Deploying Python Apps with Docker

Introduction
Prerequisites
Setting Up Docker
Creating a Dockerfile
Building the Docker Image
Running the Docker Container
Conclusion

Introduction

In this tutorial, we will learn how to deploy Python applications using Docker. Docker is a containerization platform that allows you to package your application and its dependencies into a standardized unit called a Docker container. By containerizing your application, you can ensure that it runs consistently across different environments, making deployment easier and more efficient.

By the end of this tutorial, you will be able to:

Understand the basics of Docker and containerization
Set up Docker on your machine
Create a Dockerfile to define the container image
Build and run the Docker container for your Python application

Prerequisites

Before you begin this tutorial, ensure that you have the following:

Basic knowledge of Python programming
Docker installed on your machine

Setting Up Docker

Before we can start deploying Python apps with Docker, we need to set up Docker on our machine. Follow these steps to get Docker up and running:

Install Docker: Visit the Docker website (https://www.docker.com/products/docker-desktop) and download Docker Desktop for your operating system. Follow the installation instructions provided by Docker.
Verify Installation: Open a terminal or command prompt and enter the command docker version. This should display the installed version of Docker and other details. If you see the version information, Docker is installed correctly.
Start Docker: Launch Docker Desktop from your applications or system tray. Once Docker is running, you’ll see its icon in the system tray (Windows) or menu bar (macOS). Docker may take a few moments to start up.
Test Docker: Open a terminal or command prompt and enter the command docker run hello-world. This command will pull a lightweight Docker image and run a test container. If you see the message “Hello from Docker!”, Docker is working correctly.

Creating a Dockerfile

To deploy a Python app with Docker, we need to create a Dockerfile. The Dockerfile is a text file that contains instructions for building the Docker image. Here’s an example Dockerfile for a simple Python web application: ```Dockerfile # Use the official Python base image FROM python:3.9

# Set the working directory in the container
WORKDIR /app

# Copy the dependencies file to the working directory
COPY requirements.txt .

# Install the dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Copy the rest of the application files to the working directory
COPY . .

# Set the command to run the application
CMD [ "python", "app.py" ]
``` Let's go through the different instructions in this Dockerfile:

FROM python:3.9: We start with the official Python base image, version 3.9.
WORKDIR /app: We set the working directory inside the container to /app.
COPY requirements.txt .: We copy the requirements.txt file from our local directory to the working directory inside the container.
RUN pip install --no-cache-dir -r requirements.txt: We install the Python dependencies specified in requirements.txt.
COPY . .: We copy the rest of the application files from our local directory to the working directory inside the container.
CMD [ "python", "app.py" ]: We set the command to run the Python application when the container starts.

You can adjust this Dockerfile based on the specific requirements of your Python application.

Building the Docker Image

Once we have the Dockerfile ready, we can build the Docker image. The Docker image is a snapshot of the container configuration and dependencies. Run the following command to build the image: docker build -t my-python-app . Let’s understand the command:

docker build: This command builds a Docker image using the Dockerfile in the current directory.
-t my-python-app: This specifies the name and tag for the Docker image. Change my-python-app to a custom name if desired.
.: This specifies the build context, which is the current directory. The build context includes all files in the current directory and its subdirectories.

During the build process, Docker will execute each instruction in the Dockerfile to create the image. If all goes well, you should see output indicating that the image was successfully built.

Running the Docker Container

Now that we have the Docker image, we can run a Docker container based on that image. Use the following command to run the container: docker run -d -p 5000:5000 my-python-app Let’s break down the command:

docker run: This command runs a new Docker container.
-d: This option runs the container in detached mode, meaning it runs in the background.
-p 5000:5000: This option maps port 5000 from the container to port 5000 on the host machine. Replace the port numbers if your Python app runs on a different port.
my-python-app: This specifies the Docker image to use for the container.

Once the container is running, you can access your Python app by opening a web browser and navigating to http://localhost:5000 (or the respective port you specified).

Conclusion

Congratulations! You have successfully learned how to deploy Python apps with Docker. We covered the basics of Docker, set up Docker on your machine, created a Dockerfile to define the container image, and built and ran the Docker container for your Python application.

Docker provides a powerful and efficient way to package and deploy applications, making it easier to manage dependencies and ensure consistent behavior across different environments. You can now apply this knowledge to deploy your own Python apps with Docker.

Remember to stop the running Docker container using the command docker stop CONTAINER_ID when you’re done testing your app.

Published: 13 March 2023