On Thu, Sep 23, 2010 at 12:41 AM, Tristan Zajonc firstname.lastname@example.org wrote:
I'm not an expert on this subject by any stretch, but have been following the discussion with interest.
The basic interface is very simple, consisting of a subscribe method on IObservable and on_next, on_completed, and on_error methods for IObserver. The power comes from the extension methods, similar to itertools, defined in the Observable class (http://bit.ly/acBhbP). These methods provide a huge range of composable functionality.
For instance, using a chaining style, consider a async webclient module that takes a bunch of urls:
The filter is nonblocking and returns another observable. The first() blocks and returns after the first document is received. The do calls a method. Multiple async streams can be composed together in all sorts of ways. For instance,
http = webclient.get(['http://www.cnn.com', 'http://www.nyt.com']) https = webclient.get(['https://www.cnn.com', 'https://www.nyt.com']) http.zip(https).filter(lambda x, y: x.status == 200 and y.status == 200).start(lambda x, y: slow_save(x, y))
This never blocks. It downloads both the https and http versions of web pages, zips them into a new observable, filters sites with both http and https, and then saves asynchronously the remaining sites. I personally find this easy to reason about, and much easier than manually specifying a callback chain. Errors and completed events propagate through these chains intuitively. "Marble diagrams" help with intuition here (http://bit.ly/cl7Oad).
All you need to do is implement the observable interface and you get all the composibility for free. Or you can just use any number of simple methods to convert things to observables (http://bit.ly/7VMnKv), such as observable.start(lambda: print("hi")). Or use decorators. If the observable interface became standard, all future async libraries would be composable, and their would also be a growing collection of observabletools.
As somebody who is new to async programming, I quite quickly grasped this reactive approach even though I was otherwise completely unfamiliar with C#. While it may be due to my lack of experience, I still get confused when thinking about callback chains and error channels. For instance, I have no idea how to zip an async http call and a mongodb call into a simple observable that returns a tuple when both respond and then alerts the user. This would be as simple as
or maybe it's more pythonic to write
obstools.start(obstools.zip(mongodb.get(), webclient.get), flash_completed_message)
although I've never like this inside out style.
But perhaps I missed the point of this thread?
On Wed, Sep 22, 2010 at 6:31 PM, Cameron Simpson email@example.com wrote:
On 20Sep2010 15:41, James Yonan firstname.lastname@example.org wrote: [...] | * Develop a full-featured standard async result type and reactor | model to facilitate interoperability of different async libraries. | This would consist of a standard async result type and an abstract | base class for a reactor model. | | * Let PEP 3148 focus on the problem of thread and process pooling | and leverage on the above async result type. | | The semantics that a general async type should support include: | | 1. Semantics that allow you to define a callback channel for results | and and optionally a separate channel for exceptions as well. | | 2. Semantics that offer the flexibility of working with async | results at the callback level or at the generator level (having a | separate channel for exceptions makes it easy for the generator | decorator implementation (that facilitates "yield | function_returning_async_object()") to dispatch exceptions into the | caller). | | 3. Semantics that can easily be used to pass results and exceptions | back from thread or process pools. [...]
Just to address this particular aspect (return types and notification), I have my own futures-like module, where the equivalent of a Future is called a LateFunction.
There are only 3 basic types of return in my model:
there's a .report() method in the main (Executor equivalent) class that yields LateFunctions as they complete.
A LateFunction has two basic get-the result methods. Having made a LateFunction: LF = Later.defer(func)
You can either go: result = LF() This waits for func's ompletion and returns func's return value. If func raises an exception, this raises that exception.
Or you can go: result, exc_info = LF.wait() which returns: result, None if func completed without exception and None, exc_info if an exception was raised, where exc_info is a 3-tuple as from sys.exc_info().
At any rate, when looking for completion you can either get LateFunctions as they complete via .report(), or function results plain (that may raise exceptions) or function (results xor exceptions).
This makes implementing the separate streams (results vs exceptions) models trivial if it is desired while keeping the LateFunction interface simple (few interface methods).
Yes, I know there's no timeout stuff in there :-(
By God, Mr. Chairman, at this moment I stand astonished at my own moderation! - Baron Robert Clive of Plassey _______________________________________________ Python-ideas mailing list Pythonemail@example.com http://mail.python.org/mailman/listinfo/python-ideas