Carl Banks wrote:
>
> Peter Otten wrote:
>> Carl Banks wrote:
>>
>> > def process_values(lst):
>> > if not lst:
>> > return
>> > do_expensive_initialization_step()
>> > for item in lst:
>> > do_something_with(item)
>> > do_expensive_finalization_step()
>>
>> > What if you called the function like this:
>> >
>> > process_values(x.strip() for x in values_lst)
>> >
>> > Oops, now we've just gone through an expensive initialization and
>> > finalization for nothing (since values_lst was empty). Maybe some
>> > subtle bugs introduced. If we're lucky, the finalization step will
>> > throw an exception.
>>
>> The good news is that the above has a 99 percent chance that it just
>> works with iterators/generators -- even though the writer may not have
>> been aware of them/they didn't exist when the code was written...
>
> There's a litmus test I like to use when justifying something with
> percentages: I imagine that I'm presenting it to my boss, and ask
> myself if I still expect to have a job the next day. :-)
That 99 percent chance is not meant to exempt you from actually verifying
that it works. Docstrings can do wonders here
def process_values(lst):
"Foos all bars in a list"
vs
def process_values(lst):
"Foos all bars in an iterable"
If in doubt, pass a list (-comprehension) as there are other ways of quiet
failure (the function may loop twice over its argument).
> Yes, I agree with you, it most cases I expect merely unnecessary work.
> (Which is not the best news; the best news would be an exception right
> away.) That's why I think this is only a "pretty good" reason to use
> "if len(lst)>0", not a slam dunk.
If process_values() were /aware/ of iterators it would probably be written
def process_values(items):
first_pass = True
for item in items:
if first_pass:
do_expensive_initialization_step()
first_pass = False
do_something_with(item)
if not first_pass:
do_expensive_finalization_step()
or just with an additional
items = list(items)
as its first statement.
Peter
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