Jupyter notebooks are handy for data science and other use cases that rely on iterative programming. If you’re already comfortable running Docker, here’s an easy one-liner to get up and running.
docker run --rm -p 10000:8888 -v ${PWD}:/home/jovyan/work jupyter/datascience-notebook:2023-03-09
The first port number (10000) can be changed to expose the notebook to a different port. The volume (-v) flag can be changed from the present directory (${PWD}) to a directory containing data you’d like to work with. To connect to the notebook, you’ll need to get the connection string from the output. It’ll look like this:
[I 2023-03-13 17:23:37.887 ServerApp] Jupyter Server 2.4.0 is running at:
[I 2023-03-13 17:23:37.887 ServerApp] http://bc7b3ff32303:8888/lab?token=6fd0237c4df26bc1e1af4a7c386c28c8573498850701f200
[I 2023-03-13 17:23:37.887 ServerApp] http://127.0.0.1:8888/lab?token=6fd0237c4df26bc1e1af4a7c386c28c8573498850701f200
If you’re doing this from a Chromebook, you’ll have to get the real IP address from the output of ip addr show dev eth0. The port number is actually 10000 or whatever port you exposed. So the URL to paste in your browser will be something like this:
http://100.115.92.199:10000/lab?token=6fd0237c4df26bc1e1af4a7c386c28c8573498850701f200
Easy peasy!
Echoic Dev 