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WildflowerJS Reactive JS, No BS*

A no-build reactive JavaScript framework, rooted in the web platform.
No build step. No dependencies. No lock-in.

<script src="wildflower.min.js"></script> ...and start building.

Back to Basics

The code you write is 100% web standard code. HTML stays HTML. JavaScript stays JavaScript. CSS stays CSS. No JSX, no templating language, no custom syntax to learn. If you know the web platform, you already know how to use this.

WildflowerJS extends the web platform. It doesn't replace it.

Your Development Simplified

Because you develop with 100% web standards, every tool in your existing chain already understands the code: IDE, browser DevTools, linter, formatter, screen reader, SEO crawler. Nothing to install, no custom file types, no sourcemaps. Save the file, refresh, and your change is live.

Just be a web developer.

Batteries Included: One Mental Model

Router, SSR, stores, computed properties, two-way binding, event modifiers, data pools, and TypeScript types, all built in, all speaking the same language. Learn data-bind once and you know binding everywhere: lists, pools, stores, forms. There's no five-library stack to keep in sync.

One script tag. Everything you need.

<div data-component="counter">
  <span data-bind="count"></span>
  <button data-action="increment">
    +1
  </button>
</div>

<script>
wildflower.component('counter', {
  state: { count: 0 },
  increment() { this.count++ }
})
</script>

How It Works

data-bind connects state to the DOM.

data-action connects events to methods.

this.count++ triggers a precise DOM update.

Mutate state. The DOM updates.

Two Reactivity Modes

data-list for automatic reactivity: mutate state, DOM updates. data-pool for explicit control: plain objects, zero proxy overhead, you say what changed.

Same template syntax. Different performance profile. From interactive forms to per-frame particle systems. You choose the right tradeoff for the job.

Try it. Right-click, inspect this demo. Every dot is a real DOM element.

See full demo →

Get Started View Demos
* Build Step

Zero Toolchain

Modern frameworks ask you to install a compiler, a bundler, a package manager, hundreds of fragile transitive dependencies, and a framework-specific file format, before you write a single line of your application.

WildflowerJS was built starting from a single principle: no build step, no tooling. Ever.

WildflowerJS asks you to add a script tag.

There's no CLI scaffolding step, no config files, no .vue/.jsx/.svelte source format. You don't debug through sourcemaps or wait on a build pipeline. Your project has zero dependencies.

Performance isn't a tradeoff. Build steps optimize bundle delivery, not the runtime work that follows it. WildflowerJS writes directly to the DOM, with no virtual DOM or reconciliation pass between state change and update, so it doesn't need a build step to be fast.

The framework is full-featured without the toolchain: router, SSR, stores, computed properties, transitions, pools. You don't need a toolchain to use any of it.

my-app/
  index.html
  app.js
  style.css
  wildflower.min.js

That's the entire project. No package.json.
No node_modules. No config files. Ship it.

Zero Install. Zero Attack Surface.

Every dependency you install is trust extended to a maintainer you've never met, running scripts on your dev machine and in your CI. A typical React + Vite + UI‑lib setup pulls in 300+ transitive packages before you write a feature.

Each one is a potential intrusion vector. NPM worms, OAuth chains compromising deploy platforms, postinstall hijacking: the supply chain is now where production code gets compromised, not the deploy. And signing isn't a backstop: Mini Shai‑Hulud (May 2026) compromised 170+ packages whose malicious versions carried valid SLSA Build Level 3 provenance, because the attestation came from build infrastructure the worm had already taken over.

WildflowerJS users don't have this attack surface, by construction. There is no npm install, no postinstall script, no transitive package graph. The framework is one file you copy or pin by hash.

As of v1.1, the same holds for building the framework itself. WildflowerJS bundles with a vendored rollup and terser pipeline pulled as three SHA‑512‑pinned tarballs: no npm install, no transitive packages, no postinstall scripts in the build path. The entire toolchain is three files you verify by hash.

Zero dependencies is the absence of a problem the rest of the industry has not properly addressed.

A typical React/Vue project:

  npm install
  ├── hundreds of packages
  ├── from hundreds of maintainers
  ├── postinstall scripts run on install
  └── tens to hundreds of MB of transitive code

WildflowerJS:

  <script src="wildflower.min.js"></script>
  └── 1 file.
      No transitive dependencies.

Zero Lock-in

WildflowerJS works with the DOM, not instead of it. There's no virtual DOM intercepting your code and no compiler rewriting your markup. The render cycle is yours.

That means Leaflet, DataTables, Chart.js, D3, Three.js, any library that touches the DOM, just works. No wrapper packages or framework-specific escape hatches required. Drop in a script tag and use it.

Because your code is standard HTML and JavaScript, you're never locked in. Your skills transfer and your code is more portable. If you outgrow the framework, your knowledge doesn't expire.

This also means your "ecosystem" is all of the world of vanilla JS. Without compromises or hacks.

<!-- Use any library directly -->
<div data-component="map-view">
  <div id="map" style="height: 400px"></div>
</div>
wildflower.component('map-view', {
  state: { lat: 51.505, lng: -0.09 },
  init() {
    // Leaflet works as-is. No wrappers.
    this._map = L.map('map')
      .setView([this.lat, this.lng], 13);
    L.tileLayer('https://{s}.tile.osm.org'
      + '/{z}/{x}/{y}.png').addTo(this._map);
  }
})

Precise Reactivity

When you write this.count++, WildflowerJS updates the single DOM node bound to count. Nothing else is touched. There's no tree diffing or reconciliation pass to figure that out.

This isn't a tradeoff. You get fine-grained updates and a simple mental model. Change a property, the bound element updates. That's the entire reactivity model.

Other frameworks ask you to learn signals, accessors, memos, effects, and subscription lifecycles to achieve what WildflowerJS does with a property assignment.

wildflower.component('dashboard', {
  state: {
    users: 1420,
    status: 'healthy'
  },
  computed: {
    summary() {
      return this.users + ' users, ' + this.status;
    }
  },
  refresh() {
    this.users = 1421;
    // Only the elements bound to 'users'
    // and 'summary' update. Everything
    // else on the page is untouched.
  }
})

One Reactivity Model. Everywhere.

Components, Stores, and Plugins all share the same reactive foundation. State, computed properties, and methods work identically no matter where they live. Learn it once, it works the same way in a UI component, a global store, or a framework plugin.

Other frameworks make you learn a different system for each layer. React components use hooks, but stores need Redux or Zustand, which are completely different APIs. Vue components use reactive data, but Pinia stores have their own patterns. Every layer is a new mental model.

In WildflowerJS, there's one model. A store is a component without a template. A plugin is an entity that extends the framework itself, adding directives, lifecycle hooks, and services. The same this.count++ triggers the same reactivity everywhere.

This unlocks patterns other frameworks can't express. A store can run headless physics simulations with tick(), feeding data into a component that renders it through a pool, all using the same reactive primitives, no glue code required.

// Component: reactive UI
wildflower.component('cart', {
  state: { items: [] },
  computed: {
    total() { return this.items.length; }
  }
})

// Store: global shared state
wildflower.store('user', {
  state: { name: '', role: 'guest' },
  computed: {
    isAdmin() { return this.role === 'admin'; }
  }
})

// Plugin: extends the framework
wildflower.plugin({
  name: 'notifications',
  state: { items: [], unreadCount: 0 },
  computed: {
    hasUnread() { return this.unreadCount > 0; }
  },
  add(msg) { this.items.push(msg); this.unreadCount++; }
})
// Access globally: wildflower.$notifications.add(...)

// Same state. Same computed. Same methods.

Data Pools

Every framework wraps collection items in reactive proxies, whether the item needs it or not. WildflowerJS gives you a choice: data-list for push reactivity (automatic), data-pool for pull reactivity (explicit control, zero proxy overhead).

Pools render plain objects with the same template syntax as lists. Mutate the object, call markDirty(), and only that item updates. Full CRUD, selection, bulk operations, all faster than the push-reactive path.

And because pools use pull-based rendering, they scale to simulations, games, particle systems, and data visualizations at native frame rate. Use cases that would choke a virtual DOM. No other framework has anything like this.

<div data-component="user-table">
  <tbody data-pool="users" data-key="id">
    <template>
      <tr>
        <td data-bind="name"></td>
        <td data-bind="status"
            data-bind-class="status === 'active'
              ? 'badge success'
              : 'badge inactive'"></td>
      </tr>
    </template>
  </tbody>
</div>
wildflower.component('user-table', {
  pools: { users: {} },

  init() {
    // Populate: plain objects, no proxies
    data.forEach(u => this.pools.users.add(u));
  },

  // Optional: add tick() and the same pool
  // renders every frame. Same template, same
  // data, different rendering frequency.
  // That's the only difference between a
  // display table and a particle system.
})

Built for AI-Assisted Development

Because WildflowerJS is standard HTML and JavaScript, AI code assistants already know how to write it. There's no custom syntax to hallucinate or compiler quirks to work around. The code an AI generates runs exactly as written, with no build step between generation and execution.

We go further. WildflowerJS ships an AI-optimized reference page with patterns, anti-patterns, and examples designed for code generation context windows. Our llms.txt file follows the llms.txt convention for machine-readable documentation.

And for structured app generation, our Universal App Manifest lets you describe an entire application as a JSON schema (components, state, computed properties, methods, templates) and have an AI generate the working code from the manifest, mediated through framework-specific idiom files.

You: "Build me a todo app with
WildflowerJS"

AI reads llms.txt or ai-assistant.html
     ↓
Generates standard HTML + JS
     ↓
<div data-component="todo-app">
  <input data-model="newItem">
  <button data-action="addItem">
    Add
  </button>
  <ul data-list="items">
    <template>
      <li data-bind="text"></li>
    </template>
  </ul>
</div>
     ↓
Open in your browser. It works, and you can read and understand the code.

How Updates Work

What happens between changing a property and seeing the DOM update, in four steps.

The Mental Model: Write normal JavaScript. Mutate state. The DOM updates. This page explains the machinery that makes that possible.

The Update Pipeline

Every DOM update in WildflowerJS follows the same four-step pipeline:

1. State Change
this.count++
↓
2. Dependency Lookup
Which bindings read count?
↓
3. Effects Scheduled
Queue updates for the next microtask
↓
4. Targeted DOM Updates
Only affected nodes are touched

This pipeline runs automatically. You never interact with it directly. Just change state and the framework handles the rest.

Step by Step

1. State Change: Proxy Interception

WildflowerJS wraps component state in a JavaScript Proxy. When you assign a property, the Proxy's set trap fires:

// You write:
this.count++

// The Proxy intercepts this as:
// set(target, 'count', 1)
// → records that 'count' changed
// → schedules an update

This works for any mutation: direct assignment, nested property changes, array methods:

this.count++                    // direct assignment
this.user.name = "Jane"         // nested property
this.items.push({ text: "New" }) // array mutation
this.items.splice(2, 1)         // array splice

All of these are intercepted automatically. No special syntax, no wrapper functions, no immutable update patterns required.

2. Dependency Lookup: Path-Level Tracking

When the framework processes a binding like data-bind="count", it records that this specific DOM node depends on the count property. This creates a mapping:

Property Path    →    DOM Nodes
─────────────         ─────────
count            →    span#counter-display
user.name        →    h1#greeting, span#profile-name
items            →    ul#todo-list (list binding)
items[].text     →    each li text node

When count changes, the framework looks up exactly which nodes depend on it. No tree walking, no component re-rendering, no diffing. Just a direct lookup.

3. Effects Scheduled: Microtask Batching

Updates are not applied immediately. Instead, they are queued and flushed in a single microtask:

// All three changes happen synchronously
this.firstName = "Jane"
this.lastName = "Smith"
this.email = "jane@example.com"

// But the DOM is updated only ONCE,
// after this synchronous block completes.
// Three state changes → one DOM update.

This is automatic. You never need to wrap changes in a batch function or call a flush method. The framework collects all changes within the current synchronous execution, then applies them together.

4. Targeted DOM Updates: Surgical Precision

When the microtask fires, only the specific DOM nodes that depend on changed properties are updated:

<div data-component="profile">
    <h1 data-bind="name"></h1>       <!-- Updated ✓ -->
    <p data-bind="bio"></p>         <!-- NOT touched -->
    <span data-bind="email"></span>  <!-- NOT touched -->
</div>

If only name changed, only the <h1> is touched. The <p> and <span> are untouched. The framework doesn't even look at them.

How This Differs from Virtual DOM

Virtual DOM (React, Vue)
  1. State changes
  2. Re-render entire component to virtual tree
  3. Diff old virtual tree vs new virtual tree
  4. Compute minimal set of DOM patches
  5. Apply patches to real DOM

Work is proportional to component size

WildflowerJS
  1. State changes
  2. Look up which bindings depend on changed path
  3. Update those DOM nodes directly

Work is proportional to number of changes

The key difference: virtual DOM frameworks do work proportional to component size (they must re-render and diff the entire component). WildflowerJS does work proportional to what actually changed: if one property changed and two DOM nodes depend on it, only those two nodes are touched regardless of how large the component is.

List Updates: Operation Detection

Lists get special treatment. Instead of re-rendering the entire list when an array changes, WildflowerJS detects what kind of operation occurred and applies the minimal DOM change:

Array Operation DOM Response
items.push(item) Append one new node
items.pop() Remove last node
items.splice(2, 1) Remove node at index 2
items.unshift(item) Prepend one new node
items[i] = newItem Update node at index i in place
items = [...items].sort(fn) Reconcile with minimal moves

Most frameworks require you to use keys and write diff-friendly code for efficient list updates. WildflowerJS infers the intent from the operation itself.

Nested Reactivity

The Proxy wrapping is deep: it covers nested objects and arrays automatically:

// All of these trigger updates automatically:
this.user.address.city = "Portland"    // deep nested property
this.columns[2].cards.push(newCard)    // nested array mutation
this.settings = { ...this.settings, theme: "dark" }  // object replacement

There is no depth limit. The framework tracks changes at whatever level they occur and updates only the bindings that depend on the changed path.

What This Means for You

The bottom line: Write natural JavaScript. Assign properties, push to arrays, mutate nested objects. The framework detects changes, finds affected DOM nodes, batches updates, and applies them precisely, all automatically. You focus on your application logic; the framework handles the DOM.
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