I think you're confusing a number of Python's concepts. The difference between lists and tuples is that lists are mutable (modifyable) and tuples are immutable (never-changing). For example:
>>> myList = [1,2,3]
>>> myList[1] = 3
>>> myTuple = (1,2,3)
>>> myTuple[1] = 3
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: object doesn't support item assignment
That's it. That's the big difference. Use tuples for when things shouldn't change, and lists for when they should. Tuples are thus faster (they don't have to worry about growing, shrinking, etc) while lists are more flexible.
Secondly, a list is NOT implemented as a linked list. A list is a growable array, like an C++'s
std::vector. They're called lists because they are lists of items, in the non-computer-science way. (Not to mention list doesn't imply linked list, it's just more common to see linked list than any other useage of list)
Thirdly, *everything* in Python is stored as a reference (or pointer, if that's the term you prefer). Everything is also an object. Integers and Integers, like tuples, are immutable. The function
id returns "the identity of an object. This is guaranteed to be unique among simultaneously existing objects." It is true that under the normal python interpreter this is a pointer to the object. So each instance of an object would have its own unique id, then why did all of the 7s have the same id? This is because python stores the first 100 integers internally, and anytime they are created it will just reference the existing immortal version. This is one of a few optimizations Python makes that will make the id function return less than helpful results. The other is that most constants (strings or integers) will end up being the same instance (since you can't *ever* change them, they can be shared as much as possible with no harmful side effects)
So to make a long story short, keep lists around when you want to add or remove items, or modify item order. Keep tuples around when they're not going to change (or at least not often).