Python multiprocess pool模块报错pickling error问题解决方法分析
本文实例讲述了Python multiprocess pool模块报错pickling error问题解决方法。分享给大家供大家参考,具体如下:
问题
之前在调用class内的函数用multiprocessing模块的pool函数进行多线程处理的时候报了以下下错误信息:
PicklingError: Can't pickle <type 'function'>: attribute lookup __builtin__.function failed
查了下官方文档发现python默认只能pickle以下的类型:
- None, True, and False
- integers, floating point numbers, complex numbers
- strings, bytes, bytearrays
- tuples, lists, sets, and dictionaries containing only picklable objects
- functions defined at the top level of a module (using def, not lambda)
- built-in functions defined at the top level of a module
- classes that are defined at the top level of a module
- instances of such classes whose dict or the result of calling getstate() is picklable (see section -
- Pickling Class Instances for details).
函数只能pickle在顶层定义的函数,很明显的class内的函数无法被pickle因此会报错。
import multiprocessing def work(): # top-level 函数 print "work!" class Foo(): def work(self): # 非top-level函数 print "work" pool1 = multiprocessing.Pool(processes=4) foo = Foo() pool1.apply_async(foo.work) pool1.close() pool1.join() # 此时报错 pool2 = multiprocessing.Pool(processes=4) pool2.apply_async(work) pool2.close() pool2.join() # 此时工作正常
解决方案
调用pathos包下的multiprocessing模块代替原生的multiprocessing。pathos中multiprocessing是用dill包改写过的,dill包可以将几乎所有python的类型都serialize,因此都可以被pickle。或者也可以自己用dill写一个(有点重复造轮子之嫌啊)
参考
1. https://stackoverflow.com/questions/8804830/python-multiprocessing-picklingerror-cant-pickle-type-function
2. https://docs.python.org/3/library/pickle.html
3. https://github.com/uqfoundation/pathos
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