- Jupyter for Data Science
- Dan Toomey
- 180字
- 2021-07-08 09:22:35
Using a public Docker service
There are several services out there. I think they work pretty much the same way: sign up for the service, upload your notebook, monitor usage (the Docker control program tracks usage automatically). For example, if we use https://hub.docker.com/ we are really using a version repository for our notebook. Versioning is used in software development for tracking changes that are made over time. This also allows for multiple user access privileges as well:
- First, sign up. This provides authentication to the service vendor.
- Create a repository—where you will keep your version of the notebook.
- You will need Docker installed on your machine to pull/push notebooks from/to your repository.
Installing Docker is operating system dependent. Go to the https://www.docker.com/ home page for instructions for your machine.
- Upload (push) your Jupyter image to your repository.
- Access your notebook in the repository. You can share the address (URL) of your notebook with others under control of Docker, making specific access rights to different users.
- From then on, it will work just as if it were running locally.