This course is based on Docker and Docker compose. As long as you have Docker you can run it on any operating system.
Docker should be exposed via TCP on 172.17.0.1:2375. If you have concerns in exposing docker, just use a temporary VM for the course (see below).
On Linux, set
# vim /etc/systemd/system/multi-user.target.wants/docker.service
[Service]
...
ExecStart=/usr/bin/dockerd -H fd:// -H tcp://172.17.0.1:2375
...
On Mac, check the FAQ and this issue
Consider having enough bandwidth for the first run to download the images.
Run the environemnt with:
# make course
And point the browser on the printed URL, eg.
# firefox http://localhost:8888
Once you have a digitalocean account, just
set your ssh key info in site-digitalocean.yml
then run the playbook:
$ export DO_API_TOKEN=xxxx
$ ansible-playbook -v site-digitalocean.yml
This will create one (or more) vms with the course installed.
Get the jupyter notebook url at the end of the deployment.
If you don't use ansible, you can always setup everything by hand.
- create an Ubuntu 18.04 docker droplet from the menu and ssh into your host
- expose docker on local http port
# vim /etc/systemd/system/multi-user.target.wants/docker.service
[Service]
...
ExecStart=/usr/bin/dockerd -H fd:// -H tcp://172.17.0.1:2375
...
- clone and run the project
# git clone https://github.com/ioggstream/python-course.git
# cd python-course/ansible-101
# make course
- point to the reference url
See asciicast here
