Introduction to Docker for Python and Django

Using containers to build and deploy applications.


Docker is a versatile containerization platform to help application development, distribution, and execution. It speeds delivery by letting you decouple your applications from the underlying infrastructure, which can then be treated like code. With Docker's code distribution, testing, and deployment, you can markedly minimize the time gap between development and production.

Key Docker concepts include:

  1. Container: A standalone, executable unit with the software, code, runtime, libraries, and system tools. It isolates applications for consistent performance across environments.

  2. Docker Image: A lightweight, executable package for software deployment. Used to create containers, these images are stored in registries like Docker Hub.

  3. Dockerfile: A script with instructions to build a Docker image. It defines the base image, environment setup, dependencies, and application configuration.

  4. Docker Hub: A cloud-based service for sharing Docker images. It acts as a centralized repository for Docker image management and collaboration.

  5. Container Orchestration: Docker works with tools like Docker Compose, Kubernetes, or Docker Swarm for managing container deployment, scaling, and networking.

  6. Docker Compose: This tool defines and runs multi-container Docker applications, using a single docker-compose.yml file for application management.

  7. Docker Swarm: A native Docker clustering and orchestration solution. It transforms a group of Docker nodes into a single virtual host, offering load balancing, rolling updates, and service discovery.

Docker streamlines building, shipping, and running applications consistently, making it a preferred choice for modern application development and deployment due to its ease of use, portability, and scalability.


For installation, refer to the official documentation for detailed instructions.