[Python-ideas] Does jargon make learning more difficult?

[Chris Angelico]

On Thu, Aug 23, 2018 at 3:56 AM, Rhodri James <rhodri at kynesim.co.uk> wrote:
> On 22/08/18 14:38, Jonathan Fine wrote:
>>>>> def fn():
>>
>> ...     if None:
>> ...         yield
>> ...
>>>>>
>>>>> list(fn()) # Fails, unless fn is a generator function.
>>
>> []

Actually, it fails unless fn returns some sort of iterable.

>> I think what's happening is this. Even though the None-guarded yield
>> has been optimised away, it leaves a residue. Namely, that there's a
>> yield in the function. Hence fn() is an iterator.
>>
>> Having explained the surprise, here's how it can help you. Suppose you
>> have a long function body, with a single yield at the bottom. If you
>> write like this:
>>
>>      def my_very_long_function_with_one_yield_point(...):
>>          if None: yield # This is a generator function.
>>
>> then the next programmer can know immediately that it's a generator
>> function.
>
>
> Ew.
>
> I'd prefer this way of doing it:
>
>     def my_very_long_function_with_one_yield_point(...):
>         # This is a generator
>

Or you could use a return type annotation.

Why should generator objects be special? A generator function is very
similar to a function that returns a list, except that it can yield
values as it gets them, rather than batching them up to the end. A
generator function is a function which returns an iterable object of
the type "generator". How is it different from a function that returns
an integer? They return different things. How do you show what a
function returns? You annotate it, put it in the docstring, put it in
external docs... It's a function. It does something, it returns
something. That's it.

ChrisA