Launches "temporary" IPython notebook servers.
- Reasonably fast IOPS (SSDs, PCIe cards)
- Enough CPUs and memory for all the users (
mem_limit*pool_size< Available RAM)
Get Docker, then:
docker pull jupyter/demo
export TOKEN=$( head -c 30 /dev/urandom | xxd -p )
docker run --net=host -d -e CONFIGPROXY_AUTH_TOKEN=$TOKEN jupyter/configurable-http-proxy --default-target http://127.0.0.1:9999
docker run --net=host -d -e CONFIGPROXY_AUTH_TOKEN=$TOKEN -v /var/run/docker.sock:/docker.sock jupyter/tmpnb
BAM! Visit your host on port 8000 and you have a working tmpnb setup.
If you need to set the docker-version or other options, they can be passed to jupyter/tmpnb directly:
docker run --net=host -d -e CONFIGPROXY_AUTH_TOKEN=$TOKEN -v /var/run/docker.sock:/docker.sock jupyter/tmpnb python orchestrate.py --cull-timeout=60 --docker-version="1.13"
If doing direct installation, you'll need to install it within /srv/tmpnb on Ubuntu 14.04.
mkdir -p /srv/
cd /srv/
git clone https://github.com/jupyter/tmpnb.git
cd tmpnb
script/bootstrap
The running user needs permission on the Docker socket.
git clone https://github.com/jupyter/tmpnb.git
cd tmpnb
# If modifying the Docker image in any way
docker build -t jupyter/demo images/demo
pip install -r requirements.txt
npm install jupyter/configurable-http-proxy
# Kick off the proxy and run the server.
# Runs on all interfaces on port 8000 by default.
script/dev