Appearance

Integrating Docker & CI/CD ​

Going deep into Docker and CI/CD will take a few more lessons, but this page gives you a simple overview of what they are, how they fit into your workflow, and when they can make your life easier. You don’t need to master them right now — just keep this in your loop, and when your projects start to grow or involve collaboration, you’ll know when it’s time to explore them in more detail.

What Docker and CI/CD Do ​

Docker lets you package your entire working setup — Python, FEniCS, libraries, and scripts — into one portable environment. So whether you’re running it on your laptop, a lab computer, or a cloud server, everything behaves exactly the same.

CI/CD (Continuous Integration and Continuous Deployment) takes it one step further. It can automatically build your Docker setup, run tests, and check that your simulations or scripts still work every time you push code to GitHub.

Together, they make your workflow more consistent, automated, and reproducible.

How You Can Use It ​

Here’s how a simple setup usually works:

  1. Create a Dockerfile — this file defines what your environment looks like (Python version, FEniCS, meshio, etc.).
  2. Build the image — run it once locally to make sure everything installs and runs correctly.
  3. Add a GitHub Action — a small automation file (.github/workflows/test.yml) that automatically builds and runs your code whenever you push to the repo.
  4. Share or deploy — push your Docker image to Docker Hub so that teammates or servers can use it instantly.

For example:

yaml
on: [push]
jobs:
  test-solver:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Build and test solver
        run: |
          docker build -t fenics-solver .
          docker run fenics-solver python3 main_solver.py

This means every time you update your repo, your solver gets tested automatically — no manual setup required.

Why It’s Useful ​

  • Consistency: Everyone uses the same environment, so results are easier to reproduce.
  • Automation: Tests and builds happen automatically when you push code.
  • Reproducibility: You can recreate your setup even months later.
  • Scalability: Easily move to cloud or remote servers when simulations get heavier.

Summary ​

Docker and CI/CD aren’t must-haves for every small study, but they become very powerful as your work grows. For now, just remember that these tools can automate your workflows and keep your projects reproducible. When you reach a stage where setup management or collaboration becomes complex — that’s the perfect time to explore Docker and CI/CD in depth.