Making asyncronous call synchronous in Python

Question

What is the best way to make an asynchronous call appear synchronous? Eg, something like this, but how do I coordinate the calling thread and the async reply thread? In java I might use a CountdownLatch() with a timeout, but I can't find a definite solution for Python

def getDataFromAsyncSource():
    asyncService.subscribe(callback=functionToCallbackTo)
    # wait for data
    return dataReturned

def functionToCallbackTo(data):
    dataReturned = data

Answer 1

There is a module you can use

import concurrent.futures

Check this post for sample code and module download link: Concurrent Tasks Execution in Python

You can put executor results in future, then get them, here is the sample code from http://pypi.python.org:

import concurrent.futures
import urllib.request

URLS = ['http://www.foxnews.com/',
    'http://www.cnn.com/',
    'http://europe.wsj.com/',
    'http://www.bbc.co.uk/',
    'http://some-made-up-domain.com/']

def load_url(url, timeout):
    return urllib.request.urlopen(url, timeout=timeout).read()

with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
    future_to_url = dict((executor.submit(load_url, url, 60), url)
                     for url in URLS)

    for future in concurrent.futures.as_completed(future_to_url):
        url = future_to_url[future]
        if future.exception() is not None:
            print('%r generated an exception: %s' % (url,future.exception()))
        else:
            print('%r page is %d bytes' % (url, len(future.result())))

Answer 2

A common solution would be the usage of a synchronized Queue and passing it to the callback function. See http://docs.python.org/library/queue.html.

So for your example this could look like (I'm just guessing the API to pass additional arguments to the callback function):

from Queue import Queue

def async_call():
    q = Queue()
    asyncService.subscribe(callback=callback, args=(q,))
    data = q.get()
    return data

def callback(data, q):
    q.put(data)

This is a solution using the threading module internally so it might not work depending on your async library.