Common Bugs in Databutton-Generated Code

Databutton is optimized for rapid data app development where datasets are often small during development. Production data scale is rarely tested until the app is live

Databutton apps commonly have data processing functions that work for small datasets but fail silently on large ones — running out of memory, timing out, or producing incorrect aggregations. Python data processing code may load entire tables into memory. React data visualization components may try to render millions of data points without aggregation

Start by running your app through its complete user flow — sign up, use every feature, try edge cases like empty inputs and invalid data. Most Databutton bugs surface when you go off the happy path. Use your browser's developer tools to watch for console errors, failed network requests, and unhandled promise rejections. TypeScript's strict mode will catch many issues at compile time if it's not already enabled.

For async errors, wrap every server-side operation in try/catch blocks and return meaningful error messages. For state bugs, consider whether the state belongs in the URL, in a server component, or in client state — Databutton often defaults to client state when server state would be more appropriate. For data fetching issues, implement proper loading and error states for every data-dependent component.

The best way to prevent Databutton bugs from reaching production: enable TypeScript strict mode, add ESLint rules for common mistakes (no-floating-promises, exhaustive-deps), and write tests for critical user flows. Even basic smoke tests catch the majority of issues.