Interval Scheduling with DAG Dependencies

Concepts: pyDAGScheduling, pyTopologicalIntervals, pyDualHeap

The meeting rooms problem assumes each task can start at any valid time. Real pipeline scheduling adds dependency constraints: task B cannot start until task A finishes. You now have both interval constraints (task i occupies [start_i, end_i] time slots on a worker) and DAG constraints (topological ordering must be respected). Solving both simultaneously is a staff-level problem. The approach: topological sort first (to establish a valid execution order), then assign time intervals greedily while respecting both the topo order and resource limits. Pipeline Stage Scheduling Two heaps are doing all the work here. The ready heap determines which stage to schedule next (earliest-start-eligible stage from the topo order). The workers heap determines which worker to assign it to (the one that be