[Numpy-discussion] Pickling ufuncs?

[Travis Oliphant]

James A. Bednar wrote:

>Hi,
>
>Does anyone know whether it is possible to pickle and unpickle numpy
>ufuncs?
>
Not directly.   Ufuncs are a built-in type and do not have the required 
__reduce__ method needed to be pickleable.   It could be added, but 
hasn't been.

>  I can't find anything about that on scipy.org or the mailing
>list archives.  I have several important pieces of code that accept a
>numpy ufunc as an argument and later apply it to some data, while
>keeping a copy of the ufunc in an attribute.  So far I have been able
>to pickle this code only by doing some very ugly hacks and
>workarounds.
>  
>
Is storing the name considered an ugly hack?

>The ufuncs from Numeric 24 and earlier did not even deepcopy, which
>caused us lots of other problems, but deepcopying them works now in
>numpy 1.0.1. However, they still don't seem to pickle with the regular
>picklers.  Is this deliberately disabled for some reason, or is there
>some workaround?
>  
>
No, nothing has been "disabled."  The feature was never added.

>Here's an example that illustrates the problem:
>
>
>I have a class Test defined in test.py:
>
>class Test(object):
>    def __init__(self,a):
>        self.a = a
>  
>
Why don't you store the name of the ufunc instead:

def __init__(self, a):
      self._a = a.__name__

Then, whenever you are going to use the ufunc you do

import numpy
func = getattr(numpy,self._a)

Then, pickle should work.

Alternatively you can write your own __reduce__ function for the Test 
class.

Direct pickling of ufuncs is not a trivial issue as ufuncs contain 
code-pointers at their core which cannot really be pickled.  It's not a 
simple problem to over-come in general.  We could store the name of the 
ufunc, but for user-defined ufuncs these might come from a different 
package and which package the ufunc lives under is not stored as part of 
the ufunc.

-Travis