I have Python scripts that request coastal buoy data from the National Data Buoy Center every hour and append the results to a pandas DataFrame. I currently use this information at home to assess sea conditions, but I would like to access it online from anywhere.
I'm comfortable with Python and data processing, including converting the results into formats a website can use. My main uncertainty is how to build a simple site from scratch, connect it to my existing data pipeline, and point the domain I already own to the hosting service. What would be a practical beginner-friendly setup and workflow for this?
3 Answers
You generally don’t move the domain itself to the hosting provider. After deploying the site, you update the domain’s DNS records at the registrar so they point to the host. Services such as Vercel or Cloudflare can simplify deployment and DNS configuration, though a Python backend may need a hosting platform that supports long-running services or scheduled jobs.
Since you already know Python, a small Flask or FastAPI backend with a basic HTML and JavaScript frontend would be a straightforward approach. Your scheduled script can keep updating the data, while the backend reads the latest results and returns them as JSON for the page to display in a table or chart.
The most important design question is how the data is obtained. If the site can request the source directly through an API, the frontend may only need a simple page. If your process requires downloading files, cleaning them, and storing historical results, you’ll probably want a backend or scheduled job that handles those tasks before the website reads the processed data.
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