Navigating the coding world presents a multitude of tools to explore, one of which is Docker. Our journey today includes an exploration of Docker alongside Python – two essential coding tools that provide indispensable benefits in the software development world. This interactive and beginner-friendly tutorial will unveil how to utilize these tools, dissecting basic principles and highlighting real examples.
Table of contents
What is Docker?
Docker is an open-source platform aimed at automating the deployment, scaling, and management of applications. The essence of Docker lies in its ability to allow developers to create applications in any language and then bundle them in containers.
What do we use Docker for?
The power of Docker is harnessed by developers to ensure their applications run smoothly in any environment. It eliminates the common phrase in development circles: “It works on my machine”. Docker ensures that if it works on one machine, it will work in any other.
Why Pair Python with Docker?
Python’s versatility and ease of use make it a top choice among developers. When combined with Docker, it makes deploying Python web applications a breeze, ensuring that regardless of where your app is hosted, it will run as intended. This tangible skillset not only adds value in real-world applications but also establishes a solid platform for advanced learning.
Why should you learn it?
Python and Docker are both high-demand skills in the tech industry. Learning these tools increases your versatility as a developer and opens the doors to exciting, dynamic projects. Evidently, this is not just another coding tutorial. Let’s gear up to gain some highly marketable skills in the tech world.
Setting up Docker
Firstly, we need to ensure Docker is installed on our machine. If it’s not, you can download it from the official Docker website.
Creating a Dockerfile
More often than not, a Docker container will be initiated with a Dockerfile. A Dockerfile is simply a text document that contains all the commands required to build a Docker image. Let’s create a simple Dockerfile for our Python application.
# Use an official Python runtime as a parent image FROM python:3.7-slim # Set the working directory in the container WORKDIR /app # Add contents from your local directory to the container's directory ADD . /app # Install any needed packages specified in requirements.txt RUN pip install --no-cache-dir -r requirements.txt # Run app.py when the container launches CMD ["python", "app.py"]
Building a Docker Image
With our Dockerfile in place, we can now build our Docker image. From the command line, we use the following command:
docker build -t python-app:latest .
Running a Docker Container
After building the Docker image, we can create and start a Docker container from it:
docker run -it python-app:latest
Inspecting a Docker Container
Should you need to inspect a container, for example, check our Python install version, you can execute a command inside of it:
docker exec -it mycontainer python --version
Congratulations! You are now able to build a Docker image and run a Docker container!
In the third part of our tutorial, we will continue looking at more advanced Docker commands and concepts. Be sure to tune in and expand your Docker knowledge!
Interactive Shell Access
Sometimes, there might be a necessity to access the shell directly within the container. Docker allows this using the following command:
docker exec -it mycontainer /bin/bash
Displaying Running Containers
There may be various containers running at once, and it’s essential to keep track. To see a list of all running containers, we use the following command:
If you want to see all containers, both running and stopped, use this one:
docker ps -a
Stopping and Removing Containers
Stopping a Docker container is also straightforward. Here’s how we can do it:
docker stop mycontainer
After stopping a container, you might want to remove it completely. To do so, we use the rm command:
docker rm mycontainer
Creating a Docker Network
For several containers to communicate with each other, we can create a Docker network:
docker network create mynetwork
Adding Containers to a Network
Now, let’s add containers to the network we created. We use the run command but with an additional network option:
docker run -it --network=mynetwork python-app:latest
Great job! Now that you’re well-versed with Docker and Python, you’re fully prepared to optimize your development process. However, learning is an ongoing process, and there is always room for more. Stay tuned for the next installment where we dive even deeper!
Where To Go Next – Continuing Your Journey
Your journey doesn’t have to end here. There’s a universe of knowledge waiting for you to explore, and we at Zenva are here to guide you along the path.
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All in all, the world of Python and Docker has so much to offer, and at Zenva, we can’t wait to guide you towards your goals. So, are you ready to take the next step in your coding journey?
Mastering the combination of Docker and Python is a worthwhile endeavor, demanding in tech industries worldwide. Making this skill set part of your coding arsenal promises to take your projects to the next level, providing you with a more efficient, reliable, and optimized development process.
At Zenva, we’re committed to empowering you on your learning journey. Equipped with our Python Mini-Degree or our wide range of python courses, you’ll be more than ready to take the coding world by storm. So why wait? Kick start your journey to becoming a Docker and Python pro with us today!
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