Making your life easier as an open source maintainer, from documenting processes to leveraging your community.

This short course is teaching tools and practices for producing and sharing quality, sustainable and FAIR (Findable, Accessible, Interoperable and Reusable) research software to support open and reproducible research. The course can be delivered over 2 full or 4 half days.

This lesson covers the implementation of CI/CD pipelines in research software projects, focusing on automating tests, builds, and deployments using GitLab CI.

This lesson covers how to set up continuous integration and continuous delivery pipelines for automated testing and deployment in software projects.

This lesson teaches best practices for conducting and participating in code reviews, emphasizing clear communication and collaborative problem solving.

Launching a successful open source project involves more than just code. Start your journey here.

This lesson covers intermediate Python development skills such as writing reusable code, using virtual environments, testing with pytest, and managing dependencies.

This course aims to teach a core set of established, intermediate-level software development skills and best practices for working as part of a team in a research environment using Python as an example programming language (see detailed learning objectives below).

This lesson covers the fundamentals of Docker, including creating containers, managing Docker images, and using Docker for software reproducibility and deployment.

Tracking the success of your project helps you make informed decisions and communicate impact effectively.

This lesson covers modular programming in Python, explaining how to write reusable code in modules, organize codebases, and test them to improve collaboration and maintainability.

This lesson covers best practices for building Python packages, focusing on scientific software. It explains how to structure packages, write tests, manage dependencies, and distribute packages via PyPI.

This lesson teaches the essential steps for packaging Python projects and publishing them on PyPI.

This lesson teaches how to create and publish packages in Python. We assume a basic understanding of Python, and assume learners are comfortable using simple commands in a Bash shell.

This workshop will provide you with the basics for writing your own packages in R.

This session aims to introduce the use of Docker containers with the goal of using them to effect reproducible computational environments. Such environments are useful for ensuring reproducible research outputs, for example.

This lesson covers the principles of reproducible research, including data management, version control, and the use of tools like Git to ensure that research can be replicated.

This course provides an overview of key skills for Research Software Engineers, including software design, version control with Git, testing with pytest, and project management.

Launching a successful open source project involves more than just code. Start your journey here.

This lesson covers how to write tests for your code, understand test-driven development, and use testing frameworks like pytest in Python.

This lesson covers how to write and run unit tests in Python, including an introduction to test-driven development (TDD) and its benefits.