be running in a single execution flow (with explicit points of exit/re-entry, "yields"). The full monty version of that, is what you get when you write assembly code (*memories of adolescent assembly programming on the C=64 abound here now*): you can JMP anywhere anytime, and a chunk of code (a function) can be reentered anywhere anytime as well, maybe even reentered somewhere else than where it left off. The price to pay for this is one of complexity: in assembly you have to manage restoring the local context yourself (i.e in assembly code this just means restoring the values of some registers which are assumed set and used by the code, like the local variables of a function), and there is no clear grouping of the local scope that is saved. Generators give you that for free: they automatically organize all that local context as belonging to the generator object, and it expresses clear points of exit/re-entry with the yield calls. They are really just a fancy goto, with some convenient assumptions about how control should flow. This happens to be good enough for simplifying a whole class of problems and I suppose the Python and Ruby communities are all learning to love them and use them more and more. (I think the more fundamental consequence of generators is to raise questions about the definition of what "a function" is: if I have a single chunk of code in which different parts uses two disjoint sets of variables, and it can be entered via a few entry/exit points, is it really one or two or multiple "functions"? What if different parts share some of the local scope only? Where does the function begin and end? And more importantly, is there a more complex yet stull manageable abstraction that would allow even more flexible control flow than generators allow, straddling the boundaries of what a function is?) You could easily implement something very similar to generators by encapsulating the local scope explicitly in the form of a class, with instance attributes, and having an normal method "step()" that would be careful about saving state in the object's attributes everytime it returns and restoring state from those attributes everytime it gets called. This is what iterators do. Whenever you want to "schedule" your object to be running, you call the step() method. So just in that sense generators really aren't all that exciting or "new". The main problem that generators solve is that they make this save/restore mechanism automatic, thus allowing you to write a single flow of execution as a normal function with explicit exit points (yield). It's much nicer having that in the language than having to write code that can be restored (especially when you have to write a loop with complex conditions/flow which must run and return only one iteration every time they become runnable). Therefore, as far as I understand it, generators themselves DO NOT implement any form of concurrency. I feel that where generators and concurrency come together is often met with confusion in the discussions I see about them, but maybe that's just me. I see two aspects that allow generators to participate in the elaboration of a concurrency scheme: 1. The convenience of expression of a single execution flow (with explicit interruption points) makes it easy to implement pseudo-concurrency IF AND ONLY IF you consider a generator as an independent unit of control flow (i.e. a task). Whether those generators can run asynchronously is yet undefined and depends on who calls them. 2. In a more advanced framework/language, perhaps some generators could be considered to always be possible to run asynchronously, ruled by a system of true concurrency with some kind of scheduling algorithm that oversees that process. Whether this has been implemented by many is still a mystery to me, but I can see how a low-level library that provides asynchronously running execution vehicles for each CPU could be used to manage and run a pool of shared generator objects in a way that is better (for a specific application) than the relatively uninformed scheduling provided by the threads abstraction (more at the end). Pseudo or cooperative concurrency is not the same as true asynchronous concurrency. You can ONLY avoid having to deal with issues of mutual exclusion if you DO NOT have true asynchronous concurrency (i.e. two real CPUs running at the same time)--unless you have some special scheduling system that implements very specific assumptions about data access vs the code that it schedules, in which case that scheduling algorithm itself will have to deal with potential mutual exclusion problems: YOU DON'T GET OUT OF IT, if you have two real, concurrent processing units making calculations, you have to deal with the way that they might access some same piece of data at the same time. I suppose that the essence of what I want to say with this diatribe is that everyone who talks about generators as a way to avoid the hard problems of concurrent programming should really explicitly frame the discussion in the context of a single process cooperative scheme that runs on a single processor (at any one time). It does not hold outside of that context, outside of that context you HAVE to deal with mutex issues, and that's always where it gets messy (even with generators). Now, IMO where it gets interesting is when you consider that what you're doing when you are executing multiple asynchronous control flows with explicit code in your process, is that you're essentially bringing "up" the scheduler from the kernel layer into your own code. This is very cool. This may allow you specialize that scheduler with assumptions which may ultimately simplify the implementation of your independent control flows. For example, if you have two sets of generators that access disjoint sets of data, and two processing units, your scheduler could make sure that no two generators from the same set get scheduled at the same time. If you do that then you might not have to lock access to your data structures at all. You can imagine more complex variants on this theme. One of the problems that you have with using generators like this, is that automatic "yield" on resource access does not occur automatically, like it does in threading. With threads, the kernel is invoked when access to a low-level resource is requested, and may decide to put your process in the wait queue when it judges necessary. I don't know how you would do that with generators. To implement that explicitly, you would need an asynchronous version of all the functions that may block on resources (e.g. file open, socket write, etc.), in order to be able to insert a yield statement at that point, after the async call, and there should be a way for the scheduler to check if the resource is "ready" to be able to put your generator back in the runnable queue. (A question comes to mind here: Twisted must be doing something like this with their "deferred objects", no? I figure they would need to do something like this too. I will have to check.) Any comment welcome. cheers, _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
