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Revision 1873

Added by Aaron Marcuse-Kubitza over 12 years ago

parallel.py: MultiProducerPool.apply_async(): Prepickle all function args. Try pickling the args before the queue pickles them, to get better debugging output.

View differences:

parallel.py
1 1 
# Parallel processing
2 2 

  		




  
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import cPickle


  		




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import Queue


  		




  
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import types


  		




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import warnings


  		




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import exc


  		




  
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from Runnable import Runnable


  		




  
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def try_pickle(value):


  		




  
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    try: cPickle.dumps(value)


  		




  
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    except Exception, e:


  		




  
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        exc.add_msg(e, 'Tried to pickle: '+repr(value))


  		




  
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        raise


  		




  
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def prepickle(value):


  		




  
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    if isinstance(value, types.FunctionType): return Runnable(value)


  		




  
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    elif isinstance(value, MultiProducerPool): return None


  		




  
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    elif isinstance(value, list): return map(prepickle, list_)


  		




  
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    elif isinstance(value, dict):


  		




  
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        return dict(((k, prepickle(v)) for k, v in value.iteritems()))


  		




  
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    else: return value


  		




  
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class SyncPool:


  		




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    '''A dummy synchronous Pool to use if multiprocessing is not available'''


  		




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    def __init__(self, processes=None): pass


  		




  ......




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class MultiProducerPool:


  		




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    '''A multi-producer pool. You must call pool.main_loop() in the thread that


  		




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    created this to process new tasks.'''


  		




  
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    def __init__(self, processes=None):


  		




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        '''


  		




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        @param processes If 0, uses SyncPool


  		




  ......




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    def main_loop(self):


  		




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        '''@param pool Must be a pool returned by mk_pool()'''


  		




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        try:


  		




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            # block=False raises Empty immediately if the queue is empty,


  		




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            # which indicates that the program is done


  		




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            while True: self.queue.get(block=False)() # each elem is a function


  		




  
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            while True:


  		




  
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                # block=False raises Empty immediately if the queue is empty,


  		




  
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                # which indicates that the program is done


  		




  
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                call = self.queue.get(block=False)


  		




  
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                self.pool.apply_async(call.func, call.args, call.kw_args,


  		




  
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                    call.callback)


  		




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        except Queue.Empty: pass


  		




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    class Result:


  		




  ......




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        def successful(): raise NotImplementedError()


  		




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    def apply_async(self, *args, **kw_args):


  		




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        def call(): self.pool.apply_async(*args, **kw_args)


  		




  
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    def apply_async(self, func, args=None, kw_args=None, callback=None):


  		




  
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        if args == None: args = ()


  		




  
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        if kw_args == None: kw_args = {}


  		




  
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        call = Runnable(func, *prepickle(args), **prepickle(kw_args))


  		




  
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        call.callback = callback # store this inside the Runnable


  		




  
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        # Try pickling the args. If it fails, we'll get a full traceback here,


  		




  
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        # which is not provided with pickling errors in multiprocessing's Pool.


  		




  
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        try_pickle(call)


  		




  
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        self.queue.put_nowait(call)


  		




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        return self.Result()


  		












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