Exercises#

This page contains three take-home exercises that reinforce the concepts from Lecture 2. Each exercise asks you to write code from scratch based on a specification — no starter code is provided.

All files should be created inside your lecture2/ workspace folder.

Exercise 1 – Operator Expressions

Goal

Demonstrate your understanding of arithmetic, relational, logical, and membership operators by writing a program that computes and reports mission statistics for an autonomous drone.

Specification

Create a file lecture2/mission_stats.py that does the following:

  1. Define the following variables (use the exact names shown):

    • total_distance: 134.7 (km)

    • flight_time: 2.75 (hours)

    • num_waypoints: 8

    • battery_capacity: 5000 (mAh)

    • battery_remaining: 1820 (mAh)

    • approved_altitudes: a list containing 30, 60, 90, and 120

    • requested_altitude: 75

  2. Using only the variables above and Python operators, compute and print each of the following on its own line. Format every floating-point result to two decimal places using an f-string.

    1. Average speed (total_distance / flight_time).

    2. Distance per waypoint segment — there are num_waypoints - 1 segments between waypoints.

    3. The number of complete 30 km legs that fit into total_distance (use floor division).

    4. The leftover distance after those complete legs (use modulus).

    5. Battery percentage remaining (as a float, not an integer).

    6. Whether requested_altitude is in approved_altitudes (print the Boolean directly).

    7. A single Boolean expression that is True when all three of the following conditions hold:

      • Battery percentage is above 25%.

      • Average speed is less than 60 km/h.

      • requested_altitude is not in approved_altitudes.

Expected output (your exact numbers should match):

Average speed:          48.98 km/h
Distance per segment:   19.24 km
Complete 30 km legs:    4
Leftover distance:      14.70 km
Battery remaining:      36.40%
Altitude approved:      False
All conditions met:     True

Deliverables

  • lecture2/mission_stats.py

  • The program must run without errors and produce output that matches the expected values above.

Exercise 2 – String Processing

Goal

Practice string indexing, slicing, methods, and f-string formatting by writing a program that parses and reformats raw sensor log messages.

Specification

Create a file lecture2/log_parser.py that does the following:

  1. Define a variable raw_log with this exact value:

    raw_log = "ts=1706817600;level=WARNING;src=IMU_03;msg=Gyro drift exceeded 0.05 rad/s"

  2. Without hard-coding any index numbers, write code that extracts each field from the raw log. You must use string methods such as .split(), .find(), .index(), or slicing relative to delimiters — not fixed numeric positions. Store the results in four variables:

    • timestamp — the value after ts= (as a string)

    • level — the value after level=

    • source — the value after src=

    • message — the value after msg=

  3. Using the extracted variables, print the following reformatted output. All formatting must be done with f-strings.

    1. A header line: ===== LOG ENTRY =====

    2. The timestamp right-aligned in a 20-character field.

    3. The level converted to lowercase.

    4. The source with the first "_" replaced by " #" (e.g., "IMU_03" becomes "IMU #03").

    5. The message in title case.

    6. The total character count of the original raw_log.

    7. A reversed copy of the level string.

    8. A footer line: = repeated to match the length of the header.

Expected output:

===== LOG ENTRY =====
Timestamp:          1706817600
Level:     warning
Source:    IMU #03
Message:   Gyro Drift Exceeded 0.05 Rad/S
Log length: 76
Reversed level: GNINRAW
=====================

Deliverables

  • lecture2/log_parser.py

  • The program must run without errors and produce output that matches the expected values above.

  • No index numbers may be hard-coded (e.g., raw_log[3:13] is not acceptable).

Exercise 3 – Control Flow

Goal

Write conditional logic from scratch to implement a multi-factor decision system for an autonomous forklift operating in a warehouse.

Specification

Create a file lecture2/forklift_decision.py that does the following:

  1. Define the following variables at the top of your file:

    • payload_kg: 320.0

    • max_capacity_kg: 500.0

    • aisle_width: 2.8 (meters)

    • fork_width: 1.2 (meters)

    • battery_pct: 42.0

    • obstacle_ahead: False

    • operator_override: False

  2. Task A — Load classification: Using if/elif/else, classify the load and print the result:

    • If payload_kg is 0: print "Load status: EMPTY"

    • If payload_kg is up to 50% of max_capacity_kg: print "Load status: LIGHT"

    • If payload_kg is between 50% and 85% (inclusive) of max_capacity_kg: print "Load status: MODERATE"

    • If payload_kg is above 85% but at or below 100% of max_capacity_kg: print "Load status: HEAVY — reduce speed"

    • If payload_kg exceeds max_capacity_kg: print "Load status: OVERLOADED — cannot proceed"

    You must compute the thresholds from the variables (do not hard-code 250, 425, etc.).

  3. Task B — Clearance check: Compute the clearance on each side as (aisle_width - fork_width) / 2. Using a ternary expression, set a variable clearance_ok to True if the per-side clearance is at least 0.5 meters, otherwise False. Print the per-side clearance (two decimal places) and whether it is acceptable.

  4. Task C — Go / No-Go decision: Write a single compound if/elif/else block that prints exactly one of the following outcomes:

    • "DECISION: HALTED — obstacle detected" — if obstacle_ahead is True and operator_override is False.

    • "DECISION: OVERRIDE — proceeding with caution" — if obstacle_ahead is True but operator_override is also True.

    • "DECISION: RETURN TO CHARGE" — if battery_pct is below 20 and there is no obstacle.

    • "DECISION: PROCEED" — if none of the above apply.

  5. Task D — Test your logic: Change the input variables to produce each of the following scenarios and verify your output is correct:

    • An overloaded forklift with an obstacle ahead.

    • An empty forklift with low battery and no obstacle.

    • A heavy forklift with operator override active and tight clearance.

    Add a comment block at the bottom of your file showing the variable values you used for each test and the corresponding output.

Expected output for the default values:

Load status: MODERATE
Per-side clearance: 0.80 m — Acceptable: True
DECISION: PROCEED

Deliverables

  • lecture2/forklift_decision.py

  • The program must run without errors and produce the expected output for the default variable values.

  • The comment block at the bottom must include at least three additional test scenarios with their outputs.

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