L03 Clocking Model and Multirate Intuition

Metadata

• Lecture ID: L03
• Track: A (Flow Fundamentals)
• Tier: 1
• Duration: 20 minutes
• Prerequisites: L01-L02

Learning Objectives

1. Compare Rate, Trigger, and Hybrid clock semantics.
2. Predict execution timing from clock declarations.
3. Explain why clock choice is independent from flow business logic.

Core Concept

• Mental model: clocks define when a node is eligible to run.
• Key pitfall: using Rate where strict event-driven behavior is required.

Live Demo Mapping

• Primary runnable file: examples/tutorial/a_flow_fundamentals/02_clock_types.py
• Optional extension: examples/tutorial/e_resource_and_sync/03_multirate_robot_system.py

Runnable Commands

Run from repository root:

pixi run python -m examples.tutorial.a_flow_fundamentals.02_clock_types

What To Observe

• Rate(hz=10) prints periodic scheduling intent.
• Trigger('value') prints field-driven semantics.
• Hybrid(hz=5, trigger=['value']) prints combined semantics.

Failure Drill

• Replace a trigger clock with rate clock in an event-driven stage and inspect downstream behavior assumptions.
• Discuss stale or over-sampled data risk.

Exercise

• Required task: set Rate(hz=20) and explain expected impact on producer cadence.
• Stretch task: write one paragraph on when Hybrid is safer than pure Rate.

Evaluation Rubric

• Pass criteria: learner predicts schedule behavior without running code.
• Common failure signature: learner confuses queue adapter behavior with clock policy.

Follow-up

• Next lecture: l04_building_and_validating_ir.md
• Related tutorials: b_ir_and_execution/01_context_graph.py