Python: (Pathos) Multiprocessing vs. class methods

Question

I am trying to parallelize a code using class methods via multiprocessing. The basic structure is the following:

# from multiprocessing import Pool
from path         


        

Answer 1

In multiprocessing function serialization is needed for interprocess communication. Pickle does a poor job for this purpose, install dill via pip instead. Details (with a nice Star Trek example) can be found here: http://matthewrocklin.com/blog/work/2013/12/05/Parallelism-and-Serialization/

Answer 2

pathos uses dill, and dill serializes classes differently than python's pickle module does. pickle serializes classes by reference. dill (by default) serializes classes directly, and only optionally by reference.

>>> import dill
>>> 
>>> class Foo(object):
...   def __init__(self, x):
...     self.x = x
...   def bar(self, y):
...     return self.x + y * z
...   z = 1
... 
>>> f = Foo(2)
>>> 
>>> dill.dumps(f)  # the dill default, explicitly serialize a class
'\x80\x02cdill.dill\n_create_type\nq\x00(cdill.dill\n_load_type\nq\x01U\x08TypeTypeq\x02\x85q\x03Rq\x04U\x03Fooq\x05h\x01U\nObjectTypeq\x06\x85q\x07Rq\x08\x85q\t}q\n(U\r__slotnames__q\x0b]q\x0cU\n__module__q\rU\x08__main__q\x0eU\x03barq\x0fcdill.dill\n_create_function\nq\x10(cdill.dill\n_unmarshal\nq\x11Uyc\x02\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00C\x00\x00\x00s\x0f\x00\x00\x00|\x00\x00j\x00\x00|\x01\x00t\x01\x00\x14\x17S(\x01\x00\x00\x00N(\x02\x00\x00\x00t\x01\x00\x00\x00xt\x01\x00\x00\x00z(\x02\x00\x00\x00t\x04\x00\x00\x00selft\x01\x00\x00\x00y(\x00\x00\x00\x00(\x00\x00\x00\x00s\x07\x00\x00\x00<stdin>t\x03\x00\x00\x00bar\x04\x00\x00\x00s\x02\x00\x00\x00\x00\x01q\x12\x85q\x13Rq\x14c__builtin__\n__main__\nh\x0fNN}q\x15tq\x16Rq\x17U\x01zq\x18K\x01U\x07__doc__q\x19NU\x08__init__q\x1ah\x10(h\x11Uuc\x02\x00\x00\x00\x02\x00\x00\x00\x02\x00\x00\x00C\x00\x00\x00s\r\x00\x00\x00|\x01\x00|\x00\x00_\x00\x00d\x00\x00S(\x01\x00\x00\x00N(\x01\x00\x00\x00t\x01\x00\x00\x00x(\x02\x00\x00\x00t\x04\x00\x00\x00selfR\x00\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x07\x00\x00\x00<stdin>t\x08\x00\x00\x00__init__\x02\x00\x00\x00s\x02\x00\x00\x00\x00\x01q\x1b\x85q\x1cRq\x1dc__builtin__\n__main__\nh\x1aNN}q\x1etq\x1fRq utq!Rq")\x81q#}q$U\x01xq%K\x02sb.'
>>> dill.dumps(f, byref=True)  # the pickle default, serialize by reference
'\x80\x02c__main__\nFoo\nq\x00)\x81q\x01}q\x02U\x01xq\x03K\x02sb.'

Not serializing by reference is much more flexible. However, in rare circumstances, working with references is better (as it appears to be the case when pickling something built on a SwigPyObject).

I have been meaning (for ~2 years) to expose the byref flag to the dump call inside of pathos, but have not done so yet. It should be a fairly simple edit to do so. I've just added a ticket to do so: https://github.com/uqfoundation/pathos/issues/58. While I'm at it, it should also be easy to open up replacement of the dump and load functions that pathos uses… that way you could use customized serializers (i.e. extend those that dill provides, or use some other serializer).