1. Evaluate Iterator as py_call/2 evaluates its first argument, except the Obj:Attr = Value construct is not accepted.
2. Call __iter__ on the result to get the iterator itself.
3. Get the __next__ function of the iterator.
4. Loop over the return values of the next function. If the Python return value unifies with Value, succeed with a choicepoint. Abort on Python or unification exceptions.
5. Re-satisfaction continues at (4).

The example below uses the built-in iterator range():

?- py_iter(range(1,3), X).
X = 1 ;
X = 2.

Note that the implementation performs a look ahead, i.e., after successful unification it calls‘__next__()` again. On failure the Prolog predicate succeeds deterministically. On success, the next candidate is stored.

Note that a Python generator is a Python _iterator. Therefore, given the Python generator expression below, we can use py_iter(squares(1,5),X) to generate the squares on backtracking.

def squares(start, stop):
     for i in range(start, stop):
         yield i * i

bug

Iterator may not depend on janus.Query()