This project demonstrates how to work with GitHub Actions by implementing CI/CD workflows and leveraging Docker Hub for container management.

This repository contains a GitHub Actions workflow that automates tasks for a Flask application using Docker. It ensures the application is tested, built, and deployed automatically whenever changes are made to the code.

How It Works The workflow is triggered when:

Code is pushed to the main branch. A pull request is opened for the main branch. Steps in the Workflow

1. Workflow Events

   • push: Runs the workflow when you push code to the main branch.
   • pull_request: Runs the workflow when someone creates a pull request targeting the main branch.

2. Jobs The workflow is divided into three jobs:

   • dockerbuild
   • build-and-test
   • build-and-publish

• Job 1: Build Docker Image

Purpose: Builds a Docker image for the application. Steps: Checkout the code: Downloads the repository code. Build the Docker image: docker build .: Builds the image using the DockerFile. --tag: Tags the image with a unique name, including the current timestamp.

• Job 2: Build and Test

Purpose: Verifies the code works correctly by running tests. Steps: Checkout the code: Same as in Job 1. Set up Python: Installs Python version 3.9 for testing. Install dependencies: Installs required Python packages from requirements.txt. Run tests: Executes tests using pytest to verify application functionality.

• Job 3: Build and Publish Docker Image

Purpose: Publishes the Docker image to DockerHub. Steps:

1. Checkout the code: Same as before.
2. Set up Docker Buildx: Prepares for advanced Docker builds.
3. Login to DockerHub: DOCKER_USERNAME and DOCKER_PASSWORD are securely stored as GitHub secrets.
4. Build and push the Docker image: Builds the image using the DockerFile. Pushes the image to DockerHub with the tag latest.
5. Output the image digest: Prints a unique identifier for the pushed image.

This workflow simplifies the development process by automating testing, building, and deploying the Flask application, saving time and reducing manual errors.