Course data

See also

One of the best features of jupyter.cs is powerful data access. See Accessing JupyterHub (jupyter.cs) data

If your course uses data, request a coursedata or shareddata directory as mentioned above. You need to add the data there yourself, either through the Jupyter interface or SMB mounting of data.

If you use coursedata, just start the course environment and instructors should have permissions to put files in there. Please try to keep things organized!

If you use shareddata, ask for permission to put data there - we need to make the directory for you. When asking, tell us the (computer readable short)name of the dataset. In the shareddata directory, you find a README file with some more instructions. All datasets should have a minimum README (copy the template) which makes it minimally usable for others.

In both cases, you need to chmod -R a+rX the data directory whenever new files or directories are added so that the data becomes readable to students.

Note: after you are added to relevant group to access the data, it make take up to 12 hours for your account information to be updated so that it can be accessed via remote mounting.

Don’t include large amount of data in the assignment directories - there will be at least four, if not more, copies of data made for every student.

Data from other courses

Sometimes, when you are in course A’s environment, you want to access the data from course B. For example, A is the next year’s edition of the course B, and it could be useful to check the old files.

You can access the files for every course which you are an instructor of at the path /m/jhnas/jupyter/course/. The files/ sub-directory is the entire course directory for that course, the same as /course/ in each course image. You can also access the course data directory at data/ there.

All old courses (for which you are listed as an instructor) are available, but if the course is in the “achived” state, you can’t modify the files.