RoboTA Core is a Python module that supports analysis of a range of artefacts usually stored in a hosted Git-based software project. It provides a common single data model for commit data, issue data, merge/pull requests, CI results, wiki pages, etc., independent of the underlying hosting system. It is designed to be provider agnostic; for example, artefacts can come from GitLab or GitHub hosted projects, or a locally hosted Git project. CI data is currently only accessible from Jenkins.
Its aim is to facilitate inter- and intra-project analysis of software engineering practices and outcomes. The module originated in the RoboTA project undertaken at the University of Manchester, to provide a framework for the automated assessment of software engineering coursework though it has a wider scope in the assessment of general good practice in software engineering. RoboTA (pronounced a bit like "Roberta") is short for Robot Teaching Assistant. The RoboTA suite of tools includes robota-marking (which assigns marks to projects based on a configurable marking scheme, expressed in YAML), robota-progress (which provides a simple progress dashboard for team-based student projects) and robota-common-errors (which reports on instances of common errors found in student code bases and projects).
RoboTA Core is a foundational component of all these tools, provided the base data about the project for the higher level analysis tools to use.
RoboTA was developed in the Computer Science department at the University of Manchester. From 2018 to March 2021, development of RoboTA was funded by the Institute of Coding.
To install as a Python module, type
python -m pip install robota-core
from the root directory. For developers, you should install in linked .egg mode using
python -m pip install robota-core -e
If you are using a Python virtual environment, you should activate this first before using the above commands.
This project uses Poetry for dependency management. If you're contributing to the project, you'll need to install Poetry first using one of the following commands:
-
Using pipx (recommended):
pipx install poetry -
Using pip:
pip install poetry
Note
If you're using pipx, make sure to install it first and add it to your PATH. You can find instructions on how to do this in the pipx documentation.
Installing Dependencies
Once you have Poetry installed, you can install the project dependencies by running the following command in the root directory of the project:
poetry install
This command will create a virtual environment (if one doesn't already exist) and install all the dependencies specified in the pyproject.toml file.
Building the Package
To build the package, use the following command:
poetry build
This will generate the build artifacts in the dist/ directory, which can then be published to PyPI or used locally.
Publishing the Package
To publish the package to PyPI, you can use:
poetry publish
Make sure you have the appropriate credentials set up in your environment for PyPI.
RoboTA Core requires access to a number of data sources to collect data to operate on. Details of these data sources and information required to connect to them is provided in the robota config yaml file. Documentation on the config file can be found in the data_sources section of the documentation. RoboTA config template files are provided with the robota-common-errors, robota-progress and robota-marking packages.