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    <p>This is straight from the python documentation: <a href="http://docs.python.org/2/library/multiprocessing.html" rel="nofollow">http://docs.python.org/2/library/multiprocessing.html</a></p> <pre><code>from multiprocessing import Process, Pipe def f(conn): conn.send([42, None, 'hello']) conn.close() if __name__ == '__main__': parent_conn, child_conn = Pipe() p = Process(target=f, args=(child_conn,)) p.start() print parent_conn.recv() # prints "[42, None, 'hello']" p.join() </code></pre> <p>I've had better results using shared state. Especially for simple data like temperature (a number I assume - not a complex custom object or whatever) Here is a wee example (again you will find more in the python docs)</p> <pre><code>#import stuff from multiprocessing import Process, Manager # Create a shared dictionary of paremeters for both processes to use manager = Manager() global_props = manager.dict() # SuperImportant - initialise all parameters first!! global_props.update({'temp': 21.3}) def functionOne(global_props): # Do some stuff read temperature global_props['temp'] = newVal def functionTwo(global_props): temp = global_props['temp'] # Do some stuff with the new value # assign listeners to the two processes, passing in the properties dictionary handlerOne = functionOne # This can also be a class in which case it calls __init__() handlerTwo = functionTwo processOne = Process(target=handlerOne, args=(global_props)) processTwo = Process(target=handlerTwo, args=(global_props)) # Start the processes running... processOne.start() processTwo.start() processOne.join() processTwo.join() </code></pre>
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    1. POMake Python multiprocessing.Pipe between two functions
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    1. USGreenGuerilla
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