data-science-py

Docker configuration for Data Science with Python

First of all

• Read ALL README.md file
• Clone a project pipeline repository into the src/ directory
• Configure the .env file, see the example.env file and save copy with name .env
• There are two enviroment work flow:
  • Develop
  • Production

Flow Work to Develop Enviroment

• Build Docker Image Only Once

$ ./build.sh

• Run Docker Container

$ ./run.sh

• Run Docker Container (ONLY ON WINDOWS see PWD_WINDOWS in example.env file)

$ ./run.sh W

• Run Shell into Docker Container

$ ./shell.sh

Flow Work to Production Enviroment (FUTURE WORK)

• ...
• ...

Build Container

See example.env file

See build.sh script file

$ docker build $(for i in `cat .env | grep -v '#'`; do out+="--build-arg $i " ; done; echo $out;out="") -t sebaxtian/data-science-py:1.0.0 .

Run Container

See example.env file

See run.sh script file

$ docker run -it --name data-science-py --env-file $PWD/.env -v $PWD/src/$DIR_APP:/home/python/src -p $PORT_APP:$PORT_APP sebaxtian/data-science-py:1.0.0

Start Container

$ docker start data-science-py

See logs Container

$ docker logs data-science-py

Restart Container

$ docker restart data-science-py

Shell in Container

See shell.sh script file

$ docker exec -it data-science-py bash

Erase Container

$ docker rm data-science-py

Erase Container Image

$ docker image rm sebaxtian/data-science-py:1.0.0

Docker Commands

• List Docker images

$ docker image ls

• List Docker containers (running, all, all in quiet mode)

$ docker container ls
$ docker container ls --all
$ docker container ls -aq