Fly with Python is a four-unit digital textbook that teaches Python programming through autonomous drone flight. Students write their first lines of code in CodeSpace, Firia's browser-based Python IDE, then progress to programming the CodeAIR drone's flight, sensors, and onboard logic.

Each unit breaks down into short, guided missions. Every mission ships with a complete teaching package: learning targets, classroom-ready lesson plans, key concepts, vocabulary, success criteria, assessment opportunities, and standards alignment. Pacing is yours: teach the missions in sequence over a semester, or pull them individually to fit a CS, robotics, or cross-curricular elective.

This unit introduces students to CodeSpace, Firia's Python IDE, and the CodeAIR drone. Across three guided missions plus a remix project and unit assessment, students get oriented to the IDE, meet the drone hardware, and write their first programs to control the drone, all without taking flight.

• ▸ Mission 1: Welcome to CodeSpace: An introduction to the CodeSpace Development Environment.
• ▸ Mission 2: Introducing CodeAIR: This mission introduces the CodeAIR drone.
• ▸ Mission 3: Pre-Flight Check: This mission allows students to program the drone without taking flight.
• ▸ Unit 1 Remix & Assessment: Students apply skills from Missions 1-3 in an original CodeAIR remix project, and demonstrate mastery through the Unit 1 Assessment (review questions and rubrics).

This unit prepares students to take CodeAIR airborne, safely. Students build a safety interlock with branching if statements, debounce button presses, wrap reusable behavior into functions, and explore the quadcopter power system. Later missions extend into flight maneuvers and autonomous operation.

• ▸ Mission 4: Flight Safety: Students program a set of safety procedures using buttons, branching, debouncing, and a user-defined function to arm the drone.
• ▸ Mission 5: Hovering Flight: Students program CodeAIR to avoid walls and seek an exit using sensors, custom modules, the MotionCommander interface, and variables.
• ▸ Mission 6: Navigate: Students program CodeAIR to fly autonomously using sensor data, exploring the flow sensor for x/y position tracking, battery checks, binary LED patterns, exception handling with try blocks, and a selectable-operations user interface.
• ▸ Unit 2 Remix & Assessment: Students apply skills from Missions 4-6 in an original CodeAIR remix project, and demonstrate mastery through the Unit 2 Assessment (review questions and rubrics).

This unit moves students into autonomous flight. Across four guided missions plus a remix project and unit assessment, students master the StateMachine task scheduler, formal state handlers, the flight data recorder, and sensor-driven event injection. They put it all together by programming CodeAIR to chart its own gyroscope data and run an autonomous survey of an object.

• ▸ Mission 7: Multitasking: Students program a drone to perform multiple tasks at the same time without blocking program execution, using the StateMachine task scheduler to run non-blocking code for sounds, lights, and sensors.
• ▸ Mission 8: Drone Director: Students combine the task scheduler with formal state handlers to fly precision flight profiles, using the flight data recorder, non-blocking flight commands, and event injection to direct CodeAIR like a film director directs a scene.
• ▸ Mission 9: Attitude Control: Students explore CodeAIR's gyroscope to build a feedback system, charting roll rate live, redirecting chart data to the flight recorder, and using LEDs and motors to give the drone visual and haptic responses to tilt.
• ▸ Mission 10: Survey: Students program an autonomous survey, flying CodeAIR around a box to detect corners, measure each side using state estimators and the Pythagorean Theorem, and capture the dimensions in a Python list.
• ▸ Unit 3 Remix & Assessment: Students apply skills from Missions 7-10 in an original CodeAIR remix project, and demonstrate mastery through the Unit 3 Assessment (review questions and rubrics).

This unit brings artificial intelligence to the drone. Across five guided missions plus a remix project and unit assessment, students master the onboard camera, teach CodeAIR machine vision - first following a line by its brightness, then locking onto a target by color - and finally hand the seeing over to a trained neural network. They finish by building a custom ground control station on a CodeX with live telemetry, infrared pairing, and radio communication.

• ▸ Mission 11: Reconnaissance: Students master CodeAIR's onboard camera to gather aerial visual intel, and learn planned navigation - flying precise, repeatable routes with waypoints.
• ▸ Mission 12: Line Patrol: Students turn raw camera pixels into machine vision, teaching CodeAIR to see a dark line by its brightness and follow it autonomously - no waypoints required - using grayscale conversion, thresholding, and proportional steering.
• ▸ Mission 13: Target Lock: Students move from brightness to color, using HSV color detection and bounding boxes to search for a colored target, judge its size and position, center on it with proportional control, and land right on top.
• ▸ Mission 14: Search Party: Students hand the seeing over to machine learning - loading a trained neural network and flying on its predictions to search for the Cody mascot, photograph it, and land on the helipad.
• ▸ Mission 15: Telemetry: Students build a custom flight controller on a CodeX from scratch in Python - a heads-up display with live telemetry gauges, infrared pairing, and a JSON radio communication layer - turning the CodeX into a ground control station.
• ▸ Unit 4 Remix & Assessment: Students apply skills from Missions 11-15 in an original CodeAIR remix project, and demonstrate mastery through the Unit 4 Assessment (review questions and rubrics).