(Setup instructions for the sourmash tutorial)
boot an ubuntu/images-testing/hvm-ssd/ubuntu-yakkety-daily-amd64-server-20170201 (ami-008dd060) image, with a ~50 GB local disk and with open ports 8000-9000.
Then, update software:
sudo apt-get -y update
and install docker:
wget -qO- https://get.docker.com/ | sudo sh
Also yourself to the docker group:
sudo usermod -aG docker ubuntu
and now log out and log back in.
Next, create a dockerfile that builds on jupyter/datascience-notebook to install the stuff that I want in my custom environment:
cd ~/
mkdir sourmash-nb
cd sourmash-nb
cat > Dockerfile <<EOF
FROM jupyter/datascience-notebook
RUN pip install -U https://github.com/dib-lab/sourmash/archive/master.zip
EOF
and run docker build:
docker build -t sourmash-nb .
While that's running, you can also download the sourmash database:
mkdir ~/sourmash-db
cd ~/sourmash-db
curl -O https://s3-us-west-1.amazonaws.com/spacegraphcats.ucdavis.edu/microbe-genbank-sbt-k31-2017.05.09.tar.gz
tar xzf microbe-genbank-sbt-k31-2017.05.09.tar.gz
Now run the notebook on port 8000, linking the large database into the container file system space as /data/genbank (and making it read-only) --
EXT=8000
docker run -d -v ~/sourmash-db:/data/genbank:ro -p ${EXT}:8888 sourmash-nb start-notebook.sh \
--NotebookApp.password='sha1:5d813e5d59a7:b4e430cf6dbd1aad04838c6e9cf684f4d76e245c'
Voila, you should now be able to connect to port 8000!
To run more than one, use a for loop:
for EXT in 8000 8001 8002
do
docker run ...
done
See the jupyter/datascience-notebook docs for more info on command line arguments to the container.
To kill the docker container, locate its ID and use docker kill <id>. (The ID is output by docker run when -d is used.) If you're running only one container, you can also replace -d with -it and it will run in interactive mode where you can use CTRL-C to quit out of it.