It is not conceptually irrelevant. With threads, you can create a Python object on one, store it into a global (or some shared state), and use that object from a different thread. You can't do that with subinterpreters tho.
Also, Go doesn't really solve the problem - sure, it has channels, but it still allows for mutable shared state, and unlike Rust, it doesn't make it hard to use.
Associate some shared memory with each subinterpreter (the same array or map)
You could have a rule that the refcount must be 1 when sending an object between subinterpreters.
In other words, you cannot use an object that was .send() to another subinterpreter.
Then you invalidate the reference in that subinterpreter when it calls send to the other subinterpreter which is transferred by assignment.
Can transfer any amount of data with zero copies.
Couldn't you separate the storage of the refcounts from the objects and use a map to get at them?
As for the identities between types being different.
To create an subinterpreter that can marshall between subinterpreters without copying the data structures requires a different data structure that is safe to use from any interpreter. We need to decouple the book keeping data structures from the underlying data.
We can regenerate book keeping data structures during a .send or .receive
Maintaining identity equivalence is an interesting problem. I think it's a more fundamental problem that probably has mathematical solutions.
If we think of objects as being a vector in mathematical space. We have pointers between vectors in this memory space.
For a data structure to be position independent. We need some way of intending references to be global. But we don't want to introduce a layer of indirection on the reference of object relationships. That would be slower. Could use an atomic counter to ensure that identifiers are globally unique.
Don't want to serialize the access to global types.
It sounds to me it is a many-to-many to many-to-many problem. Which even databases don't solve very well.
In other words, the code for a function is hashed and that is its identity that never changes while the program is running.
If we use the same approach with Python, each object could have a hash that corresponds to the code only, instead of the data. This is the objects identity even when added to the book keeping data of another subinterpreter.
This requires decoupling of book keeping information from actual object storage. But replaces pointers with lookups which could be inlined to pointer arithmetic.