Are you looking to work with raster and vector data in R? This guide will walk you through the key steps to contribute to lesson development, visualize changes using sandpaper, and understand how to deploy your work effectively. Let’s dive in!

Getting Started with Lesson Development

The first step in contributing is to locate the lesson files you wish to edit. All files are contained within the _episodes folder of the repository. Here’s a roadmap:

• Clone the repository to your local machine.
• Navigate to the _episodes folder to find the lesson files you want to edit.

Visualizing Your Changes Locally

To see the changes you are making to the lesson, you can use the sandpaper R package. This package allows you to visualize your modifications effectively. You have two commands at your disposal:

• sandpaper::serve() – This will start a local server to visualize your lesson live.
• sandpaper::build_lesson() – This command will build the lesson so that you can see how it appears in the final output.

After running either command, navigate to http://localhost:4321 to view your changes in real-time.

Deploying Your Changes

Once you are happy with your modifications, it’s time to push them to GitHub. Each time you push a change, GitHub Actions automatically rebuilds the lesson. Look for the green badge at the top of the README file to ensure the build has been successful. Upon a successful build, the results will be published at http://www.datacarpentry.org/r-raster-vector-geospatial.

**Important Note:** Be cautious with any manual commits to gh-pages as these will be overwritten during the automated build and deployment processes.

Meet the Lesson Maintainers

While interacting with this project, you might want to connect with the dedicated lesson maintainers for assistance:

• Jemma Stachelek
• Ivo Arrey
• Drake Asberry

Troubleshooting

If you encounter problems during the lesson development or deployment process, consider the following troubleshooting tips:

• Ensure that you have the latest version of the sandpaper package installed.
• Double-check your internet connection when pushing changes to GitHub.
• If experiencing build issues, revisit the lesson files for any discrepancies.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

In Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.