CI/CD pipeline for Flask - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does CI/CD stand for in software development?

CI/CD stands for Continuous Integration and Continuous Delivery (or Continuous Deployment). It means automatically testing and delivering code changes to users quickly and safely.

beginner

Why use a CI/CD pipeline for a Flask application?

A CI/CD pipeline helps catch errors early, speeds up delivery, and makes sure your Flask app updates smoothly without breaking for users.

beginner

Name a common tool used for running automated tests in a Flask CI pipeline.

Pytest is a popular tool to run automated tests for Flask applications during the CI process.

intermediate

What is the role of Docker in a CI/CD pipeline for Flask?

Docker packages your Flask app and its environment into a container, making it easy to test and deploy consistently across different machines.

intermediate

Explain the difference between Continuous Delivery and Continuous Deployment.

Continuous Delivery means your code is always ready to be released but needs manual approval. Continuous Deployment means code changes are automatically released to users after passing tests.

What is the first step in a typical CI/CD pipeline for a Flask app?

A Push code to the repository

B Build the Docker image

C Run automated tests

D Deploy to production

The pipeline usually starts when code is pushed to the repository, triggering the next steps automatically.

Which file commonly defines the steps of a CI/CD pipeline in GitHub Actions?

A app.py

B requirements.txt

C Dockerfile

D .github/workflows/*.yml

GitHub Actions workflows are defined in YAML files inside the .github/workflows directory.

What command installs dependencies listed in requirements.txt for a Flask app?

A pip install -r requirements.txt

B python app.py

C docker build .

D pytest

The command 'pip install -r requirements.txt' installs all Python packages needed by the app.

In a CI/CD pipeline, what does 'automated testing' help prevent?

A Manual code writing

B Slow internet

C Code errors and bugs

D Server crashes unrelated to code

Automated tests check code for errors and bugs before deployment.

Which tool can be used to deploy a Flask app to a cloud service in a CI/CD pipeline?

A npm

B Heroku CLI

C Git

D pytest

Heroku CLI is used to deploy apps to the Heroku cloud platform.

Describe the main stages of a CI/CD pipeline for a Flask application.

Think about what happens from writing code to making it live.

Explain how Docker helps in deploying a Flask app in a CI/CD pipeline.

Imagine packing your app in a box that works anywhere.

Practice

1. What is the main purpose of a CI/CD pipeline for a Flask application?

easy

A. To automate testing and deployment whenever code changes

B. To manually deploy code after testing

C. To write Flask application code faster

D. To create user interfaces automatically

Solution

1. Step 1: Understand CI/CD pipeline role

   A CI/CD pipeline automates the process of testing and deploying code changes to catch errors early and speed up delivery.

2. Step 2: Match purpose with options

   To automate testing and deployment whenever code changes correctly states automation of testing and deployment on code changes, which is the main goal of CI/CD.

3. Final Answer:

   To automate testing and deployment whenever code changes -> Option A

4. Quick Check:

   CI/CD automates testing and deployment = C [OK]

Hint: CI/CD means automatic test and deploy on code change [OK]

Common Mistakes:

• Thinking CI/CD writes code
• Confusing manual deployment with CI/CD
• Assuming CI/CD creates UI automatically

2. Which of the following is a correct minimal GitHub Actions workflow file name and location for a Flask CI/CD pipeline?

easy

A. .github/workflows/flask-ci.yml

B. github/actions/flask-ci.yaml

C. .github/actions/flask-ci.yml

D. workflows/.github/flask-ci.yml

Solution

1. Step 1: Identify GitHub Actions workflow file location

   GitHub Actions requires workflow files inside the repository at .github/workflows/ directory.

2. Step 2: Check file name and extension

   The file should have a .yml or .yaml extension. .github/workflows/flask-ci.yml uses correct directory and file name.

3. Final Answer:

   .github/workflows/flask-ci.yml -> Option A

4. Quick Check:

   Workflow files go in .github/workflows/ = D [OK]

Hint: GitHub Actions workflows live in .github/workflows/ [OK]

Common Mistakes:

• Placing workflow files outside .github/workflows/
• Using wrong file extensions
• Misnaming the directory

3. Given this GitHub Actions snippet for a Flask app:

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.12'
      - name: Install dependencies
        run: pip install -r requirements.txt
      - name: Run tests
        run: pytest

What will happen when this workflow runs?

medium

A. It only installs dependencies without running tests

B. It checks out code, sets Python 3.12, installs dependencies, and runs tests

C. It runs tests without installing dependencies

D. It fails because Python version is missing

Solution

1. Step 1: Analyze each step in the workflow

   The workflow checks out the code, sets up Python 3.12, installs dependencies from requirements.txt, then runs pytest tests.

2. Step 2: Confirm all steps are present and correct

   All steps are correctly ordered and complete, so the workflow will perform all these actions successfully.

3. Final Answer:

   It checks out code, sets Python 3.12, installs dependencies, and runs tests -> Option B

4. Quick Check:

   Checkout + setup + install + test = B [OK]

Hint: Check steps order: checkout, setup, install, test [OK]

Common Mistakes:

• Assuming tests run without installing dependencies
• Thinking Python version is missing
• Ignoring the checkout step

4. You wrote this GitHub Actions step to install dependencies:

- name: Install dependencies
  run: pip install requirements.txt

Why does this step fail in your Flask CI/CD pipeline?

medium

A. Because pip install cannot run in GitHub Actions

B. Because requirements.txt file is missing

C. Because the command should be 'pip install -r requirements.txt'

D. Because Python version is not specified

Solution

1. Step 1: Identify the pip install syntax error

   The command 'pip install requirements.txt' tries to install a package named 'requirements.txt' instead of reading the file.

2. Step 2: Correct the command syntax

   The correct command to install from a requirements file is 'pip install -r requirements.txt'. This flag tells pip to read the file.

3. Final Answer:

   Because the command should be 'pip install -r requirements.txt' -> Option C

4. Quick Check:

   Use '-r' flag to install from file = A [OK]

Hint: Use 'pip install -r requirements.txt' to install dependencies [OK]

Common Mistakes:

• Omitting the '-r' flag
• Assuming pip install can't run in CI
• Blaming missing Python version

5. You want to deploy your Flask app automatically after tests pass using GitHub Actions. Which step should you add to your workflow to deploy to Heroku?

hard

A. Add a step that runs 'pip install flask-heroku'

B. Add a step that runs 'heroku login' interactively

C. Add a step that copies files to a local folder

D. Add a step using 'akhileshns/heroku-deploy@v3.12.12' action with Heroku API key and app name

Solution

1. Step 1: Understand automated deployment in GitHub Actions

   To deploy automatically, use a GitHub Action designed for Heroku deployment that accepts API keys and app name securely.

2. Step 2: Identify correct deployment action

   The 'akhileshns/heroku-deploy@v3.12.12' action is a popular choice for Heroku deployment in GitHub workflows.

3. Final Answer:

   Add a step using 'akhileshns/heroku-deploy@v3.12.12' action with Heroku API key and app name -> Option D

4. Quick Check:

   Use Heroku deploy action with API key = A [OK]

Hint: Use Heroku deploy GitHub Action with API key for auto deploy [OK]

Common Mistakes:

• Trying interactive login in CI
• Copying files locally instead of deploying
• Installing unrelated packages