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The Edu POD will have all standard POD utilities and bioinformatics software installed. In addition, instructors wish to make use of both web-based application servers: JupyterHub server with Python3.4 and R Studio server, so those will be installed on all EDU Edu compute servers.
Instructors may also request that additional software be installed. Such requests should be made at least two weeks before the start of a class. However, since users cannot install Python packages in the JupyterHub server environment, requests to install of Python packages into the JupyterHub environment will generally be handled within one or two business days.Python 3.4 will be used for both the system Python3 installation and the (separate) Python3 installation for JupyterHub server for now, because that is the Python3 version available through the Ubuntu public repositories and using a more recent version would require major changes to the way Python packages are now deployed on top of our default BioLinux platform.
Note that the system and JupyterHub server Python3 installations are separate. All add-on JupyterHub server Python3 packages and many add-on system Python3 packages are installed explicitly, but there are a number of pre-installed system Python3 packages that come with BioLinux that we do not track individually. As a result, there may be a few differences between the available system and JupyterHub server Python3 packages. Instructors should be aware that such difference can exist, and request package installations where needed.
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- Home directory access is user-only so that students cannot see each others work
- No quota (or snapshots), Home directories do not have quotas so that larger data files can be stored here
- Work areas for each class ID and course (class/semester)
- Collaborative multi-user projects can be located here
- A single Scratch area for each class ID
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Direct Samba access to the class Work area is not available, but symbolic links in home directories can provide access.
Data retention
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