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.mojaki@gmail.com> wrote:
On Tue, Oct 6, 2020 at 7:21 PM Christopher Barker <pythonchb@gmail.com> wrote:


On Tue, Oct 6, 2020 at 10:14 AM Marco Sulla <Marco.Sulla.Python@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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