README
Using Visual Studio Code or simply bask
Pre-requisites:
- XQuartz Server on MacOS https://www.xquartz.org
- Docker
- Visual Code (optional)
Using existing image:
- open project /working directory
- start up xquarts
- Start docker (note IP is dynamic):
docker run -it -e DISPLAY=10.0.1.20:0 -p 8888:8888 -p 6006:6006 -v $(pwd)/notebooks:/notebooks --privileged --name tf5 amaksimov/python_data_science - SSH into docker container:
docker exec -it tf5 bash - enter:
apt-get update apt-get install -y python3-tk cd notebooks python3 house_price_prediction.py
Using docker-compose:
TODO
2. spin up docker engine: docker-compose up
3. in another terminal run: docker exec -it tf4 bash
apt-get update
apt-get install -y python3-tk
cd notebooks
export HOSTNAME=hostname
4. Start
brew install socat
socat TCP-LISTEN:6000,reuseaddr,fork UNIX-CLIENT:"$DISPLAY"
Links: https://dev-ops-notes.com/docker/howto-run-jupiter-keras-tensorflow-pandas-sklearn-and-matplotlib-docker-container/ https://dzone.com/articles/docker-x11-client-via-ssh jessfraz/dockerfiles#169