I have Python scripts that request ocean and wave measurements from coastal buoys through the National Data Buoy Center every hour. The scripts process the readings with pandas and append them to a dataset, which I currently use at home to assess sea conditions. I would like to build a simple webpage that displays this information so I can access it from anywhere.
I am comfortable with Python, data processing, and converting the data into formats a website can use, but I am unsure how to build the site from scratch and connect the domain name I already own to a hosting provider. What would be a straightforward setup for the backend, frontend, data updates, hosting, and domain configuration?
3 Answers
Since you already know Python, a small Flask or FastAPI backend with a simple HTML, CSS, and JavaScript frontend should be enough. Have your scheduled script fetch and process the buoy data, save it in JSON or a database, and let the webpage request that data from an API endpoint for display in tables or charts.
For deployment, you can host the frontend and backend with a provider such as Vercel, Cloudflare, or another service that supports your chosen Python setup. Your hourly data job could run on a scheduled task, server, or workflow service. Store the processed output somewhere the site can safely read rather than relying on a local pandas DataFrame that disappears when the process stops.
You generally do not move the domain registration itself to the hosting provider. After deploying the site, update the domain's DNS records at your registrar—usually an A record or CNAME—to point to the host. The hosting provider will give you the exact records and often handles HTTPS automatically.
The key design choice is where the data comes from. If the browser can request it directly through an accessible API, the site can stay very simple. If the source requires downloading files, authentication, or regular processing, keep that work on the backend instead.