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}Decomposition and Testing
functions
beginner
Break problems into functions and protect behavior with focused tests.
Questions
- What problem does Decomposition and Testing help us solve in a small Python program?
- What should we predict before running the example?
- What value, output, or error should we inspect after changing one line?
Objectives
- Run a complete example for decomposition and testing in Colab.
- Explain the example line by line using plain language.
- Change one part of the code and predict the result before running it.
- Recognize one common mistake and use the error message as evidence.
Hands-on episode: Decomposition and Testing
Decomposition means breaking a problem into focused functions. Testing means writing small checks that prove each function behaves as expected for important examples.
We will learn this by running code, not by memorizing a definition first. Open the Colab notebook from the button above, find this section, and run each cell in order. Keep a small note beside the notebook with three columns: prediction, actual result, and what changed.
Example 1.1
Compare the function body with the assertion and read the assertion as a sentence.
Run the cell once without editing it. If the result is different from your prediction, leave the prediction visible and write one sentence about the difference. That sentence is more useful than a perfect first guess.
Explain Example 1.1
- The function has one job: combine prices into a subtotal.
- The loop accumulates one price at a time, which makes the changing value easy to trace.
- The assertion says, ‘for this example input, the expected result is 10.’
- If the function changes later and breaks this promise, the assertion will fail loudly.
Now explain the example out loud or in a Markdown cell. Use short sentences: “this line creates…”, “this name stores…”, “this output appears because…”. If you cannot explain a line yet, run only the lines above it and inspect the values that exist at that moment.
Challenge 1.1
NoteChallenge
Add assert subtotal([]) == 0. This checks an edge case: no prices. A good test suite includes ordinary examples and boundary examples.
Show a safe way to approach the challenge
- Copy Example 1.1 into a new Colab cell.
- Change exactly one value, name, condition, or line.
- Write the expected output before running the cell.
- Run the cell and compare the actual result with your prediction.
- If the result surprises you, undo the change and try a smaller one.
Suggested first move: Add assert subtotal([]) == 0.
Debugging checkpoint 1.1
WarningDebugging checkpoint
Do not split code into tiny functions just to have many functions. Split when a step has a clear name, a clear input, and a clear result. If a test is hard to write, the function may be doing too many jobs.
Do not debug by rewriting the whole example. Read the error type or surprising output, inspect the closest value with print(...) or type(...), then change one thing. This is the same routine you will use in larger projects.
Apply it
Take a receipt calculator and split it into subtotal, tax_amount, and grand_total. Write one assertion for each function before combining them.
Finish by adding a Markdown cell that answers: What did this example teach me that I can reuse in a project?
Key points
- Learn the concept by running a complete, small example first.
- Predict before execution so your thinking becomes visible.
- Change one thing at a time so cause and effect stay clear.
- Treat errors as clues about the exact line or value Python could not handle.
Why this matters
Break problems into functions and protect behavior with focused tests.
This lesson combines related subtopics that belong together in one learning conversation. You will still pause for a quiz after each section, but you do not need to jump between separate pages while building one clear explanation.
NoteGuiding questions
By the end of this lesson, you should be able to answer:
- How do the sections in Decomposition and Testing fit together?
- Which small example demonstrates each section?
- Which debugging clue should I check first for each section?
NoteLearning objectives
You will practice how to:
- explain the shared concept for this lesson;
- use each section as one step in a larger workflow;
- complete 2 short section quizzes before moving on;
- connect examples, mistakes, and debugging routines.
Lesson map
- 1. Decomposition — Break a larger problem into smaller named functions.
- 2. Testing Functions — Check function behavior with examples and assertions.
1. Decomposition
Break a larger problem into smaller named functions.
TipAnalogy
Decomposition is like planning a trip: choose destination, book travel, pack, and check in instead of saying only travel.
What this means
Decomposition reduces complexity by solving one small responsibility at a time.
Example 1
Predict what will happen before you run the code.
Step-by-step explanation
def add_tax(price):— pause here and say what this line reads, creates, changes, or displays.return price * 1.08— pause here and say what this line reads, creates, changes, or displays.def format_price(price):— pause here and say what this line reads, creates, changes, or displays.return f"${price:.2f}"— pause here and say what this line reads, creates, changes, or displays.print(format_price(add_tax(10)))— pause here and say what this line reads, creates, changes, or displays.
After running the example, compare the actual output with your prediction. If they differ, do not erase your prediction. The difference is the part that can teach you the most.
Challenge
NotePractice
Change one input value, predict the new output, run the code, and explain the difference in one sentence.
Show one possible solution path
- Copy Example 1 into Colab, Jupyter, or a
.pyfile. - Mark the line you plan to change.
- Write a one-sentence prediction.
- Run the changed code.
- If the result surprises you, restore the original and change a smaller part.
The goal is not to find the only correct answer. The goal is to create a small experiment where you can explain cause and effect.
Common mistakes
WarningCommon mistake
A function that does too many unrelated jobs is hard to test. Split by responsibility.
When you get stuck, use this debugging routine:
- Read the last line of the error message or inspect the unexpected output.
- Find the smallest line of code that could be responsible.
- Print or inspect the value and type at that point.
- Change one thing.
- Run again and record what changed.
Check your understanding
This quiz checks the ideas in this section before you move on.
2. Testing Functions
Check function behavior with examples and assertions.
TipAnalogy
A test is like a measuring cup: it tells you whether the recipe produced the amount you expected.
What this means
A test is executable evidence that a function behaves as expected for a chosen case.
Example 2
Predict what will happen before you run the code.
Step-by-step explanation
def add(a, b):— pause here and say what this line reads, creates, changes, or displays.return a + b— pause here and say what this line reads, creates, changes, or displays.assert add(2, 3) == 5— pause here and say what this line reads, creates, changes, or displays.assert add(-1, 1) == 0— pause here and say what this line reads, creates, changes, or displays.
After running the example, compare the actual output with your prediction. If they differ, do not erase your prediction. The difference is the part that can teach you the most.
Challenge
NotePractice
Change one input value, predict the new output, run the code, and explain the difference in one sentence.
Show one possible solution path
- Copy Example 1 into Colab, Jupyter, or a
.pyfile. - Mark the line you plan to change.
- Write a one-sentence prediction.
- Run the changed code.
- If the result surprises you, restore the original and change a smaller part.
The goal is not to find the only correct answer. The goal is to create a small experiment where you can explain cause and effect.
Common mistakes
WarningCommon mistake
Only testing happy paths can hide bugs. Include edge cases such as empty input or zero.
When you get stuck, use this debugging routine:
- Read the last line of the error message or inspect the unexpected output.
- Find the smallest line of code that could be responsible.
- Print or inspect the value and type at that point.
- Change one thing.
- Run again and record what changed.
Check your understanding
This quiz checks the ideas in this section before you move on.
Notebook and Colab practice
Open a blank notebook at https://colab.new. Use one section at a time: copy the Example 1, predict the result, run it, answer the section quiz, and then move to the next section. This is better than copying the entire page at once.
Instructor note
Teaching notes
- Treat each section as a short teaching episode.
- Pause for the section quiz before introducing the next section.
- Ask learners to compare sections: what stayed the same, and what changed?
- If time is short, teach the first two sections live and assign the rest as practice.
Key points
TipKey points
- Decomposition: Decomposition reduces complexity by solving one small responsibility at a time.
- Testing Functions: A test is executable evidence that a function behaves as expected for a chosen case.
- Use the section quizzes as gates: review before moving on if a quiz feels uncertain.
References
- Defining functions: https://docs.python.org/3/tutorial/controlflow.html#defining-functions
- Python Tutorial: https://docs.python.org/3/tutorial/
- Quarto OJS documentation: https://quarto.org/docs/interactive/ojs/
- ipywidgets documentation: https://ipywidgets.readthedocs.io/en/stable/