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Description:

travo 1.0.0

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.