Python Quizzes by Chapter

The quiz page's topic selector narrows the question bank to one chapter. Use it straight after finishing a lesson, while the material is fresh, and again a few days later to check what you've retained:

1. Open the Python quiz.
2. Choose the chapter you just completed, for example "Python Loops".
3. Start with a short quiz; increase the length once you score consistently.

A mixed quiz across all chapters is useful for revision before an exam or interview, but early on it can include specialist topics, such as machine learning or data structures, that you haven't studied yet. Low scores on those tell you nothing about the chapters you have finished. Match the quiz to what you've learned.

Each lesson also ends with its own short quiz and exercises. The chapter quizzes draw on a larger pool, so they show whether understanding holds up across different questions on the same topic.

Two settings change what a quiz measures:

Difficulty: easy questions check definitions and basic syntax; medium questions ask you to predict output or choose between similar options; hard questions involve edge cases and interactions between concepts. "Mixed" draws from all three.

Mode:

Speed can hide whether an answer was reasoned or guessed. In timed mode, note any question you answered on instinct and check its explanation afterwards even if you got it right. A correct guess is still a gap in understanding.

A wrong answer is useful when you identify which rule you got wrong. For each mistake, write one sentence:

• Question: What does range(2, 9, 3) produce?
• My answer: 2, 5, 8, 11
• Correct: 2, 5, 8
• Rule I missed: the stop value is never included, and the sequence stops before reaching it.

Then explain why each wrong option is wrong, not just why the right one is right. This catches partial understanding: if you can't say why "2 3 4 5 6 7 8" is wrong, you may not have understood the step argument.

Avoid remembering answers by their position or wording. Questions and option order vary, and memorised positions don't transfer to real code. If you get a question wrong twice, go back to the lesson section it comes from and work through its examples again.

Turn results into a short plan:

results = {"loops": (9, 10), "dictionaries": (6, 10), "functions": (4, 10)}
for chapter, (right, total) in sorted(results.items(), key=lambda r: r[1][0] / r[1][1]):
    pct = right / total * 100
    action = "re-read lesson and redo examples" if pct < 60 else \
             "practise exercises on weak points" if pct < 80 else "move on; revisit next week"
    print(f"{chapter:<13} {pct:>3.0f}%  {action}")

Address the weakest chapter first, using the lesson's examples and the matching exercises, then apply the concept to a fresh problem of your own, such as a small script using dictionaries in a new context. Retake the chapter quiz a few days later.

One quiz score is only one piece of evidence. A high score on easy multiple-choice questions doesn't mean you can write the code from scratch. Combine quizzes with exercises and small projects to judge whether you're ready to move on.

Task: use the Python quiz for chapter checkpoints and record the rule behind each missed answer.

1. Pick two chapters you've completed. Take a ten-question relaxed quiz on each.
2. For every wrong answer, write the rule you missed in a file, one per line, prefixed with the chapter name.
3. Read your notes back and count misses per chapter:

notes = """loops: range stop is excluded
loops: while needs its condition to change
dictionaries: in checks keys, not values"""

misses = {}
for line in notes.splitlines():
    chapter, rule = line.split(": ", 1)
    misses.setdefault(chapter, []).append(rule)
print({chapter: len(rules) for chapter, rules in misses.items()})   # {'loops': 2, 'dictionaries': 1}

Revise the chapter with most misses, then retake both quizzes in exam mode a few days later. For the worked check, a missed quiz question should guide study by prompting you to review its explanation and apply the concept again.

Start with the Python quiz and the Python exercises. Continue with the beginner projects and the study roadmap.