invocation_tree: generates a live invocation tree (call tree) of your program, making function calls and returns visible as the code runs. By watching the tree grow and unwind in real time, you get an intuitive feel for recursion’s depth-first execution and can spot where things go wrong. More broadly, it supports a “divide and conquer” way of thinking by showing how a problem splits into subproblems and then combines back into a final result.

memory_graph: is a teaching tool and debugging aid that makes Python’s reference model visible—especially aliasing, mutable data types, and the effects of shallow vs deep copy. It helps learners build the right mental model for Python data by showing how names point to objects and how mutations propagate through shared references. It visualizes the structure of your data so you can more easily understand and debug anything from simple containers to custom data structures. It also visualizes function calls and variable scope via the call stack, letting you inspect the complete program state as execution unfolds.