Provides the latest release of nanshe and dependencies installed in a supported cluster environment with a working copy of the Jupyter Notebook.
This repo is part of an automated build, which is hosted on Docker Hub ( https://hub.docker.com/r/nanshe/nanshe_notebook ). Changes added to this trigger an automatic rebuild and deploy the resulting image to Docker Hub. To download an existing image, one simply needs to run docker pull nanshe/nanshe_notebook.
If one wishes to develop this repo, building will need to be performed manually. This container can be built simply by cding into the repo and using docker build -t <NAME> . where <NAME> is the name tagged to the image built. More information about building can be found in Docker's documentation ( https://docs.docker.com/reference/builder ). Please consider opening a pull request for changes that you make.
Only releases of nanshe are installed in this repo. nanshe is only released if it passes a build and is actively tested in this exact same environment. The container used by this container as a base, jakirkham/centos_drmaa_conda, is tested independently. That being said, the test suite is run for the installed release of nanshe during the build phase. If it fails, the build phase will be interrupted and the container will not be tagged or released on Docker Hub.
Once an image is acquired either from one of the provided builds or manually, the image is designed to provide a pre-configured Jupyter notebook environment. Simply run docker run -it -p 8888:8888 <NAME>. This will configure Grid Engine and a number of environment variables useful for maintaining it and starts up the Jupyter notebook. To open the notebook, go to your browser and type localhost:8888. If you are using docker-machine, get the IP address of the VM from docker-machine ip <MACHINE> where <MACHINE> is the machine running the container. If some other VM is in use with docker, one will need to figure out how to configure networking and port forwarding to access the notebook. At this point, nanshe can be imported and run in any way. In the case of an automated build, <NAME> is nanshe/nanshe_notebook.