Streamlit is the go-to dashboarding solution for showcasing ML models or visualizing data. It has a vibrant community, multiple years of development under its belt, and tons of third-party integrations. On the other hand, everyone that tried to create complex interactions, like drill-downs or logins, knows that control flow can get messy really quick. Initially simple dashboards often evolve into something bigger and the simple-but-powerful Streamlit formula may not always be up to the tasks.

FastHTML is a new contender in the arena of Python web frameworks and, according to its docs, "it excels at building dashboards." FastHTML stands on the shoulders of giants, giving you a smooth Python experience for authoring web pages, while allowing access to the foundations of the web, like CSS and JS, at any time. We will see if FastHTML can put code where its mouth is, by building the same dashboard, step by step, in both frameworks and investigate their strengths and weaknesses.

This is a talk for data enthusiasts that dabble in web technologies for the sake of showcasing their work or building internal tooling. Do not expect a course on building customer-facing web apps. We will build a dashboard that features:

• an interactive Plotly chart
• a drill-down with detailed information shown in a second plot
• a login
• multiple pages and navigation

We will examine how hard or easy it is to implement each of these features and how interacting with them in the browser feels. At the end we will see if the reigning champion can defend their crown or if the ambitious contender takes the win.