[Numpy-discussion] numpy error handling

[Tim Hochberg]

Rob Hooft wrote:

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> Travis Oliphant wrote:
> | save = numpy.seterr(dividebyzero='warn')
> |
> | ...
> |
> | numpy.seterr(restore=save)
>
> Most of this discussion is outside of my scope, but I have programmed
> this kind of pattern in a different way before:
>
> ~   save = context.push(something)
> ~   ...
> ~   del save
>
> i.e. the destructor of the saved context object restores the old
> situation. In most cases it will be called by letting "save" go out of
> scope. I know that relying on timely object destruction can be
> troublesome when porting to Jython, but it is very convenient in CPython.
>
> If that goes too far, one could make a separate method on save:
>
> ~    save.pop()
>
> This can do sanity checking too (are we really at the top of the stack?
> Only called once?). The destructor should check whether pop has been 
> called.


Well, the syntax that *I* really want is this:

    class error_mode(object):
        def __init__(self, all=None, overflow=None, underflow=None,
    dividebyzero=None, invalid=None):
             self._args = (overflow, overflow, underflow, dividebyzero,
    invalid)
        def __enter__(self):
             self._save = numpy.seterr(*self._args)
        def __exit__(self):
           numpy.seterr(self._save)

That way, in a few months, I can do this:

    with error_mode(overflow='raise'):
        # do stuff

and it will be almost impossible to mess up. This syntax is lighter and 
cleaner than a stack or relying on garbage collection to free the 
resources. So, for my purposes, the simple syntax Travis proposes is 
perfectly adequate and simpler to implement  and get right than a stack 
based approach. If 'with' wasn't coming down the pipe, I would push for 
a stack, but I like Travis' proposal just fine.

YMMV of course.

-tim