Recently I have began to use Jupyter notebooks with Python but have struggled with the constant need to download dependencies or have something not...
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Great tutorial, good work!
My suggestion is to learn docker compose next to avoid having to type incredibly lengthy
docker runcommands.It also helps you keep everything under version control so you can easily share your creations with other people with minimal guesswork on their part.
Thanks, I'll have to check that out!
Great post! I'm a huge fan of using Docker for Data Science.
I gave a talk a few months ago on how to incorporate Docker into various Data Science Workflows. Hope you find it useful!
Thanks! I will look into it. Just started using it and loving it already.
Awesome post @rosejcday . Mapbox actually just launched a library for location data visualizations with Jupyter Notebooks, check it out and lmk what you think! github.com/mapbox/mapboxgl-jupyter
This post is a great intro to setting up Jupyter using Docker! 👍🏼
I fought with a similar setup myself, after deciding to stop misusing my MacBook for data science experiments, and deploy a Docker container on the Google Cloud instead. Besides the things you have listed in your post, I had to tackle bundling a dedicated SHA-hashed Jupyter password, because my instance is publicly accessible over the Internet. Another issue I had to deal with was bundling the image with a private key for accessing the git repository where I keep my experiments. Not all without issues, but I managed. Maybe, I should sit down and write a post about this. Perhaps, it will be helpful to you and others.
The Docker Hub link is incorrect in
"Download the Docker image from Docker Hub."
Weird! It was the right link when I checked, try again and see if it works now for you.
It works now. Thanks for the article : )
I love docker and also how easy it is to use for Data Science. Thank you.
Why you don't use virtualenv?
What would the benefit of using virtualenv be inside a docker container? I have researched it but everyone seems to have mixed views on using it or not using it.
I mean, use virtualenv instead of docker
I like the portability of Jupiter too. I use it to 1) write stories out of data for management and to 2) write tutorials for Python. What are your use cases?
At the moment I use it mainly for school. It has been great for school projects that need to be shared between a team.