Building Docker Images for a Python Flask Server - A Step-by-Step Guide
Welcome back to Continuous Improvement, the podcast where we delve into the tools and technologies that enhance our digital worlds. I’m your host, Victor Leung, and today, we’re diving into the practical world of Docker and how it revolutionizes application deployment, specifically for Python Flask applications.
Docker has transformed the way we deploy applications by ensuring consistency across environments. Today, I’ll walk you through the steps to build a Docker image for a simple Python Flask server, from scratch to execution.
Let’s start with the basics. You’ll need a Flask application. Here’s a simple example:
# app.py
from flask import Flask
app = Flask(__name__)
@app.route('/')
def home():
return "Welcome to the Flask App!"
if __name__ == '__main__':
app.run(host='0.0.0.0', port=5000)
This code sets up a basic server that responds with a welcome message.
Next up, the requirements.txt
file. This is crucial as it lists all the dependencies your application needs:
Flask==2.2.2
Werkzeug==2.2.2
It’s a straightforward list that tells Docker what to install to run your application.
Now, let’s write a Dockerfile, which is essentially a blueprint for building your Docker image:
# Dockerfile
FROM python:3.10-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD [ "python", "./app.py" ]
This setup pulls a lightweight Python image, sets up a working directory, installs dependencies, and specifies how to run your application.
With your Dockerfile ready, it’s time to build your image. Open your terminal and run:
docker build -t flask-app .
This command builds the image locally and tags it as flask-app
.
Finally, to run your Flask app in a Docker container, execute:
docker run -p 5000:5000 flask-app
This command runs your image as a container and maps port 5000 on your local machine to port 5000 on the container, making your server accessible via localhost:5000
.
And there you have it! You’ve just containerized a Python Flask application using Docker. This process not only simplifies development and testing but also streamlines production deployments. Docker ensures your application runs consistently, regardless of where it’s deployed.
Thanks for tuning in to Continuous Improvement. I hope today’s episode inspires you to experiment with Docker and perhaps integrate it into your development workflow. Until next time, keep learning, keep improving, and remember, the best way to predict the future is to invent it. I’m Victor Leung, signing off.