Coverage reporting in Flask - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is coverage reporting in Flask testing?

Coverage reporting shows which parts of your Flask app's code were run during tests. It helps find untested code.

beginner

Which Python tool is commonly used for coverage reporting in Flask projects?

The 'coverage.py' tool is commonly used to measure code coverage in Flask projects.

intermediate

How do you start coverage measurement before running Flask tests?

You start coverage with 'coverage run -m pytest' to run tests while measuring coverage.

intermediate

What command generates a readable HTML report after running coverage in Flask?

Use 'coverage html' to create an HTML report showing which lines were tested.

beginner

Why is coverage reporting important in Flask app development?

It helps ensure your tests cover all important code, reducing bugs and improving app quality.

Which command runs tests with coverage measurement in a Flask project?

A pytest --coverage

B flask run

C coverage run -m pytest

D coverage report

The command 'coverage run -m pytest' runs tests and measures coverage.

What does the 'coverage html' command do?

A Runs tests with coverage

B Installs coverage.py

C Starts the Flask server

D Generates an HTML report of coverage

'coverage html' creates a visual report showing tested code lines.

Why should you use coverage reporting in Flask testing?

A To speed up the Flask server

B To find untested code

C To deploy the app

D To write HTML pages

Coverage helps identify parts of code not tested by your tests.

Which Python package is essential for coverage reporting?

A coverage.py

B Flask-Login

C requests

D SQLAlchemy

'coverage.py' is the tool used to measure code coverage.

What does a coverage report NOT show?

A How fast the Flask app runs

B Which lines were missed by tests

C Which lines of code ran during tests

D Percentage of code covered by tests

Coverage reports do not measure app speed, only test coverage.

Explain how to set up and use coverage reporting in a Flask project.

Think about commands and why coverage helps.

Describe why coverage reporting improves Flask app quality.

Consider the benefits of knowing test completeness.

Practice

1. What is the main purpose of coverage reporting in a Flask application?

easy

A. To improve the speed of the Flask app

B. To deploy the Flask app to a server

C. To show which parts of the app are tested by your tests

D. To create a user interface for the app

Solution

1. Step 1: Understand coverage reporting

   Coverage reporting tracks which parts of your code are executed during tests.

2. Step 2: Identify its purpose in Flask

   It helps you see which parts of your Flask app have tests and which do not.

3. Final Answer:

   To show which parts of the app are tested by your tests -> Option C

4. Quick Check:

   Coverage reporting = shows tested parts [OK]

Hint: Coverage shows tested code parts, not speed or deployment [OK]

Common Mistakes:

• Confusing coverage with app speed optimization
• Thinking coverage deploys the app
• Assuming coverage creates UI

2. Which command correctly runs tests with coverage in a Flask project?

easy

A. pytest coverage run

B. coverage run -m pytest

C. flask coverage run

D. coverage test run

Solution

1. Step 1: Recall the coverage run syntax

   The correct command to run tests with coverage is 'coverage run -m pytest'.

2. Step 2: Check other options

   Other options mix commands incorrectly or use invalid syntax.

3. Final Answer:

   coverage run -m pytest -> Option B

4. Quick Check:

   Correct coverage test run command = coverage run -m pytest [OK]

Hint: Use 'coverage run -m pytest' to run tests with coverage [OK]

Common Mistakes:

• Swapping order of coverage and pytest
• Using 'flask' command with coverage incorrectly
• Typing 'coverage test run' which is invalid

3. Given you ran coverage run -m pytest successfully, which command shows a text summary of coverage results?

medium

A. coverage report

B. pytest --coverage

C. coverage html

D. flask coverage report

Solution

1. Step 1: Identify commands for coverage output

   'coverage report' shows a text summary in the terminal, while 'coverage html' creates a web page report.

2. Step 2: Eliminate incorrect options

   'pytest --coverage' is not a standard command, and 'flask coverage report' is invalid.

3. Final Answer:

   coverage report -> Option A

4. Quick Check:

   Text summary command = coverage report [OK]

Hint: Use 'coverage report' for text summary, 'coverage html' for web report [OK]

Common Mistakes:

• Confusing 'coverage html' with text output
• Using invalid commands like 'pytest --coverage'
• Trying 'flask coverage report' which doesn't exist

4. You ran coverage run -m pytest but coverage report shows 0% coverage. What is the likely cause?

medium

A. Tests did not execute any Flask app code

B. You forgot to install Flask

C. Coverage report command is misspelled

D. You ran coverage without pytest

Solution

1. Step 1: Understand 0% coverage meaning

   0% coverage means no code was executed during tests, so coverage tool found no lines run.

2. Step 2: Analyze possible causes

   If tests ran but did not call Flask app code, coverage stays zero. Missing Flask or misspelling commands would cause errors, not zero coverage.

3. Final Answer:

   Tests did not execute any Flask app code -> Option A

4. Quick Check:

   0% coverage = no app code run in tests [OK]

Hint: 0% means tests ran but didn't touch app code [OK]

Common Mistakes:

• Assuming 0% means Flask is not installed
• Thinking coverage report command typo causes 0%
• Believing running coverage without pytest causes 0%

5. You want to generate a detailed HTML coverage report for your Flask app after running tests. Which sequence of commands is correct?

hard

A. flask coverage run; coverage html; open html/index.html

B. pytest run coverage; coverage report; open index.html

C. coverage test run; coverage html; open coverage/index.html

D. coverage run -m pytest; coverage html; open htmlcov/index.html

Solution

1. Step 1: Run tests with coverage

   Use 'coverage run -m pytest' to run tests and collect coverage data.

2. Step 2: Generate HTML report and open it

   Run 'coverage html' to create the report in 'htmlcov' folder, then open 'htmlcov/index.html' to view it.

3. Step 3: Verify other options

   Other options use invalid commands or wrong paths for report files.

4. Final Answer:

   coverage run -m pytest; coverage html; open htmlcov/index.html -> Option D

5. Quick Check:

   Run tests, generate HTML, open htmlcov/index.html [OK]

Hint: Run tests, then 'coverage html', then open htmlcov/index.html [OK]

Common Mistakes:

• Using wrong command order or invalid commands
• Opening wrong file path for HTML report
• Confusing 'pytest run coverage' with correct syntax