使用 pool.map(funct, iterable)
时出现此错误:
Am getting this error when using the pool.map(funct, iterable)
:
AttributeError: __exit__
没有解释,只是堆栈跟踪到模块内的 pool.py 文件.
No Explanation, only stack trace to the pool.py file within the module.
这样使用:
with Pool(processes=2) as pool:
pool.map(myFunction, mylist)
pool.map(myfunction2, mylist2)
我怀疑picklability可能存在问题(python需要pickle
,或将列表数据转换为字节流)但我不确定这是真的还是如何调试.
I suspect there could be a problem with the picklability (python needs to pickle
, or transform list data into byte stream) yet I'm not sure if this is true or if it is how to debug.
产生此错误的新代码格式:
new format of code that produces this error :
def governingFunct(list):
#some tasks
def myFunction():
# function contents
with closing(Pool(processes=2)) as pool:
pool.map(myFunction, sublist)
pool.map(myFunction2, sublist2)
产生错误:
PicklingError: Can't pickle <type 'function'>: attribute lookup __builtin__.function failed
在 Python 2.x 和 3.0、3.1 和 3.2 中,multiprocessing.Pool()
对象不是上下文管理器.您不能在 with
语句中使用它们.只有在 Python 3.3 及更高版本中,您才能使用它们.来自 Python 3 multiprocessing.Pool()
文档:
In Python 2.x and 3.0, 3.1 and 3.2, multiprocessing.Pool()
objects are not context managers. You cannot use them in a with
statement. Only in Python 3.3 and up can you use them as such. From the Python 3 multiprocessing.Pool()
documentation:
3.3 版中的新功能:池对象现在支持上下文管理协议 - 请参阅上下文管理器类型.__enter__()
返回池对象,__exit__()
调用 terminate().
New in version 3.3: Pool objects now support the context management protocol – see Context Manager Types.
__enter__()
returns the pool object, and__exit__()
calls terminate().
对于早期的 Python 版本,您可以使用 contextlib.closing()
,但考虑到这将调用 pool.close()
,而不是 pool.terminate()
.在这种情况下手动终止:
For earlier Python versions, you could use contextlib.closing()
, but take into account this'll call pool.close()
, not pool.terminate()
. Terminate manually in that case:
from contextlib import closing
with closing(Pool(processes=2)) as pool:
pool.map(myFunction, mylist)
pool.map(myfunction2, mylist2)
pool.terminate()
或创建自己的 terminating()
上下文管理器:
or create your own terminating()
context manager:
from contextlib import contextmanager
@contextmanager
def terminating(thing):
try:
yield thing
finally:
thing.terminate()
with terminating(Pool(processes=2)) as pool:
pool.map(myFunction, mylist)
pool.map(myfunction2, mylist2)
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