travo 1.0.0

Management tools for gitlab-based assignment workflows

Travo: Distributed GitLab ClassRoom

Travo is a lightweight open source Python toolkit that turns your favorite GitLab forge into a flexible management solution for computer assignments, à la GitHub classroom. It does so by automating steps in the assignment workflow through Git and GitLab's REST API.

Rationale: Teaching computer science or computational courses is all about collaboration on code. It is thus unsurprising that, with a pinch of salt, software forges like GitLab can provide helpful infrastructure to support and enhance that collaboration.

Features

• Easy to use for students: simple workflow with two automated operations: fetch and submit, available from the terminal or a widget-based dashboard in Jupyter.
• Flexible and battlefield tested on small to large courses (300+ students at lower undergraduate level) with optional support for multiple assignments, student groups, instructors, and sessions, as well as (basic) team work.
• Distributed and personal-data friendly: Travo can be used with any instance of GitLab, including a self-hosted one on premises by your institution. No other infrastructure is needed. Students and instructors can use any work environment (personal laptop, computer labs, JupyterHub, Docker images...) provided that Travo is installed.
• Command Line Interface (CLI) for most common usages.
• Graphical User Interface within Jupyter with student and instructor dashboards.
• Automatic and manual grading of Jupyter assignments through nbgrader integration.
• Empowering: Travo manages assignments according to standard Git and GitLab software development workflows, and opens the door for your students and instructors to discover at their pace version control, forges, collaborative development and devop practices.
• Lightweight, modular and extensible: you use whichever part of Travo is convenient for you and ignore, extend or replace the rest. For example, instructors can setup tailored CLI Python scripts for their courses, or bespoke automatic grading using Continuous Integration.
• Internationalized: French, English (in progress); more languages can be added.

Documentation

For more information check the Travo documentation and tutorials.

Screenshots

Fetching and submitting assignments from the terminal:

./course.py fetch Assignment1

./course.py submit Assignment1

The student dashboard for Jupyter users :

Overview of student submissions on GitLab :

Requirements and installation

Travo requires Python >= 3.8. It can be installed from pypi with:

pip install travo

To benefit from the Jupyter integration (dashboards), please use instead:

pip install 'travo[jupyter]'

The development version can be installed with:

pip install git+https://gitlab.com/travo-cr/travo.git

For more details check the installation instructions.

Authors

Pierre Thomas Froidevaux, Alexandre Blondin-Massé, Chiara Marmo, Jérémy Neveu, Jean Privat, Nicolas M. Thiéry, with contributions from Nicolas Grenier, Corentin Morice, Viviane Pons, Marco Pasi, and Brian Ravenet.

Contributing

Feedback, e.g. by posting issues, and contributions are most welcome!

Brief history and status

Travo started in Spring 2020 at UQAM as a shell script. See the Legacy User Interface. The user interface was completely refactored in Summer and Fall 2020. Travo was then reimplemented in Python in Winter 2021 and continuously expanded since. Travo is used in production in a dozen large classes at Université Paris-Saclay and UQAM, and many other smaller classes.

• Documentation: The tutorials could use some more love. On the other hand we would be very happy to help you get started as this is the most efficient approach to explore new use cases and improve the documentation. Get in touch!
• Better messages: less verbosity by default; provide tips on what to do next.
• Internationalization: Basic support for internationalization has been set up, and many, but not all, messages are available both in French and English. The next steps are to scan the Travo library to use internationalization in all messages, and to translate the messages. Contributions welcome!
• Support for collaborative work: in progress, with experimental support for modeling teams of students working collaboratively on an assignment, with basic tooling for students. Tooling for instructors remains to be implemented.
• Forge agnosticism: Currently, only GitLab is supported, but the code was designed to be modular to make it easy to support other forges (e.g. GitHub).
• Automatic grading: Support for a wider range of use cases beyond Jupyter assignments; tighter integration with nbgrader for Jupyter assignments.