Lie Ryan wrote:
> On 1/5/2010 1:31 PM, r0g wrote:
>> Michi wrote:
>>> On Jan 4, 1:30 pm, Steven D'Aprano
>>> <ste...@remove.this.cybersource.com.au> wrote:
<snip>
>> A pattern I have used a few times is that of returning an explicit
>> success/failure code alongside whatever the function normally returns.
>> While subsequent programmers might not intuit the need to test for
>> (implicit) "magic" return values they ought to notice if they start
>> getting tuples back where they expected scalars...
>>
>> def foo(x)
>> if x>0:
>> return True, x*x
>> else:
>> return False, "Bad value of x in foo:",str(x)
>>
>> ok, value = foo(-1)
>> if ok:
>> print "foo of x is", value
>> else:
>> print "ERROR:", value
>
> Except that that is a reinvention of try-wheel:
>
True, but there's more than one way to skin a cat! Mine's faster if you
expect a high rate of failures (over 15%).
> def foo(x):
> if x > 0:
> return x*x
> else:
> raise MathError("Bad value of x in foo: %s" % x)
>
> try:
> print foo(-1)
> except MathError, e:
> print "ERROR: System integrity is doubted"
>
> or rather; that is perhaps a good example of when to use 'assert'. If
> the domain of foo() is positive integers, calling -1 on foo is a bug in
> the caller, not foo().
Maybe, although I recently learned on here that one can't rely on assert
statements in production code, their intended use is to aid debugging
and testing really.
Besides, that was just a toy example.
>
> I have been looking at Haskell recently and the way the pure functional
> language handled exceptions and I/O gives me a new distinct "insight"
> that exceptions can be thought of as a special return value that is
> implicitly wrapped and unwrapped up the call stack until it is
> explicitly handled.
Yes there's some very interesting paradigms coming out of functional
programming but, unless you're a maths major, functional languages are a
long way off being productivity tools! Elegant: yes, provable: maybe,
practical for everyday coding: not by a long shot!
Roger.
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