[Python-ideas] Function to return first(or last) true value from list

[אלעזר]

What is the "classic" use case for next() raising StopIteration, to be
silently caught ? We need __next__ to do so in for loops, but when do we
need it in the functional form?

Elazar


2014-02-21 11:25 GMT+02:00 Peter Otten <__peter__ at web.de>:

> Oscar Benjamin wrote:
>
> > On 20 February 2014 22:38, אלעזר <elazarg at gmail.com> wrote:
> >>
> >> 2014-02-21 0:00 GMT+02:00 Steven D'Aprano <steve at pearwood.info>:
> >>>
> >>> On Thu, Feb 20, 2014 at 04:14:17PM +0000, Oscar Benjamin wrote:
> >>> >
> >>> > The thing is just that bare next is not something that's widely
> >>> > recognised as being dangerous. I've seen examples of this kind of bug
> >>> > in samples from many Python aficionados (including at least one from
> >>> > you Terry).
> >>>
> >>> Why is it dangerous, and what kind of bug?
> >>>
> >>> If you're talking about the fact that next(it) can raise StopIteration,
> >>> I think you are exaggerating the danger. Firstly, quite often you don't
> >>> mind if it raises StopIteration, since that's what you would have done
> >>> anyway. Secondly, I don't see why raising StopIteration is so much more
> >>> dangerous than (say) IndexError or KeyError.
> >>>
> >> I had this bug just the other day. I did not plan for the empty case,
> >> since it was obvious that the empty case is a bug, so I relied on the
> >> exception being raised in this case. But I did not get the exception
> >> since it was caught in a completely unrelated for loop. It took me a
> >> while to figure out what's going on, and it would've taken even more for
> >> someone else, not familiar with my assumption or with the whole
> >> StopIteration thing (which I believe is the common case). An IndexError
> >> or a KeyError would have been great in such a case.
> >
> > Exactly. The bug I had manifested in a StopIteration that was raised
> > in a semi-deterministic (dependent on slowly varying data) fashion
> > after ~1 hour of processing. Had it resulted in an IndexError I would
> > have seen a traceback and could have fixed the bug within about 5
> > minutes.
> >
> > But StopIteration doesn't necessarily bubble up in the same way as
> > other exceptions because it can be caught and silently supressed by a
> > for loop (or any consumer of iterators). So instead of a traceback I
> > had truncated output data. It took some time to discover and verify
> > that the output data was truncated. Then it took some time rerunning
> > the script under pdb which was no help since it couldn't latch into
> > the suppressed exception. I assumed that it must be an exception but
> > there were no try/except clauses anywhere in the code. Eventually I
> > found it by peppering the code with:
> >
> > try:
> >     ...
> > except Exception as e:
> >     import pdb; pdb.set_trace()
> >
> > It took most of a day for me to track that down instead of 5 minutes
> > precisely because StopIteration is not like other exceptions.
> > Admittedly I'd spot a similar bug much quicker now simply because I'm
> > aware of the possibility.
> >
> > A simplified version of the bug is shown below:
> >
> > def itermerge(datasources):
> >     for source in datasources:
> >         iterator = iter(source)
> >         first = next(iterator)
> >         for item in iterator:
> >             yield first * item
> >
> > data = [
> >     [1, 1, 2, 3],
> >     [1, 4, 5, 6],
> >     [],  # Who put that there?
> >     [1, 7, 8, 9],
> > ]
> >
> > for item in itermerge(data):
> >     print(item)
> >
> > If you run the above then you get:
> >
> > $ python tmp.py
> > 1
> > 2
> > 3
> > 4
> > 5
> > 6
> >
> > So the data is silently truncated at the empty iterable.
> >
> >> It is *very* similar to the "and or" story.
>
> I think the difference is that once you've learned the lesson you stop
> using
> `and...or` while you change your usage pattern for next() to minimal scopes
>
> def process_source(source):
>     it = iter(source)
>     first = next(it)
>     for item in it:
>         yield first * item
>
> def itermerge(sources):
>     for source in sources:
>         yield from process_source(source)
>
>
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