Hi, The documentation for the Multiprocessing.Array says:
multiprocessing.Array(typecode_or_type, size_or_initializer, *, lock=True)¶ ... If lock is False then access to the returned object will not be automatically protected by a lock, so it will not necessarily be “process-safe”. ... However: In [48]: mp.Array('i',1,lock=False) --------------------------------------------------------------------------- AssertionError Traceback (most recent call last) /Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/ multiprocessing/__init__.pyc in Array(typecode_or_type, size_or_initializer, **kwds) 252 ''' 253 from multiprocessing.sharedctypes import Array --> 254 return Array(typecode_or_type, size_or_initializer, **kwds) 255 256 # /Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/ multiprocessing/sharedctypes.pyc in Array(typecode_or_type, size_or_initializer, **kwds) 85 if lock is None: 86 lock = RLock() ---> 87 assert hasattr(lock, 'acquire') 88 return synchronized(obj, lock) 89 AssertionError: ------- I.e. it looks like lock=false is not actually supported. Or am I reading this wrong? If not, I can submit a bug report. I am trying to create a shared, read-only numpy.ndarray between several processes. After some googling the basic idea is: sarr = mp.Array('i',1000) ndarr = scipy.frombuffer(sarr._obj,dtype='int32') Since it will be read only (after being filled once in a single process) I don't think I need any locking mechanism. However is this really true given garbage collection, reference counts and other implicit things going on? Or is there a recommended better way to do this? Thanks -- http://mail.python.org/mailman/listinfo/python-list