.. toctree::
:maxdepth: 1
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tutorial
test_files/index
otter_assign/index
otter_check/index
workflow/index
execution
plugins/index
pdfs
seeding
logging
api_reference
cli_reference
resources
Changelog <https://github.com/ucbds-infra/otter-grader/tree/master/CHANGELOG.md>
Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. It is designed to grade Python and R assignments for classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograding platforms of 3rd-party learning management systems (LMSs), non-containerized grading on an instructor's machine, and a client package that allows students to check and instructors to grade assignments their own machines. Otter is designed to grade Pyhon and R executables, Jupyter Notebooks, and RMarkdown documents and is compatible with a few different LMSs, including Canvas and Gradescope.
Otter is organized into six components based on the different stages of the assignment pipeline, each with a command-line interface:
- :ref:`Otter Assign <otter_assign>` is an assignment development and distribution tool that allows instructors to create assignments with prompts, solutions, and tests in a simple notebook format that it then converts into santized versions for distribution to students and autograders.
- :ref:`Otter Generate <workflow_otter_generate>` creates the necessary setup files so that instructors can autograde assignments.
- :ref:`Otter Check <otter_check>` allows students to run publically distributed tests written by instructors against their solutions as they work through assignments to verify their thought processes and implementations.
- :ref:`Otter Export <pdfs>` generates PDFs with optional filtering of Jupyter Notebooks for manually grading portions of assignments.
- :ref:`Otter Run <workflow_executing_submissions_otter_run>` grades students' assignments locally on the instructor's machine without containerization and supports grading on a JupyterHub account.
- :ref:`Otter Grade <workflow_executing_submissions_otter_grade>` grades students' assignments locally on the instructor's machine in parallel Docker containers, returning grade breakdowns as a CSV file.
Otter is a Python package that is compatible with Python 3.6+. The PDF export internals require either LaTeX and Pandoc or wkhtmltopdf to be installed. Docker is also required to grade assignments locally with containerization, and Postgres only if you're using Otter Service. Otter's Python package can be installed using pip. To install the current stable version, install with
pip install otter-graderIf you are going to be autograding R, you must also install the R package using
devtools::install_github:
devtools::install_github("ucbds-infra/ottr@stable")Installing the Python package will install the otter binary so that Otter can be called from the
command line. You can also call Otter as a Python module with python3 -m otter.
Otter uses Docker to create containers in which to run the students' submissions. Docker and our Docker image are only required if using Otter Grade. Please make sure that you install Docker and pull our Docker image, which is used to grade the notebooks. To get the Docker image, run
docker pull ucbdsinfra/otter-grader