Creating a containerized "Hello World" Python application involves writing a simple Python script and a Dockerfile to containerize the application. Here’s how you can do it:

Create a file named app.py with the following content:

# app.py

print("Hello, World!")

Create a file named Dockerfile in the same directory as your app.py with the following content:

# Use an official Python runtime as a parent image
FROM python:3.12-slim

# Set the working directory in the container
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Run app.py when the container launches
CMD ["python", "app.py"]

Open a terminal, navigate to the directory containing your app.py and Dockerfile, and run the following command to build the Docker image:

docker build -t hello-world-app .

This command tells Docker to build an image with the tag hello-world-app using the current directory (denoted by .) as the context.

After building the Docker image, you can run it with the following command:

docker run hello-world-app

You should see the output Hello, World! in your terminal.

You can verify that the Docker image was created successfully and list all Docker images with the following command:

docker images

To see the running container, use:

docker ps

To see all containers, including stopped ones, use:

docker ps -a

Your project directory should look like this:

hello-world-app/
├── app.py
└── Dockerfile

• Python Base Image: We are using python:3.9-slim, a lightweight Python image. You can choose different versions or variants based on your needs.
• Work Directory: Setting the work directory with WORKDIR /app ensures that all subsequent commands are run in this directory inside the container.
• Copy Command: COPY . /app copies the contents of the current directory on your host into the /app directory in the container.
• Command: CMD ["python", "app.py"] specifies the command to run the Python script when the container starts.

This simple example demonstrates the basic steps to create a containerized Python application. You can expand on this by adding more dependencies, handling environment variables, or integrating with other services.