DE Applications of Tree Traversal

Concepts: pyFlattenJSON, pyLineageDAG, pyTreeDEApplications

Here is the connection most candidates miss: trees are everywhere in data engineering. JSON documents are trees. XML is a tree. SQL query plans are trees. Data lineage DAGs are trees (well, directed graphs, but traversed the same way). Every time you call json.loads() and navigate nested dicts, you are traversing a tree. The interviewer asking you to flatten a nested JSON is asking you to do a tree traversal. Frame it that way and you instantly sound more senior. Recursive JSON Flattener Flattening a nested JSON document into a flat dict with dot-separated keys is one of the most common DE coding screens. It is a pre-order tree traversal: process the key at the current level, then recurse into child dicts. Dependency Graph Traversal Data pipelines have dependency trees: table B depends on