11.08.18 23:08, Santiago Basulto пише:
Hello folks! I'm using the `concurrent.futures.ProcessPoolExecutor` with
a couple of functions that have been decorated with a class decorator.
Both `concurrent.futures` and `multiprocessing` breaks because "the
object's can't be pickled". There's a really simple fix for this, which
is just, instead of "decorating" the function (with the @), instantiate
the decorator and use it directly.
Example. This is my (very simple, for demonstration purposes) decorator:
class CheckOnlyIntegers:
def __init__(self, fn):
self.fn = fn
def __call__(self, *args):
if not all([type(arg) == int for arg in args]):
raise ValueError("Invalid param is not an integer")
return self.fn(*args)
If I define a simple `add` function and decorate it using the
`CheckOnlyIntegers` decorator:
@CheckOnlyIntegers
def add(x, y):
return x + y
and try using a regular `ProcessPoolExecutor().submit(add, 2, 3)`, it
fails with:
```
Can't pickle <function add at 0x10ace3e18>: it's not the same object as
__main__.add.
```
By default instances of Python classes are pickled by pickling a set of
their attributes. Functions are pickled by name. But since the name of
self.fn corresponds to the decorated function, not the function itself,
it can't be pickled.
You can implement the explicit pickle support for your decorator that
bypass this limitation.
def __reduce__(self):
return self.fn.__qualname__
Now the decorated function will be pickled by name.
It may help to set also self.__module__ = self.fn.__module__ in the
constructor.
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