In the world of data engineering, the "it works on my machine" excuse is a relic of the past. Docker has revolutionized how we build and deploy applications by using containerization. A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another. Why Containerize? Isolation : Keep your Python libraries for one project separate from another. Portability : Run the same container on Ubuntu, Windows (via WSL), or macOS. Scalability : Easily spin up multiple instances of a service. Essential Docker Commands To manage your containers effectively, you must master these core CLI commands: Command Description docker build -t my-image . Builds an image from a Dockerfile in the current directory. docker run -d --name my-container my-image Runs a container in the background (detached mode). docker ps -a Lists all containers, including those that have stopped.…