我是一名新手程序员，尝试使用python进行科学编程。我认为这些帖子（如何在IPython.parallel中使用交互式定义的类？和IPython parallel推送自定义对象）触及了类似的问题，但对我没有用处。我想将我的代码作为脚本运行（用于PBS或SGE排队调度器），但我不知道该如何使用dill。
从本质上讲，我试图使用Ipython并行集群来拆分在自定义类方法中定义的计算。
我想将一个集群对象传递到我的自定义类实例中，然后使用集群来拆分对定义为成员的数据片段进行操作的计算。
- 在使用CCD_ 1（CCD_
- 然后，我想运行，
python test_parallel.py - 其中，
test_parallel.py为
class Foo(object):
def __init__(self):
from numpy import arange
self.data = arange(10)*10
def A(self, y):
print "in A:", y
self.data[y]
def parallelA(self, z, cl):
print "in parallelA:", cl[:].map_sync(self.A, z)
def serialA(self, z):
print "in serialA:", map(self.A, z)
if __name__ == "__main__":
from IPython.parallel import Client
f = '/path/to/security/ipcontroller-client.json'
c = Client(f)
asdf = Foo()
asdf.serialA([1, 3, 5]) ## works
asdf.parallelA([1, 3, 5], c) ## doesn't work
输出为
$ ~/Projects/parcellation$ python test_parallel.py
in serialA: in A: 1
in A: 3
in A: 5
[None, None, None]
in parallelA:
Traceback (most recent call last):
File "test_parallel.py", line 24, in <module>
asdf.parallelA([1, 3, 5], c) ## doesn't work
File "test_parallel.py", line 11, in parallelA
print "in parallelA:", cl[:].map_sync(self.A, z)
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/view.py", line 366, in map_sync
return self.map(f,*sequences,**kwargs)
File "<string>", line 2, in map
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/view.py", line 66, in sync_results
ret = f(self, *args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/view.py", line 624, in map
return pf.map(*sequences)
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/remotefunction.py", line 271, in map
ret = self(*sequences)
File "<string>", line 2, in __call__
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/remotefunction.py", line 78, in sync_view_results
return f(self, *args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/remotefunction.py", line 243, in __call__
ar = view.apply(f, *args)
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/view.py", line 233, in apply
return self._really_apply(f, args, kwargs)
File "<string>", line 2, in _really_apply
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/view.py", line 66, in sync_results
ret = f(self, *args, **kwargs)
File "<string>", line 2, in _really_apply
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/view.py", line 51, in save_ids
ret = f(self, *args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/view.py", line 567, in _really_apply
ident=ident)
File "/usr/local/lib/python2.7/dist-packages/IPython/parallel/client/client.py", line 1263, in send_apply_request
item_threshold=self.session.item_threshold,
File "/usr/local/lib/python2.7/dist-packages/IPython/kernel/zmq/serialize.py", line 145, in pack_apply_message
arg_bufs = flatten(serialize_object(arg, buffer_threshold, item_threshold) for arg in args)
File "/usr/local/lib/python2.7/dist-packages/IPython/utils/data.py", line 30, in flatten
return [x for subseq in seq for x in subseq]
File "/usr/local/lib/python2.7/dist-packages/IPython/kernel/zmq/serialize.py", line 145, in <genexpr>
arg_bufs = flatten(serialize_object(arg, buffer_threshold, item_threshold) for arg in args)
File "/usr/local/lib/python2.7/dist-packages/IPython/kernel/zmq/serialize.py", line 89, in serialize_object
buffers.insert(0, pickle.dumps(cobj, PICKLE_PROTOCOL))
cPickle.PicklingError: Can't pickle <type 'instancemethod'>: attribute lookup __builtin__.instancemethod failed
理解为什么这不起作用的任何帮助，以及需要最少代码更改的修复都将非常有用。
谢谢！
我找到了一个解决方案：
class Foo(object):
def __init__(self):
from numpy import arange
self.data = arange(10)*10
@staticmethod
def A(data, y):
print "in A:", y ## doesn't produce an output
return data[y]
def parallelA(self, z, cl):
print "in parallelA:", cl[:].map_sync(self.A, [self.data]*len(z), z)
if __name__ == "__main__":
from IPython.parallel import Client
f = '/path/to/security/ipcontroller-client.json'
c = Client(f)
asdf = Foo()
asdf.parallelA([1, 3, 5], c)
运行上述代码时输出：
$ python test_parallel.py
in parallelA: [10, 30, 50]