User GuideΒΆ

DataCabinet enables running computer laboratory for classrooms. It does it using Jupyter notebooks, conda environments and containers. It is powered by a distributed system running on AWS.

Our intent is to provide the building blocks and flexibility to be able to create complex programming assignments. They can have data, packages, backend components, autograding etc associated with them(more coming soon). The students or other uses of these assignments can easily open, work and submit assignments for review.

  • Jupyter notebooks with support for python or R on your web browser. Other kernels can be manually installed.
  • Isolated Conda environments with their own package dependencies as DataCabinet projects.
  • A dedicated disk and a shared disk to easily share projects and environments.
  • Integrated with NBGrader assignments with advanced capbilities DataCabinet and NBGrader
  • Using git projects with DataCabinet.
  • Common Problems

Common Tasks

DataCabinet and NBGrader