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Dockerizing your Python app for CI/CD [Continuous Integration and Continuous Deployment/Delivery

 

Dockerizing Your Python App for CI/CD

Dockerizing your Python application helps ensure consistent environments across different stages of your CI/CD pipeline, from local development to production.

Why Docker for CI/CD?

  • Consistent environment across development, testing, and production.
  • Easier dependency management.
  • Simplifies deployment.
  • Works seamlessly with CI/CD tools like GitHub Actions, GitLab, Jenkins, and AWS.

Prerequisites

  • Docker installed on your machine.
  • Python application with tests using Pytest.
  • CI/CD platform (e.g., GitHub Actions, GitLab CI/CD).

Folder Structure

my_project/
├── api.py              # Application code
├── test_api.py         # Pytest test cases
├── requirements.txt    # Python dependencies
├── Dockerfile          # Docker instructions
└── .github/
    └── workflows/
        └── ci_cd.yml   # CI/CD Pipeline (GitHub Actions example)

Step 1: Create Dockerfile

The Dockerfile defines how to build your application into a Docker image.

Dockerfile

# Use official Python image
FROM python:3.10-slim

# Set working directory
WORKDIR /app

# Copy requirements and install dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy app source code
COPY . .

# Run tests by default
CMD ["pytest"]

Step 2: Create requirements.txt

List your project dependencies:

aiohttp
pytest
pytest-asyncio

Step 3: Build Docker Image Locally

To build the Docker image locally, run:

docker build -t my_project .

Run the container:

docker run --rm my_project

If tests pass, you'll see the Pytest output.

Step 4: GitHub Actions CI/CD Pipeline

We'll configure GitHub Actions to automatically:

  1. Build the Docker image.
  2. Run tests inside the container.

Create the CI/CD pipeline at:

.github/workflows/ci_cd.yml

ci_cd.yml

name: CI/CD Pipeline

on:
  push:
    branches:
      - main
  pull_request:
    branches:
      - main

jobs:
  docker-build:
    runs-on: ubuntu-latest

    steps:
      - name: Checkout code
        uses: actions/checkout@v3

      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v2

      - name: Build Docker Image
        run: docker build -t my_project .

      - name: Run Tests
        run: docker run --rm my_project

Step 5: Push Code to GitHub

Commit and push your code:

git add .
git commit -m "Dockerize app with CI/CD"
git push origin main

Step 6: View Pipeline Results

  1. Go to your GitHub repository.
  2. Navigate to the Actions tab.
  3. Click on the latest pipeline run to view the logs.

Docker Image Publishing (Optional)

If you want to publish your Docker image to Docker Hub or GitHub Packages, add these steps:

- name: Log in to Docker Hub
  uses: docker/login-action@v2
  with:
    username: ${{ secrets.DOCKER_USERNAME }}
    password: ${{ secrets.DOCKER_PASSWORD }}

- name: Push Docker Image
  run: docker push my_project:latest

Best Practices

  • Use multi-stage builds to optimize image size.
  • Add health checks to Docker containers.
  • Use environment variables for configuration.
  • Automatically remove old images using Docker cleanup tools.

Conclusion

Dockerizing your Python app for CI/CD ensures consistent environments, faster testing, and simplified deployments. By combining Docker with Pytest and CI/CD pipelines, you can achieve seamless automation from code commit to production deployment.


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