Flatten and unflatten nested Python structures

You are given nested Python data structures used to represent hierarchical data. ## Supported node types - Parent/container nodes can be: - `list` - `tuple` - `dict` - Leaf nodes are **always integers** (`int`). For deterministic behavior, traverse containers in this order: - `list` / `tuple`: left-to-right - `dict`: iterate keys in the dictionary’s iteration order (assume it is deterministic for the input) --- ## Part A — Flatten **Task:** Write a function `flatten(structure) -> list[int]` that extracts all integer leaves in traversal order into a single flat list. **Example** Input: ```python {'a': [1, 2, 3], 'b': {'c': [{'d': 4}], 'e': 5}} ``` Output: ```python [1, 2, 3, 4, 5] ``` --- ## Part B — Unflatten This is the inverse operation. **Inputs:** - `flat_list`: a list of integers (new values) - `template`: a nested structure (same allowed types as above) whose **shape** should be reproduced **Task:** Write a function `unflatten(flat_list, template)` that returns a **new** object with the exact same nested shape and container types as `template`, but with each integer leaf replaced by values from `flat_list` in traversal order. **Assumptions / constraints:** - `flat_list` contains exactly the number of integers required by `template` (or define and implement behavior if it has too few/too many). **Example (conceptual)** Given: - `flat_list = [6, 7, 8, 9, 0]` - `template` is a nested dict/list/tuple structure with 5 integer leaves (e.g., corresponding to leaves at keys/positions `a, b, c, d, e` in traversal order) Output: - a new structure with the same shape as `template`, whose leaf values become `6, 7, 8, 9, 0` in that order.