Containerizing Python applications with Docker
Docker is a platform that allows you to package applications and their dependencies into containers. Containers are lightweight, portable, and self-sufficient units that can run consistently across different environments. A Dockerfile contains instructions for building a Docker image, which is a template for creating containers. Key Docker concepts include: images (read-only templates), containers (running instances of images), registries (stores for images like Docker Hub), and volumes (persistent data storage). Docker helps solve the 'it works on my machine' problem by ensuring consistent environments from development to production. For Python applications, Docker typically involves creating a minimal base image, copying application code, installing dependencies, and specifying how to run the application. Understanding Docker is essential for modern application deployment, microservices architectures, and cloud-native development.