I have a simple multiprocessing example that I'm trying to create. The ordinary map() function version works, but when changed to Pool.map, I'm getting a strange error:
from multiprocessing import Pool
from functools import partial
x = [1,2,3]
y = 10
f = lambda x,y: x**2+y
# ordinary map works:
map(partial(f,y=y),x)
# [11, 14, 19]
# multiprocessing map does not
p = Pool(4)
p.map(partial(f, y=y), x)
Exception in thread Thread-2:
Traceback (most recent call last):
File "/usr/lib/python2.7/threading.py", line 551, in __bootstrap_inner
self.run()
File "/usr/lib/python2.7/threading.py", line 504, in run
self.__target(*self.__args, **self.__kwargs)
File "/usr/lib/python2.7/multiprocessing/pool.py", line 319, in _handle_tasks
put(task)
PicklingError: Can't pickle <type 'function'>: attribute lookup __builtin__.function failed
Pickling error? What is this exactly?
The arguments to Pool.map
must be picklable. Module-level functions are picklable, but partial(f, y=y)
is not defined at the module-level and so is not pickable.
There is a simple workaround:
def g(x, y=y):
return f(x, y)
p.map(g, x)
Functions made with functools.partial
used to be unpickable.
However, with Python2.7 or better, you can also define g
(at the module level) using functools.partial:
import multiprocessing as mp
import functools
def f(x, y):
return x**2 + y
x = [1,2,3]
y = 10
g = functools.partial(f, y=y)
if __name__ == '__main__':
p = mp.Pool()
print(p.map(g, x))
yields [11, 14, 19]
. But note to get this result f
had to be defined with def
rather than lambda
. I think this is because pickle
relies on "fully qualified" name references to look up function object values.