This ties in well with the previous infrastructure studies I’ve been completing, and I’d like to be able to combine both skills to build out a cloud-based deployment pipeline for my Python projects.
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To begin with, I’ve created a local development Docker host, with Jenkins installed for CI/CD, and Prometheus and Grafana installed for monitoring. My next step is following the Docker documentation for Pythonwhich details deploying a Flask application to a container. I’ve listed the steps I’ve taken below.
Steps Taken
Prepare Repository and Minimal Flask Server
I’ll be using the GitLab repo that I’ve previously stored files relating to this Docker host, creating a new branch for this project.
mkdir hello-py && cd hello-pyto create a folder within the file structure to hold project filesmkdir server && cd server && touch main.pyto create the code file structure and Flask server entry point, entering the following code:
from flask import Flask
app = Flask(__name__)
@app.route("/")
def home():
return print("hello, py!")
if __name__ == "__main__":
app.run(debug=True)- Within the
hello-py/serverfolder, open a terminal instance and create a Python virtual environment, selecting relevant OS specific commands:
# Linux & macOS
python3 -m venv .venv
source .venv/bin/activate
# Windows
py -3 -m venv .venv
.venv\scripts\activate- Following this, in VSCode, press ⇧⌘P and select the Python interpreter
python -m pip install --upgrade pipwithin VSCode’s .venv terminal to update pippython -m pip install flaskto install Flaskpip freeze > requirements.txtto output the Python package requirements- I added
.venvto the .gitignore file to prevent the folder from being committed to the repo python -m flask runto start the server at URL http://localhost:5000
Create a Dockerfile
touch Dockerfilewithin the hello-py directory create a file to build the custom Docker image# syntax=docker/dockerfile:1specify the Dockerfile syntaxFROM python:3.9.13-slim-busterspecify the base Python image to useWORKDIR /hello-pycreate a working directory for the subsequent commandsCOPY requirements.txt requirements.txtcopy the pip requirements fileRUN pip3 install -r requirements.txtuse the copied requirements file to install pip dependenciesCOPY . .will copy the Python project files into the /hello-py image directoryCMD [ "python3", "-m" , "flask", "run", "--host=0.0.0.0"]supply the command to run that will launch the server, and make it accessible outside of the container
The final Dockerfile code should look like this:
# syntax=docker/dockerfile:1
# base python image for custom image
FROM python:3.9.13-slim-buster
# create working directory and install pip dependencies
WORKDIR /hello-py
COPY requirements.txt requirements.txt
RUN pip3 install -r requirements.txt
# copy python project files from local to /hello-py image working directory
COPY . .
# run the flask server
CMD [ "python3", "-m" , "flask", "run", "--host=0.0.0.0"]Build the Image
docker build --tag hello-py .in the local file’s terminal to build the image using the Dockerfile
Testing the Image in a Local Container
docker run -d -p 5001:5000 hello-pyon my local machine to test that the image was built successfully
I’m using an external port of 5001 on the container on my local machine as I have been using port 5000 for running the Flask server through VSCode’s terminal, and want to make sure there are no conflicts. When we move the image to the remote Docker host I’ll use an external port of 5000
Push to Docker Hub and Deploy to Remote Container
docker login --username=mjrodrun this if required to connect CLI to Docker Hub accountdocker tag hello-py mjrod/hello-pytag the image with your Docker Hub username: <username>/<image-name>docker push mjrod/hello-pyto push a new repository to Docker Hub to store the image
After this, log into the remote Docker host using SSH and run the following
docker pull mjrod/hello-py:latestto pull the previously uploaded image from Docker Hubdocker run -d -p 5000:5000 --name=hello-py mjrod/hello-pyto launch the container
Navigate to http://<remote-docker-ip>:5000 to see the Python application running in the remote container
Next Steps
- Begin coding my Python application — now that I have the ability to package up my Python code and deploy it to a container, I’d like to begin building high-quality web applications to cement both my programming and infrastructure learnings.
- Build a Jenkins pipeline to automate the rebuilding phases for each Docker images — each time I make code changes, the steps outlined in this document will need to be repeated to make the images reflect the code base. I’d like to link my Gitlab repo and my Docker host using Jenkins to automate some of this task away.
