Hello Terry,
It is not play with words. A tree is a recursive - nested - hierachical data structure with the restriction of no cycles or alternate pathways. Python collections whose members are general objects, including collections, can be nested. The resulting structures *are* tree structures, if not more general directed graphs. They are quite commonly used in Python.
Let's get somethig clear. Tree data structures have an associated logic that justifies their name as a de facto Tree Data Structure. If your low level description was how you described a tree to someone new to the concept, they would be none the wiser about what a Tree represents or what uses they could have for them. This logic is no different from the internal logic that diferentiates a dictionary from a list and helps carry their distinct operations. Despite a dictionary being nothing more than a glorified list.
Just as well, tree data structures only make sense along with their logic. Storage, traversal, insertion, random searches, retrieval, etc, all these algorithms are what in the end define a Tree data structure and what will help categorize it. Python standard library doesn't have any tree data structure implementation. It has lists, dictionaries, and other base structures that in the end will help define storage patterns for tree data structures. And that's it.
A simple binary tree needs to be implemented in Python as a binary tree, if it wants to be recognized as such. All your code examples illustrate exactly that. And if you care about code reuse, you will want to define a number of associated algorithms to take advantage of your storage model and answer your performance or memory requirements. Along with your list pattern for storage, you will probably also want to implement an insertion/search/update/traversal algorithms. That's when you have a tree.
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