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Home/ Questions/Q 8138013
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Editorial Team
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Editorial Team
Asked: June 6, 20262026-06-06T11:21:44+00:00 2026-06-06T11:21:44+00:00

I’m trying to use a generator with a Python class that works somewhat similarly

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I’m trying to use a generator with a Python class that works somewhat similarly to a linked list.

Here is a really simple example of what I mean:

class GeneratorTest():
    def __init__(self, list):
        if list:
            self.elem = list[0]
            if list[1:]:
                self.n = GeneratorTest(list[1:])
            else:
                self.n = None

    def __iter__(self):
        return self

    def next(self):
        my_next = self
        while my_next is not None:
            yield my_next
            my_next = my_next.n

Of course this is just an example, but it’s enough to illustrate the point.

Now, I was expecting to be able to invoke something like:

g = GeneratorTest([1,2,3,4,5])
for x in g:
    print x

And have the cycle stop when it reached the last value, but the for loop just continues endlessly.

I’m quite new to generators, so I’m sure it’s a basic premise I’m missing here.

Is the problem related to the fact that I yield the same object that creates the generator?
I’m sure that if I had an object with a list of GeneratorTest objects, I could return each of these objects quite simply, but I feel as there should be a way to make this work without a “wrapper” object.

What am I missing here?

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  1. Editorial Team
    Editorial Team
    2026-06-06T11:21:46+00:00Added an answer on June 6, 2026 at 11:21 am

    The problem is that next (or, in Py3, __next__) shouldn’t be a generator – it should maintain its state externally, and return each value. Yours keeps returning a new generator each time, but since Python doesn’t iterate over that generator, your loop never actually runs.
    This may mean you want __iter__ to return something other than self initially (although whatever it returns is required to have an __iter__ that returns self).

    But the good news is that generators exist precisely to keep track of these rules for you. Move your current next code into __iter__ and everything works – Python does iterate over whatever __iter__ returns (as you would expect).

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