š Hi!
In this article, I'll walk you through the steps I took to revamp my aging Python applications and migrate them to a Docker container on a production server.
The Legacy Setup
Several years ago, I had a collection of Python applications that I shared with my coworkers using an old Windows server. This server hosted Jupyter Notebook with remote access enabled.
Today, to my surprise, I realised that some of these scripts were still being actively used by a group of users.
I decided to migrate the jupyter notebook server to a Docker container.
Creating the Dockerfile
We need a Dockerfile
, which is essentially a recipe for building a Docker image. This file included all the necessary instructions to set up a Python environment, install the required libraries, and configure Jupyter Notebook.
# Use an official Python 3.11 image
FROM python:bookworm
# Need voila to serve the scripts as applications
RUN pip install voila
RUN pip install notebook
# Create the isolated dir on docker
RUN mkdir /jupyterbooks
WORKDIR /jupyterbooks
EXPOSE 8888
# Run jupyter with remote access enabled
CMD sh -c "jupyter notebook --no-browser --allow-root --IdentityProvider.token='yourSecretToken' --ServerApp.allow_origin='*' --ServerApp.port=8888 --ServerApp.allow_remote_access=True --ServerApp.ip='0.0.0.0'"
Also created a docker-compose.yml
file to configure the container
version: "3.3"
services:
jupyter-service:
container_name: jupyter-service
build:
context: .
dockerfile: Dockerfile
image: jupyter-service
restart: always
ports:
- 8888:8888
volumes:
- jupyter-data:/jupyterbooks
volumes:
jupyter-data:
name: jupyter-data
Copied the old scripts at the new docker jupyter-data volume with docker cp myNotebooks jupyter-service:/jupyterbooks/
And finally docker compose up -d
does the trick.
Conclusion
I'ts amazing how two short files can configure such a service.
Now I can access the notebook with my token and the users can consume the applications without password through voila.
Cheers!
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