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Smarter Scientific Software Development with GitHub Actions

Candace Savonen, MS and Carrie Wright, PhD

The course is intended for individuals in the biomedical sciences who wish to make their work more reproducible through the use of automation. It focuses on the basics of continuous integration continuous deployment techniques using the GitHub Actions software.

This course is written for individuals who:

- Are comfortable with GitHub and know how to make a pull request

- Wish to save time and enhance their scientific projects using automation

- Have perhaps tried to learn about GitHub Actions before but felt overwhelmed about how to start

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What's inside

Syllabus

Welcome to the Course

This first module introduces you to the course as well as describes the motivation for why automation should be an essential tool for every scientist who writes code.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Focuses on continuous integration and continuous deployment, which are essential for reproducible research in biomedical science

Assumes familiarity with GitHub and pull requests, which is common among researchers collaborating on scientific projects

Taught by Fred Hutchinson Cancer Center, a research institute known for its work in cancer research and biomedical science

Teaches how to use GitHub Actions, which can save time and enhance scientific projects through automation

Provides tips for troubleshooting GitHub Actions, which can be challenging for beginners in scientific software development

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Reviews summary

Github actions for scientific reproducibility

learners say this course is highly targeted towards individuals in the biomedical sciences looking to improve reproducibility and save time through automation using GitHub Actions. It provides a practical introduction focusing on the basics, including hands-on activities, and is designed for those already comfortable with GitHub and pull requests. The course aims to help learners get started with GitHub Actions, particularly if they have felt overwhelmed by the topic before. Based on the curriculum, it appears to offer helpful demonstrations and troubleshooting tips for applying these tools to scientific projects. This niche focus makes it highly relevant for its intended audience.

Provides a solid starting point for beginners.

"It's a good introduction to get started, but doesn't go very deep."

"This course is a solid starting point for beginners with GitHub Actions."

"If you're already advanced, you might not find much new here."

Assumes prior experience with GitHub and pull requests.

"You really need to know GitHub basics coming into this course."

"Make sure you're comfortable with creating pull requests beforehand."

"This isn't a course for total GitHub novices; prerequisites are key."

Includes practical exercises and activities.

"The hands-on labs were very useful for learning by doing."

"I appreciated the practical exercises to reinforce concepts."

"Working through the activities helped solidify my understanding."

Specifically tailored for scientific workflows.

"This course is perfect for automating my research scripts."

"I needed something specifically for scientific coding reproducibility."

"It directly addresses the challenges in my field as a scientist."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Smarter Scientific Software Development with GitHub Actions with these activities:

Review Git Fundamentals

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Strengthen your understanding of Git, especially branching and pull requests, as these are essential for using GitHub Actions effectively.

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Complete an online Git tutorial.
Practice branching and merging in a local repository.
Familiarize yourself with common Git commands.

Read 'The GitHub Book'

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Learn the fundamentals of Git and GitHub to better understand how GitHub Actions integrates with your workflow.

View Pro Git on Amazon

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Read the chapters on branching and merging.
Practice the concepts in a personal repository.

Follow GitHub Actions Tutorials

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Work through online tutorials that demonstrate how to set up and configure GitHub Actions for common scientific workflows.

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Find tutorials on automating testing and deployment.
Adapt the tutorials to your own projects.
Document the steps you took.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Automate a Small Project

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Apply your knowledge by automating a small, existing scientific project using GitHub Actions for continuous integration.

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Choose a project with existing code and tests.
Set up a GitHub Actions workflow to run tests on each commit.
Configure notifications for build failures.
Extend the workflow to automate deployment.

Document Your Workflow

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Create a blog post or documentation page detailing your experience setting up GitHub Actions for a scientific project.

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Describe the project and its goals.
Explain the GitHub Actions workflow you created.
Share any challenges you faced and how you overcame them.
Publish your documentation online.

Contribute to a GitHub Actions Workflow

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Contribute to an open-source project by improving or adding to their existing GitHub Actions workflows.

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Find an open-source project using GitHub Actions.
Identify areas where the workflow can be improved.
Submit a pull request with your changes.
Respond to feedback from the project maintainers.

Read 'Effective DevOps'

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Understand the broader context of DevOps and how GitHub Actions fits into a larger automation strategy.

View Effective DevOps on Amazon

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Read the chapters on culture and collaboration.
Reflect on how these principles apply to your research team.

Career center

Learners who complete Smarter Scientific Software Development with GitHub Actions will develop knowledge and skills that may be useful to these careers:

Computational Biologist

As a computational biologist, often requiring an advanced degree, you develop and apply computational methods to solve biological problems. The automation skills covered in this course directly support the need for efficient and reproducible research in computational biology. Learning about GitHub Actions helps you in building and maintaining complex computational pipelines. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Computational Biologist

Bioinformatics Analyst

As a bioinformatics analyst, you analyze biological data using computational tools and techniques. The automation skills taught in this course helps you streamline data analysis workflows and ensure reproducibility. Learning about continuous integration and continuous deployment can optimize your bioinformatics processes. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Bioinformatics Analyst

Scientific Programmer

As a scientific programmer, you develop software tools and applications for scientific research. The focus on automation and continuous integration in this course is highly relevant to your role. Learning about GitHub Actions can enhance your ability to manage and deploy scientific software. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Scientific Programmer

Bioinformatics Scientist

As a bioinformatics scientist, you develop and apply computational methods to analyze biological data. You use programming to solve problems in genetics, genomics, and proteomics. The emphasis on automation in this course is very helpful. Learning to use GitHub Actions will allow for more reproducible research and collaboration. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Bioinformatics Scientist

Genomic Data Scientist

As a genomic data scientist, often requiring an advanced degree, you analyze large-scale genomic data to identify patterns and insights related to health and disease. The use of automation tools, as taught in this course, helps you streamline complex data processing pipelines and ensure reproducibility. Learning GitHub Actions can improve your ability to manage and share genomic data. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Genomic Data Scientist

Automation Engineer

As an automation engineer, you design, develop, and implement automated systems. This course, with its focus on continuous integration and continuous deployment using GitHub Actions, provides a solid foundation for the role. The hands-on activities in the course will be particularly valuable. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Automation Engineer

Research Scientist

As a research scientist, you design and conduct experiments, analyze data, and write reports. In this role, you contribute to the advancement of knowledge in your field. A course like this one helps you automate tasks, track experiments and data, and share your findings with collaborators. Learning continuous integration and continuous deployment helps you efficiently manage and share code. Using GitHub Actions, as taught in this course, helps scientists who write code to better organize their experimentation.

See salaries and explore the career path for Research Scientist

Biostatistician

As a biostatistician, often requiring an advanced degree, you apply statistical methods to biological and health-related data. This course is helpful because it shows how to automate complex analyses and ensure that they are reproducible. The GitHub Actions knowledge from this course may be particularly useful in validating statistical models. The course aims to help scientists who write code to better organize their projects. The troubleshooting tips in the course may come in handy in this role.

See salaries and explore the career path for Biostatistician

Software Engineer

As a software engineer, you design, develop, and test software applications. The focus on automation and reproducibility in this course directly aligns with the principles of software engineering. Learning about continuous integration and continuous deployment helps you streamline development processes and ensure code quality. In particular this course emphasizes GitHub Actions, which is a useful tool for collaboration. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Software Engineer

Research Engineer

As a research engineer, you will work on combining scientific research with engineering principles to develop new technologies or products. The automation skills that this course teaches may allow you to streamline the development process, as well as ensure that data and results are reproducible. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Research Engineer

Data Scientist

As a data scientist, you will be responsible for analyzing large datasets to extract meaningful insights and develop data driven solutions. The use of automation that this course teaches may be useful for managing and deploying complex data pipelines. Furthermore, learning about continuous integration and deployment helps you ensure the reliability, validity, and reproducibility of your data science workflows. You can apply the troubleshooting tips from the final module of this course as you build your solutions. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

As a machine learning engineer, you develop and deploy machine learning models. The use of automation that this course teaches may be useful for managing and deploying complex machine learning pipelines. Learning continuous integration and continuous deployment helps you ensure the reliability, validity, and reproducibility of your models. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

As a data analyst, you collect, process, and analyze data to identify trends and insights. The automation skills taught in this course helps you streamline data analysis workflows and ensure accuracy. Learning how to use GitHub Actions enables you to collaborate effectively with other analysts. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Data Analyst

Laboratory Manager

As a laboratory manager, you oversee the operations of a research laboratory. The automation techniques taught in this course can be applied to manage workflows and ensure data integrity. Learning about continuous integration and continuous deployment helps you track experiments and results effectively. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Laboratory Manager

Science Educator

As a science educator, you teach scientific concepts and principles to students. The course can help you share coding skills. Learning about continuous integration and continuous deployment helps you present up-to-date methods. This course may be especially helpful to those in biomedical science who wish to make their work more reproducible. The course aims to help scientists who write code to better organize their projects.

See salaries and explore the career path for Science Educator

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Smarter Scientific Software Development with GitHub Actions.

Pro Git

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Provides a comprehensive guide to using GitHub for version control and collaboration. It covers topics such as branching, merging, and pull requests, which are essential for understanding and utilizing GitHub Actions. While not directly about GitHub Actions, it provides the necessary foundation for effectively using the platform. It useful reference for those new to Git and GitHub.

Effective DevOps

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Provides a broader context for understanding DevOps principles and practices, which are closely related to continuous integration and continuous deployment. It helps you understand the cultural and organizational aspects of automation, which can be valuable when implementing GitHub Actions in a scientific research environment. This book is more valuable as additional reading than as a current reference. It provides a good overview of the DevOps landscape.

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