So, Sequence views that do direct addressing with doubly-linked lists?

https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence


https://docs.python.org/3/library/stdtypes.html#dict-views :

> The objects returned by dict.keys(), dict.values() and dict.items() are
view objects. They provide a dynamic view on the dictionary’s entries,
which means that when the dictionary changes, the view reflects these
changes.

You may be looking for (directly-addressable) NumPy arrays?
https://numpy.org/doc/stable/reference/generated/numpy.array.html

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.view.html :

> a.view(ndarray_subclass) or a.view(type=ndarray_subclass) just returns an
instance of ndarray_subclass that looks at the same array (same shape,
dtype, etc.) This does not cause a reinterpretation of the memory.



On Tue, Oct 6, 2020, 1:35 PM Alex Hall <alex.moj...@gmail.com> wrote:

> On Tue, Oct 6, 2020 at 7:21 PM Christopher Barker <python...@gmail.com>
> wrote:
>
>>
>>
>> On Tue, Oct 6, 2020 at 10:14 AM Marco Sulla <marco.sulla.pyt...@gmail.com>
>> wrote:
>>
>>> What I do not understand is why you need to use the iterator instead
>>> of using the iterable itself. This way you can jump to whatever
>>> position without slicing.
>>>
>>
>> if you want the Nth item, that's easy, yes.
>>
>> if you want to iterate through items N to the end, then how do you do
>> that without either iterating through the first N and throwing them away,
>> or making a slice, which copies the rest of the sequence?
>>
>
> ```python
> for i in range(start, stop):
>     x = lst[i]
>     process(x)
> ```
>
> The only problem is that there's slightly more execution in Python-land
> than in C-land, but that only matters if `process(x)` does very little and
> you're really concerned about performance. I can see how the proposal could
> be useful but only in very limited use cases.
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