Filter Query with a Text Input

Introduction

A text-input filter is one of the quickest ways to make data feel live, but it also changes how users interpret the list beneath it. In Wappler, the job is not just connecting an input to a filter. The job is making the search responsive, honest about what is being searched, and easy to combine with sorting or paging without confusing the user.

Immediate feedback

Text-driven filtering works best when users see the list respond quickly and predictably.

Scope matters

Users should understand whether they are filtering a visible client-side list or a broader URL/server-driven result set.

Filter from a clearly named input.

Let users see the result set change as they type or submit.

Explain what part of the list the search applies to.

Combine search with sorting and paging in a predictable order.

Make text filters feel trustworthy

Search feels broken fastest when the page hides its filtering rules.

Be clear about what matches

Users should be able to infer whether the filter is broad text matching, a specific field match, or a narrowed subset of the original data. Ambiguity makes search feel random.

Expectation management

Name the field or pattern when the filter is more specific than a general search.

Handle empty results gracefully

When the filter removes every row, the page should explain that no results matched instead of looking blank or broken.

Related pattern

Pair text filtering with a clear no-results state.

Make refinement and reset easy

A user who typed a narrow filter should be able to broaden or clear it without friction. Search is an exploratory action, not a one-shot command.

Low-friction flow

Clearing or changing the filter should feel like a normal part of using the list.

Next steps

Once a text input can filter the view cleanly, the next step is combining it with URL state, checkbox filters, and no-results messaging.