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}Testing and README
capstone
Protect capstone behavior with tests and explain the project clearly.
Questions
- What problem does Testing and README 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 capstone tests and README 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: Testing and README
A capstone should include minimal tests for important functions and a README with purpose, setup, usage, example output, limitations, and next steps.
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
Read the test and README line as two forms of the same promise.
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 name says what behavior matters.
- The test gives one concrete example of correct behavior.
- A README usage example should show a similar input and output so people know what to expect.
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 a test for an empty week and decide whether the total should be 0 or an error. Writing the test forces a design decision.
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 a test for an empty week and decide whether the total should be 0 or an error.
Debugging checkpoint 1.1
WarningDebugging checkpoint
Do not write a README that only says ‘run the project’ without commands. Also avoid tests that require private files or a local path only you have.
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
Create a README skeleton with project purpose, setup command, run command, example output, test command, and limitation. Then write two tests for the main behavior.
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
Protect capstone behavior with tests and explain the project clearly.
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 Testing and README 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. Testing Your Project — Add practical tests that protect the main behavior of your capstone.
- 2. Writing a README — Explain what your project does, how to run it, and how to understand the results.
1. Testing Your Project
Add practical tests that protect the main behavior of your capstone.
TipAnalogy
Tests are guardrails on a bridge: they do not move the project forward, but they keep it from falling.
What this means
Project tests capture examples of correct behavior so changes can be made safely.
Example 1
Predict what will happen before you run the code.
Step-by-step explanation
def normalize_name(name):— pause here and say what this line reads, creates, changes, or displays.return name.strip().title()— pause here and say what this line reads, creates, changes, or displays.assert normalize_name(" ada ") == "Ada"— 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
Do not postpone all tests until the end. Add tests when behavior becomes important.
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. Writing a README
Explain what your project does, how to run it, and how to understand the results.
TipAnalogy
A README is a museum label: it gives enough context for visitors to appreciate what they are seeing.
What this means
A README is the front door to your project for future you and other people.
Example 2
Predict what will happen before you run the code.
Step-by-step explanation
# Project Title— pause here and say what this line reads, creates, changes, or displays.## What it does— pause here and say what this line reads, creates, changes, or displays.Short explanation.— pause here and say what this line reads, creates, changes, or displays.## How to run— pause here and say what this line reads, creates, changes, or displays.python main.py— 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 README that only says the title does not help someone run or evaluate your work.
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
- Testing Your Project: Project tests capture examples of correct behavior so changes can be made safely.
- Writing a README: A README is the front door to your project for future you and other people.
- Use the section quizzes as gates: review before moving on if a quiz feels uncertain.
References
- Python packaging user guide: https://packaging.python.org/en/latest/
- The Turing Way reproducible research: https://book.the-turing-way.org/reproducible-research/reproducible-research
- 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/