Create a Docker File and using Docker file Build Images

A Dockerfile is a text file that contains all the commands a user could call on the command line to assemble an image. This Dockerfile example sets up a lightweight Python application container. It performs several key actions:

• Uses the python:3.8-slim image as a base.

• Sets the working directory inside the container to /app.

• Copies the current directory's contents into the container at /app.

• Installs dependencies listed in requirements.txt.

• Makes port 80 available to the container's external network.

• Sets an environment variable NAME with the value World.

• Specifies that the container runs app.py with Python when it launches.

Performing Tasks with Docker in a New Folder

To streamline your Docker workflows, follow these steps to create a folder where you can perform all related tasks:

1. Create a New Folder: Open your terminal and use the command mkdir your-folder-name to create a new folder where you will carry out your Docker tasks.

2. Navigate to Your New Folder: Change your current directory to the newly created folder by entering cd your-folder-name.

3. Initialize Your Docker Project: Inside the folder, you can now perform all Docker-related tasks, such as initializing Docker projects, creating Docker files, and managing Docker containers and images.

By organizing your Docker tasks within a specific folder, you maintain a clean and efficient workflow.

• mkdir docker_config

• vi Dockerfile

This Dockerfile provides a clear, reproducible method for building a containerized Python application.

* docker build . -t my_python_app .

This command will build your Docker container based on the instructions in the Docker file you created. Make sure you run this command within the docker_config directory where your Dockerfile is located. The -t flag tags your image my_python_app for easy reference.

To verify that your Docker image has been successfully built, use the docker images command, which will list all Docker images on your system, including your newly created my_python_app image. This allows you to confirm that your image is ready for use.

• docker images

Manage Images Commands

To remove the images

• docker rmi image_name/imgae_id

Lists images

• docker image ls

Tags an image

• docker tag image_name/image_id tag_name