Complete Airflow-like Task Pipeline Skeleton | Dataford Interview Questions

Given an incomplete object-oriented skeleton that simulates an Airflow-like task pipeline where tasks have dependencies, complete it and add the missing APIs.

Asked in the virtual onsite stage. OOD coding round; the remainder of the prompt is hidden behind the points wall.

Implement Task and Pipeline. A task has a unique name and may depend on other tasks. The pipeline must support adding tasks, adding dependencies, and returning a valid execution order. Return None when a dependency is missing or the graph contains a cycle. When multiple tasks are ready, preserve task insertion order.

I/O Contract

run_pipeline(task_specs) receives a list of dictionaries with name and dependencies fields. It returns a list of task names or None.

Constraints

0 <= task_specs.length <= 1000
Each task name is a non-empty string
Task names are unique
Each dependency name is a string
A task may list a dependency at most once
The required output preserves insertion order among simultaneously ready tasks

Function Signature

def run_pipeline(task_specs):

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