}>
{githubName}
{packageRepos.map(repo => }>
{repo.name}
)}
{examples.map(({url, name}) => }>
{name}
)}
}>
Get help on Slack
;
};
export const ExternalLink = () => {
return ;
};
The documentation is meant for client-side environments. Check out the [Node.js docs](/lib/node) for server-side environments.
## Installation
Install with a package manager
```bash npm2yarn theme={null}
npm install --save @growthbook/growthbook
```
## Quick Usage
### Step 1: Configure your app
```js theme={null}
import { GrowthBook } from "@growthbook/growthbook";
// Create a GrowthBook instance
const gb = new GrowthBook({
apiHost: "https://cdn.growthbook.io",
clientKey: "sdk-abc123",
// Targeting attributes
attributes: {
id: "123",
country: "US"
},
// Only required for A/B testing
// Called every time a user is put into an experiment
trackingCallback: (experiment, result, user) => {
console.log("Experiment Viewed", {
experimentId: experiment.key,
variationId: result.key,
attributes: user?.attributes,
});
},
});
// Download features and experiments from the CDN
// Also, start running any Visual Editor or URL Redirect experiments
await gb.init();
```
### Step 2: Start Feature Flagging!
There are 2 main methods for evaluating features: `isOn` and `getFeatureValue`:
```js theme={null}
// Simple boolean (on/off) feature flag
if (gb.isOn("my-feature")) {
console.log("Feature enabled!");
}
// Get the value of a string/JSON/number feature with a fallback
const color = gb.getFeatureValue("button-color", "blue");
```
## Plugins
GrowthBook comes with a number of built-in plugins that add additional functionality. You can enable these by passing them into the GrowthBook constructor.
Plugins require GrowthBook version 1.4.0 or higher, released in Feb 2025.
### Third Party Tracking
The third-party tracking plugin automatically sends an "Experiment Viewed" event to several popular analytics tracking tools (Segment, Google Analytics, and Google Tag Manager). This plugin requires a browser environment and does not work from Node.js.
This plugin does not install any 3rd party libraries, it just sends events to ones that are already installed on your site. Below are all of the supported trackers:
* `segment` - Requires `window.analytics` to be defined.
* `gtag` - Requires `window.gtag` to be defined.
* `gtm` - Requires `window.dataLayer` to be defined.
```js theme={null}
import { thirdPartyTrackingPlugin } from "@growthbook/growthbook/plugins";
// Optional settings for the plugin
const pluginOptions = {
// By default, it will attempt to send to all 3 of these
trackers: ["segment", "gtag", "gtm"],
// Additional custom tracking callback
additionalCallback: (experiment, result) => {
console.log("Experiment Viewed", {
experimentId: experiment.key,
variationId: result.key,
})
}
}
const gb = new GrowthBook({
apiHost: "https://cdn.growthbook.io",
clientKey: "sdk-abc123",
plugins: [
thirdPartyTrackingPlugin(pluginOptions),
],
});
```
### Auto-Attributes
The auto-attributes plugin automatically detects and sets common attributes in GrowthBook for the current user. These attributes are available locally for targeting and are not sent to GrowthBook's servers.
This plugin requires a browser environment and does not work from Node.js.
```js theme={null}
import { autoAttributesPlugin } from "@growthbook/growthbook/plugins";
// Optional settings for the plugin (documented below)
const pluginOptions: {}
const gb = new GrowthBook({
apiHost: "https://cdn.growthbook.io",
clientKey: "sdk-abc123",
plugins: [
autoAttributesPlugin(pluginOptions),
],
});
```
#### Attributes
Here is a list of all attributes that are set by this plugin:
* `id` - A random unique identifier for the user, persisted in a cookie
* `url` - The current URL of the page
* `path` - The current URL path of the page
* `host` - The current URL host of the page
* `query` - The current URL query string of the page
* `pageTitle` - The current page title
* `deviceType` - The device type of the user. Either "mobile" or "desktop"
* `browser` - The browser name of the user (edge, chrome, firefox, safari, or unknown)
* `utmSource`, `utmMedium`, `utmCampaign`, `utmTerm`, `utmContent` - UTM parameters from the URL (persisted in sessionStorage for subsequent page views)
In addition, any variables set through Google Tag Manager (`window.dataLayer`) will be added as attributes as well.
You can still specify your own custom attributes in the GrowthBook constructor, and they will be merged with the auto-attributes.
#### Options
By default the plugin generates a random UUID for the user and stores it in a cookie. You can customize this behavior with the following options.
* `uuidKey` - The attribute key to use for the uuid (default is `id`)
* `uuid` - Pass in your own user id instead of having the plugin generate a random one.
* `uuidCookieName` - The name of the cookie to use for the generated uuid (default is `gb_uuid`)
* `uuidCookieDomain` - Scope the uuid cookie to a parent domain (e.g. `".example.com"`) so the same anonymous id is shared across subdomains. Recommended if you run experiments that redirect users between subdomains, otherwise the visitor gets a new id (and can be re-bucketed) on the destination subdomain.
* `uuidAutoPersist` - If `false`, the generated id will NOT be stored in a cookie automatically. Default depends on the `uuid` option. If `uuid` is set, the default is `false`. Otherwise, the default is `true`.
If you have a cookie consent banner, you can set `uuidAutoPersist` to `false` and then later manually trigger the cookie to be saved by calling:
```js theme={null}
document.dispatchEvent(new CustomEvent("growthbookpersist"));
```
## Loading Features and Experiments
In order for the GrowthBook SDK to work, it needs to have feature and experiment definitions from the GrowthBook API. There are a few ways to get this data into the SDK.
### Built-in Fetching and Caching
If you pass an `apiHost` and `clientKey` into the GrowthBook constructor, it will handle the network requests, caching, retry logic, etc. for you automatically. If your feature payload is encrypted, you can also pass in a `decryptionKey`.
```ts theme={null}
const gb = new GrowthBook({
apiHost: "https://cdn.growthbook.io",
clientKey: "sdk-abc123",
// Only required if you have feature encryption enabled in GrowthBook
decryptionKey: "key_abc123",
});
// Wait for features to be downloaded with a timeout (in ms)
await gb.init({
timeout: 2000,
});
```
Until features are loaded, all features will evaluate to `null`. If you're ok with a potential flicker in your application (features going from `null` to their real value), you can call `init` without awaiting the result.
If you want to refresh the features at any time (e.g. when a navigation event occurs), you can call `gb.refreshFeatures()`.
#### Error Handling
In the case of network issues, the `init` call will not throw an error. Instead, it will stay in the default state where every feature evaluates to `null`.
You can still get access to the error if needed:
```ts theme={null}
const res = await gb.init({
timeout: 1000
});
console.log(res);
```
The return value has 3 properties:
* **success** - `true` if the GrowthBook instance was populated with features/experiments. Otherwise `false`
* **source** - Where this result came from. One of the following values: `network`, `cache`, `init`, `error`, or `timeout`
* **error** - If success is `false`, this will contain an `Error` object with more details about the error
### Custom Integration
If you prefer to handle the network and caching logic yourself, you can pass in a full JSON "payload" directly into the SDK. For example, you might store features in Postgres and send it down to your front-end as part of your app's initial bootstrap API call.
```ts theme={null}
await gb.init({
payload: {
features: {
"feature-1": {...},
"feature-2": {...},
"another-feature": {...},
}
}
})
```
The data structure for "payload" is exactly the same as what is returned by the GrowthBook SDK endpoints and webhooks.
You can update the payload at any time by calling `setPayload(newPayloadJSON)` and there are also `getPayload()` and `getDecryptedPayload()` methods, which are useful in hybrid apps where you want to hydrate the client with data from the server.
Note: you don't need to specify `clientKey` or `apiHost` on your GrowthBook instance unless you want to enable streaming (see below) or call `refreshFeatures()` later.
#### Synchronous Init
There is a alternate synchronous version of init named `initSync`, which can be useful in some environments. There are some restrictions/differences:
* You MUST pass in `payload`
* The `payload` MUST NOT have encrypted features or experiments
* If using sticky bucketing, you should use an instance of `StickyBucketServiceSync`, such as `BrowserCookieStickyBucketService`.
* The return value is the GrowthBook instance to enable easy method chaining
## Streaming Updates
The GrowthBook SDK supports streaming with Server-Sent Events (SSE). When enabled, changes to features within GrowthBook will be streamed to the SDK in realtime as they are published. This is only supported on GrowthBook Cloud or if running a GrowthBook Proxy Server.
### Streaming in Browser Environments
SSE is supported on all major browsers, so enabling streaming is as easy as passing `streaming: true` into your `init` call:
```ts theme={null}
gb.init({
streaming: true,
// Other settings...
})
```
You may also differentiate your streaming host URL from your API host by setting the `streamingHost` property in the GrowthBook constructor (ex: Remote Evaluation is done on a CDN edge worker while Streaming is done through a GrowthBook Proxy server).
## Remote Evaluation
See the [Remote Evaluation overview](/self-host/remote-evaluation) for more information about what Remote Evaluation is, how it works, and deployment options.
When used in a front-end context, the JS SDK may be run in Remote Evaluation mode. This mode brings the security benefits of a backend SDK to the front end by evaluating feature flags exclusively on a private server. Using Remote Evaluation ensures that any sensitive information within targeting rules or unused feature variations are never seen by the client. Note that Remote Evaluation should not be used in a backend context.
You must enable Remote Evaluation in your SDK Connection settings. Cloud customers are also required to self-host a GrowthBook Proxy Server, edge worker, or custom remote evaluation backend.
To use Remote Evaluation, add the `remoteEval: true` property to your SDK instance. A new evaluation API call will be made any time a user attribute or other dependency changes. You may optionally limit these API calls to specific attribute changes by setting the `cacheKeyAttributes` property (an array of attribute names that, when changed, trigger a new evaluation call).
```ts theme={null}
const gb = new GrowthBook({
apiHost: "https://gb-proxy.mydomain.io/",
clientKey: "sdk-abc123",
// Enable remote evaluation
remoteEval: true,
// Optional: only trigger a new evaluation call when the `id` and `email` attribute changes
cacheKeyAttributes: ["id", "email"],
});
```
**Sticky Bucketing with Remote Evaluation**
If you would like to implement Sticky Bucketing while using Remote Evaluation, you must configure your remote evaluation backend to support Sticky Bucketing. In the case of the GrowthBook Proxy Server, this means implementing a Redis database for sticky bucketing use. You will not need to provide a StickyBucketService instance to the client side SDK.
## Caching
The JavaScript SDK has 2 caching layers:
1. In-memory cache (available on all platforms)
2. Persistent localStorage cache (only available in browsers by default)
There are a number of cache settings you can configure within GrowthBook. This must be done BEFORE creating a GrowthBook instance.
Below are all of the default values. You can call `configureCache` with a subset of these fields and the rest will keep their default values.
```ts theme={null}
import { configureCache } from "@growthbook/growthbook";
configureCache({
// The localStorage key the cache will be stored under
cacheKey: "gbFeaturesCache",
// Consider features stale after this much time (60 seconds default)
staleTTL: 1000 * 60,
// Cached features older than this will be ignored (4 hours default)
maxAge: 1000 * 60 * 60 * 4,
// For Remote Eval only - limit the number of cache entries (~1 entry per user)
maxEntries: 10,
// When `false`, we add a `visibilitychange` listener to disable SSE when the page is idle
disableIdleStreams: false,
// Consider a page "idle" when it is hidden for this long (default 20 seconds)
idleStreamInterval: 20000,
// Set to `true` to completely disable both in-memory and persistent caching
disableCache: false,
})
```
## Polyfills
The GrowthBook SDK relies on `fetch`, `SubtleCrypto`, `EventSource`, and `localStorage` being available at runtime. In browser environments these are natively available, but you can override any of them with `setPolyfills` if needed.
This is especially useful when:
* Running in a non-browser JS environment (e.g. testing with Jest or jsdom) where globals like `fetch` or `localStorage` may not be available
* Using a custom `EventSource` implementation for streaming
* Providing an alternative persistent storage backend in place of `localStorage`
```js theme={null}
import { setPolyfills } from "@growthbook/growthbook";
setPolyfills({
// Custom fetch implementation
fetch: myCustomFetch,
// Custom SubtleCrypto implementation
SubtleCrypto: mySubtleCrypto,
// Custom EventSource implementation (for streaming support)
EventSource: myEventSource,
// localStorage-compatible object
localStorage: {
getItem: (key) => myStorage.get(key),
setItem: (key, value) => myStorage.set(key, value),
},
});
```
**Note**: `setPolyfills` must be called **before** creating a GrowthBook instance.
For server-side (Node.js) usage, see the [Node.js SDK docs](/lib/node) which covers required polyfills for that environment.
## Re-rendering When Features Change
When features change (e.g. by calling `gb.refreshFeatures()`), you need to re-render your app so that all of your feature flag checks can be re-evaluated. You can specify your own custom rendering function for this purpose:
```js theme={null}
// Callback to re-render your app when feature flag values change
gb.setRenderer(() => {
// TODO: re-render your app
});
```
## Experimentation (A/B Testing)
In order to run A/B tests, you need to set up a tracking callback function. This is called every time a user is put into an experiment and can be used to track the exposure event in your analytics system (Segment, Mixpanel, GA, etc.).
**Note**: If you use the `third-party-tracking` plugin, you don't need to specify a `trackingCallback` since the plugin will handle that for you automatically.
```js theme={null}
const gb = new GrowthBook({
apiHost: "https://cdn.growthbook.io",
clientKey: "sdk-abc123",
trackingCallback: (experiment, result, user) => {
// Example using Segment
analytics.track("Experiment Viewed", {
experimentId: experiment.key,
variationId: result.key,
attributes: user?.attributes,
});
},
});
```
Starting in version 1.7.0, the callback receives a third `user` argument: a `TrackingUserContext` containing the `attributes` and optional `url` used when the experiment was evaluated. We recommend recording attributes from this argument so exposure events consistently reflect the attributes GrowthBook used for targeting and assignment.
This same tracking callback is used for both feature flag experiments and Visual Editor experiments.
### Feature Flag Experiments
There is nothing special you have to do for feature flag experiments. Just evaluate the feature flag like you would normally do. If the user is put into an experiment as part of the feature flag, it will call the `trackingCallback` automatically in the background.
```js theme={null}
// If this has an active experiment and the user is included,
// it will call trackingCallback automatically
const newLogin = gb.isOn("new-signup-form");
```
If the experiment came from a feature rule, `result.featureId` in the trackingCallback will contain the feature id, which may be useful for tracking/logging purposes.
### Visual Editor Experiments
Experiments created through the GrowthBook Visual Editor will run automatically as soon as their targeting conditions are met.
**Note**: Visual Editor experiments are only supported in a web browser environment. They will not run in Node.js, Mobile apps, or Desktop apps.
If you are using this SDK in a Single Page App (SPA), you will need to let the GrowthBook instance know when the URL changes so the active experiments can update accordingly.
```js theme={null}
// Call this every time a navigation event happens in your SPA
function onRouteChange() {
gb.setURL(window.location.href);
}
```
Visual Editor experiments are enabled by default, but can be disabled with various GrowthBook constructor settings:
* **disableVisualExperiments** - If true, all visual editor experiments will be skipped
* **disableJsInjection** - If true, any visual editor experiment that injects custom javascript will be skipped.
#### Content Security Policy
If you plan to use the Custom Javascript feature of the Visual Editor and you have a Content Security Policy on your site, there are two options:
1. Enable `unsafe-inline` script-src
2. OR generate a unique nonce value, add it to your script-src directive, and pass it into the GrowthBook constructor as `jsInjectionNonce`
### URL Redirect Experiments
Similarly to Visual Editor experiments, URL redirect tests will run automatically if targeting conditions are met.
If you are using this SDK in a Single Page App (SPA), you'll want to pass in a custom navigation function into the SDK (as default navigation for URL Redirects uses `window.location.replace(url)`) and set the `navigateDelay` to 0.
```js theme={null}
// Example in Next.js
import router from "next/router";
const gb = new GrowthBook({
navigate: (url) => router.replace(url),
navigateDelay: 0,
// ... other settings
});
```
For SPA's you will also need to let the GrowthBook instance know when the URL changes so the active experiments can update accordingly.
```js theme={null}
// Call this every time a navigation event happens in your SPA
function onRouteChange() {
gb.setURL(window.location.href);
}
```
URL Redirect experiments are enabled by default, but can be disabled with various GrowthBook constructor settings:
* **disableUrlRedirectExperiments** - If true, all URL Redirect experiments will be skipped
* **disableCrossOriginUrlRedirectExperiments** - If true, any URL Redirect with a destination pointing to a different origin will be skipped.
### Deferred Tracking
Sometimes, your analytics tracker is loaded after GrowthBook. In that case, you should not specify a `trackingCallback` in the constructor and instead use `setTrackingCallback` later when ready. When you do this, the GrowthBook instance will queue up tracking calls and then fire them all at once when you set the callback.
There are some scenarios where you need to queue up tracking calls in one GrowthBook instance and fire them in another. For example, if your analytics tracker is only available on the front-end, but you are running experiments in Node.js.
Export the queued tracking calls with the `getDeferredTrackingCalls()` method. The result is a serializable JSON object containing the experiment, result, and `user` context captured during evaluation:
```ts theme={null}
const tracks = gb.getDeferredTrackingCalls();
```
When these calls are serialized and sent between a server and client, the captured `user` context is passed as the third argument to the tracking callback. Deferred calls created by SDK versions earlier than 1.7.0 may not include `user`.
Then, import with `setDeferredTrackingCalls`. This does not fire them automatically. You must call `fireDeferredTrackingCalls` after.
```ts theme={null}
gb2.setDeferredTrackingCalls(tracks);
gb2.fireDeferredTrackingCalls();
```
### Sticky Bucketing
Sticky bucketing ensures that users see the same experiment variant, even when user session, user login status, or experiment parameters change. See the [Sticky Bucketing docs](/app/sticky-bucketing) for more information. If your organization and experiment supports sticky bucketing, you must implement an instance of the `StickyBucketService` to use Sticky Bucketing. The JS SDK exports several implementations of this service for common use cases, or you may build your own:
* `LocalStorageStickyBucketService` —
For simple bucket persistence using the browser's LocalStorage (can be polyfilled for other environments).
* `BrowserCookieStickyBucketService` — For simple bucket persistence using browser cookies, which are transportable to the back end. Assumes `js-cookie` is implemented (can be polyfilled). Cookie attributes can also be configured. The default cookie expiry is 180 days; override by passing `expires: {days}` into the constructor's `cookieAttributes`.
* Build your own — Implement the abstract `StickyBucketService` class and connect to your own data store, or custom wrap multiple service implementations (ex: read/write to both cookies and Redis).
Implementing most StickyBucketService implementations is straightforward and works with minimal setup. For instance, to use the `BrowserCookieStickyBucketService`:
```js theme={null}
import { BrowserCookieStickyBucketService } from "@growthbook/growthbook";
import Cookies from 'js-cookie';
const gb = new GrowthBook({
apiHost: "https://cdn.growthbook.io",
clientKey: "sdk-abc123",
stickyBucketService: new BrowserCookieStickyBucketService({
jsCookie: Cookies,
}),
// ...
});
```
## TypeScript
When used in a TypeScript project, GrowthBook includes basic type inference out of the box:
```ts theme={null}
// Type will be `string` based on the fallback provided ("blue")
const color = gb.getFeatureValue("button-color", "blue");
// You can manually specify types as well
// feature.value will be type `number`
const feature = gb.evalFeature("font-size");
console.log(feature.value);
// Experiments will use the variations to infer the return value
// result.value will be type "string"
const result = gb.run({
key: "my-test",
variations: ["blue", "green"],
});
```
### Strict Typing
If you want to enforce stricter types in your application, you can do that when creating the GrowthBook instance:
```ts theme={null}
// Define all your feature flags and types here
interface AppFeatures {
"button-color": string;
"font-size": number;
"newForm": boolean;
}
// Pass into the GrowthBook instance
const gb = new GrowthBook({
...
});
```
Now, all feature flag methods will be strictly typed.
```ts theme={null}
// feature.value will by type `number`
const feature = gb.evalFeature("font-size");
console.log(feature.value);
// Typos will cause compile-time errors
gb.isOn("buton-color"); // "buton" instead of "button"
```
Instead of defining the `AppFeatures` interface manually like above, you can auto-generate it from your GrowthBook account using the [GrowthBook CLI](/tools/cli).
## Updating
As a general philosophy, we aim to keep the SDK 100% backwards compatible at all times. View the [Changelog](https://github.com/growthbook/growthbook/blob/main/packages/sdk-js/CHANGELOG.md) for a complete list of all SDK changes.
### Updating to 1.0.0
Updating from a **0.X.X** release to **1.0.0** is still backwards compatible for the vast majority of use cases, although there are a few minor changes:
* The `enableDevMode: true` setting previously also disabled cache as a side-effect. This is no longer the case in 1.0.0, and you must explicitly also set `disableCache: true`
* Previously, a network request to fetch features was started immediately upon creating a GrowthBook instance. Starting in 1.0.0, it waits until you call `loadFeatures` (or the new `init` method) before starting the network request. As a replacement, there is now a standalone `prefetchPayload` function that you can use to kick off a network request outside of the context of a GrowthBook instance.
#### Switching to init
GrowthBook 1.0.0 introduced a new `init` (and `initSync`) method.
We recommend everyone starts using this in their implementation. It solves many pain points including easier error handling and more control over caching and streaming.
For those currently using `loadFeatures`, `init` is a direct replacement. The only difference is that streaming is now opt-in instead of on-by-default.
```ts theme={null}
// Previous
await gb.loadFeatures({ timeout: 1000 });
// New
await gb.init({ timeout: 1000, streaming: true });
```
For those currently NOT using `loadFeatures` and passing features/experiments directly into the GrowthBook constructor, `init` and `initSync` can be used instead. The code below assumes you have a `payload` variable with the contents from the SDK Connection Endpoint.
```ts theme={null}
// Previous
const gb = new GrowthBook({
features: payload.features,
experiments: payload.experiments
});
// New (async)
const gb = new GrowthBook();
await gb.init({ payload: payload });
// New (non-async)
const gb = (new GrowthBook()).initSync({ payload: payload });
```
## GrowthBook Instance (reference)
### Attributes
You can specify attributes about the current user and request. These are used for two things:
1. Feature targeting (e.g. paid users get one value, free users get another)
2. Assigning persistent variations in A/B tests (e.g. user id "123" always gets variation B)
The following are some commonly used attributes, but use whatever makes sense for your application.
```ts theme={null}
new GrowthBook({
attributes: {
id: "123",
loggedIn: true,
deviceId: "abc123def456",
company: "acme",
paid: false,
url: "/pricing",
browser: "chrome",
mobile: false,
country: "US",
},
});
```
#### Updating Attributes
If attributes change, you can call `setAttributes()` to update. This will completely overwrite any existing attributes. To do a partial update, use the following pattern:
```js theme={null}
gb.setAttributes({
// Only update the `url` attribute, keep the rest the same
...gb.getAttributes(),
url: "/new-page"
})
```
#### Secure Attributes
When *secure attribute hashing* is enabled, all targeting conditions in the SDK payload referencing attributes with datatype `secureString` or `secureString[]` will be anonymized via SHA-256 hashing. This allows you to safely target users based on sensitive attributes. You must enable this feature in your SDK Connection for it to take effect.
If your SDK Connection has secure attribute hashing enabled, you will need to manually hash any `secureString` or `secureString[]` attributes that you pass into the GrowthBook SDK.
To hash an attribute, use a cryptographic library with SHA-256 support, and compute the SHA-256 hashed value of your attribute *plus* your organization's secure attribute salt.
The example below is using CryptoJS ([https://www.npmjs.com/package/crypto-js](https://www.npmjs.com/package/crypto-js)), which provides a synchronous API.
```js theme={null}
import sha256 from 'crypto-js/sha256';
const salt = "f09jq3fij"; // Your secure attribute salt (set in Organization Settings)
// hashing a secureString attribute
const userEmail = sha256(salt + user.email).toString();
// hashing a secureString[] attribute
const userTags = user.tags.map(tag => sha256(salt + tag).toString());
gb.setAttributes({
id: user.id,
loggedIn: true,
email: userEmail,
tags: userTags,
});
await gb.init();
```
If you prefer to use a browser native implementation, you will need to await hashing before calling `setAttributes` since SubtleCrypto methods are async. Here's an example implementation:
```js theme={null}
// Native browser implementation
async function sha256(str) {
const buffer = await crypto.subtle.digest("SHA-256", new TextEncoder().encode(str));
const hashArray = Array.from(new Uint8Array(buffer));
return hashArray.map(byte => byte.toString(16).padStart(2, "0")).join("");
}
// Hashing a single string
const userEmail = await sha256(salt + user.email);
// Hashing an array of strings
const userTags = await Promise.all(
user.tags.map(tag => sha256(salt + tag))
);
```
### Feature Usage Callback
GrowthBook can fire a callback whenever a feature is evaluated for a user. This can be useful to update 3rd party tools like NewRelic or DataDog.
```ts theme={null}
new GrowthBook({
onFeatureUsage: (featureKey, result) => {
console.log("feature", featureKey, "has value", result.value);
},
});
```
The `result` argument is the same thing returned from `gb.evalFeature`.
Note: If you evaluate the same feature multiple times (and the value doesn't change), the callback will only be fired the first time.
### Dev Mode
There is a [GrowthBook Chrome DevTools Extension](https://chrome.google.com/webstore/detail/growthbook-devtools/opemhndcehfgipokneipaafbglcecjia) that can help you debug and test your feature flags in development.
In order for this to work, you must explicitly enable dev mode when creating your GrowthBook instance:
```js theme={null}
const gb = new GrowthBook({
enableDevMode: true,
});
```
To avoid exposing all of your internal feature flags and experiments to users, we recommend setting this to `false` in production in most cases.
### evalFeature
In addition to the `isOn` and `getFeatureValue` helper methods, there is the `evalFeature` method that gives you more detailed information about why the value was assigned to the user.
```ts theme={null}
// Get detailed information about the feature evaluation
const result = gb.evalFeature("my-feature");
// The value of the feature (or `null` if not defined)
console.log(result.value);
// Why the value was assigned to the user
// One of: `override`, `unknownFeature`, `defaultValue`, `force`, or `experiment`
console.log(result.source);
// The string id of the rule (if any) which was used
console.log(result.ruleId);
// Information about the experiment (if any) which was used
console.log(result.experiment);
// The result of the experiment (or `undefined`)
console.log(result.experimentResult);
```
### Inline Experiments
Instead of declaring all features up-front in the context and referencing them by ids in your code, you can also just run an experiment directly. This is done with the `gb.run` method:
```js theme={null}
// These are the only required options
const { value } = gb.run({
key: "my-experiment",
variations: ["red", "blue", "green"],
});
```
#### Customizing the Traffic Split
By default, this will include all traffic and do an even split between all variations. There are 2 ways to customize this behavior:
```js theme={null}
// Option 1: Using weights and coverage
gb.run({
key: "my-experiment",
variations: ["red", "blue", "green"],
// Only include 10% of traffic
coverage: 0.1,
// Split the included traffic 50/25/25 instead of the default 33/33/33
weights: [0.5, 0.25, 0.25],
});
// Option 2: Specifying ranges
gb.run({
key: "my-experiment",
variations: ["red", "blue", "green"],
// Identical to the above
// 5% of traffic in A, 2.5% each in B and C
ranges: [
[0, 0.05],
[0.5, 0.525],
[0.75, 0.775],
],
});
```
#### Hashing
We use deterministic hashing to assign a variation to a user. We hash together the user's id and experiment key, which produces a number between `0` and `1`. Each variation is assigned a range of numbers, and whichever one the user's hash value falls into will be assigned.
You can customize this hashing behavior:
```js theme={null}
gb.run({
key: "my-experiment",
variations: ["A", "B"],
// Which hashing algorithm to use
// Version 2 is the latest and the one we recommend
hashVersion: 2,
// Use a different seed instead of the experiment key
seed: "abcdef123456",
// Use a different user attribute (default is `id`)
hashAttribute: "device_id",
});
```
**Note**: For backwards compatibility, if no `hashVersion` is specified, it will fall back to using version `1`, which is deprecated. In the future, version `2` will become the default. We recommend specifying version `2` now for all new experiments to avoid migration issues down the line.
#### Meta Info
You can also define meta info for the experiment and/or variations. These do not affect the behavior, but they are passed through to the `trackingCallback`, so they can be used to annotate events.
```js theme={null}
gb.run({
key: "results-per-page",
variations: [10, 20],
// Experiment meta info
name: "Results per Page",
phase: "full-traffic"
// Variation meta info
meta: [
{
key: "control",
name: "10 Results per Page",
},
{
key: "variation",
name: "20 Results per Page",
},
]
})
```
#### Mutual Exclusion
Sometimes you want to run multiple conflicting experiments at the same time. You can use the `filters` setting to run mutually exclusive experiments.
We do this using deterministic hashing to assign users a value between 0 and 1 for each filter.
```js theme={null}
// Will include 60% of users - ones with a hash between 0 and 0.6
gb.run({
key: "experiment-1",
variation: [0, 1],
filters: [
{
seed: "pricing",
attribute: "id",
ranges: [[0, 0.6]]
}
]
});
// Will include the other 40% of users - ones with a hash between 0.6 and 1
gb.run({
key: "experiment-2",
variation: [0, 1],
filters: [
{
seed: "pricing",
attribute: "id",
ranges: [[0.6, 1.0]]
}
]
});
```
**Note** - If a user is excluded from an experiment due to a filter, the rule will be skipped and the next matching rule will be used instead.
#### Holdout Groups
To use global holdout groups, use a nested experiment design:
```js theme={null}
// The value will be `true` if in the holdout group, otherwise `false`
const holdout = gb.run({
key: "holdout",
variations: [true, false],
// 10% of users in the holdout group
weights: [0.1, 0.9]
});
// Only run your main experiment if the user is NOT in the holdout
if (!holdout.value) {
const res = gb.run({
key: "my-experiment",
variations: ["A", "B"]
})
}
```
#### Targeting Conditions
You can also define targeting conditions that limit which users are included in the experiment. These conditions are evaluated against the `attributes` passed into the GrowthBook context. The syntax for conditions is based on the MongoDB query syntax and is straightforward to read and write.
For example, if the attributes are:
```json theme={null}
{
"id": "123",
"browser": {
"vendor": "firefox",
"version": 94
},
"country": "CA"
}
```
The following condition would evaluate to `true` and the user would be included in the experiment:
```js theme={null}
gb.run({
key: "my-experiment",
variation: [0, 1],
condition: {
"browser.vendor": "firefox",
"country": {
"$in": ["US", "CA", "IN"]
}
}
})
```
#### Inline Experiment Return Value
A call to `gb.run(experiment)` returns an object with a few useful properties:
```ts theme={null}
const {
value,
key,
name,
variationId,
inExperiment,
hashUsed,
hashAttribute,
hashValue,
} = gb.run({
key: "my-experiment",
variations: ["A", "B"],
});
// If user is included in the experiment
console.log(inExperiment); // true or false
// The index of the assigned variation
console.log(variationId); // 0 or 1
// The value of the assigned variation
console.log(value); // "A" or "B"
// The key and name of the assigned variation (if specified in `meta`)
console.log(key); // "0" or "1"
console.log(name); // ""
// If the variation was randomly assigned by hashing
console.log(hashUsed);
// The user attribute that was hashed
console.log(hashAttribute); // "id"
// The value of that attribute
console.log(hashValue); // e.g. "123"
```
The `inExperiment` flag will be false if the user was excluded from being part of the experiment for any reason (e.g. failed targeting conditions).
The `hashUsed` flag will only be true if the user was randomly assigned a variation. If the user was forced into a specific variation instead, this flag will be false.
## Feature Definitions (reference)
The feature definition JSON file contains information about all of the features in your application.
Each feature consists of a unique key, a list of possible values, and rules for how to assign those values to users.
```ts theme={null}
{
"feature-1": {...},
"feature-2": {...},
"another-feature": {...},
}
```
### Basic Feature
An empty feature always has the value `null`:
```js theme={null}
{
"my-feature": {}
}
```
#### Default Values
You can change the default assigned value with the `defaultValue` property:
```js theme={null}
{
"my-feature": {
defaultValue: "green"
}
}
```
### Rules
You can override the default value with **Rules**.
Rules give you fine-grained control over how feature values are assigned to users. There are 2 types of feature rules: `force` and `experiment`. Force rules give the same value to everyone. Experiment rules assign values to users randomly.
#### Rule Ids
Rules can specify a unique identifier with the `id` property. This can help with debugging and QA by letting you see exactly why a specific value was assigned to a user.
#### Rule Conditions
Rules can optionally define targeting conditions that limit which users the rule applies to. These conditions are evaluated against the `attributes` passed into the GrowthBook context. The syntax for conditions is based on the MongoDB query syntax and is straightforward to read and write.
For example, if the attributes are:
```json theme={null}
{
"id": "123",
"browser": {
"vendor": "firefox",
"version": 94
},
"country": "CA"
}
```
The following condition would evaluate to `true`:
```json theme={null}
{
"browser.vendor": "firefox",
"country": {
"$in": ["US", "CA", "IN"]
}
}
```
If a condition evaluates to `false`, the rule will be skipped. This means you can chain rules together with different conditions to support even the most complex use cases.
#### Force Rules
Force rules do what you'd expect - force a specific value for the feature
```js theme={null}
// Firefox users in the US or Canada get "green"
// Everyone else gets the default "blue"
{
"button-color": {
defaultValue: "blue",
rules: [
{
id: "rule-123",
condition: {
browser: "firefox",
country: {
$in: ["US", "CA"]
}
},
force: "green"
}
],
}
}
```
##### Gradual Rollouts
You can specify a `range` for your rule, which determines what percent of users will get the rule applied to them. Users who do not get the rule applied will fall through to the next matching rule (or default value). You can also specify a `seed` that will be used for hashing.
In order to figure out if a user is included or not, we use deterministic hashing. By default, we use the user attribute `id` for this, but you can override this by specifying `hashAttribute` for the rule:
This is useful for gradually rolling out features to users (start with a small range and slowly increase).
```js theme={null}
{
"new-feature": {
defaultValue: false,
rules: [
{
force: true,
hashAttribute: "device-id",
seed: 'new-feature-rollout-abcdef123',
// 20% of users
range: [0, 0.2]
// Increase to 40%:
// range: [0, 0.4]
}
]
}
}
```
#### Experiment Rules
Experiment rules let you adjust the percent of users who get randomly assigned to each variation. This can either be used for hypothesis-driven A/B tests or to simply mitigate risk by gradually rolling out new features to your users.
```js theme={null}
// Each variation gets assigned to a random 1/3rd of users
{
"image-size": {
rules: [
{
variations: ["small", "medium", "large"]
}
]
}
}
```
##### Customizing the Traffic Split
By default, an experiment rule will include all traffic and do an even split between all variations. There are 2 ways to customize this behavior:
```js theme={null}
// Option 1: Using weights and coverage
{
variations: ["red", "blue", "green"],
// Only include 10% of traffic
coverage: 0.1,
// Split the included traffic 50/25/25 instead of the default 33/33/33
weights: [0.5, 0.25, 0.25]
}
// Option 2: Specifying ranges
{
variations: ["red", "blue", "green"],
// Identical to the above
// 5% of traffic in A, 2.5% each in B and C
ranges: [
[0, 0.05],
[0.5, 0.525],
[0.75, 0.775]
]
}
```
A user is assigned a number from 0 to 1 and whichever variation's range includes their number will be assigned to them.
##### Variation Meta Info
You can use the `meta` setting to provide additional info about the variations such as name.
```js theme={null}
{
"image-size": {
rules: [
{
variations: ["sm", "md", "lg"],
ranges: [
[0, 0.5],
[0.5, 0.75],
[0.75, 1.0]
],
meta: [
{
key: "control",
name: "Small",
},
{
key: "v1",
name: "Medium",
},
{
key: "v2",
name: "Large",
}
]
}
]
}
}
```
##### Tracking Key and Name
When a user is assigned a variation, we call the `trackingCallback` function so you can record the exposure with your analytics event tracking system. By default, we use the feature id to identify the experiment, but this can be overridden if needed with the `key` setting. You can also optionally provide a human-readable name.
```js theme={null}
{
"feature-1": {
rules: [
{
// Use "my-experiment" as the key instead of "feature-1"
key: "my-experiment",
name: "My Experiment",
variations: ["A", "B"]
}
]
},
}
```
##### Hash Attribute
We use deterministic hashing to make sure the same user always gets assigned the same value. By default, we use the attribute `id`, but this can be overridden with the `hashAttribute` setting:
```js theme={null}
const gb = new GrowthBook({
attributes: {
id: "123",
company: "acme",
},
features: {
"my-feature": {
rules: [
// All users with the same "company" value
// will be assigned the same variation
{
variations: ["A", "B"],
hashAttribute: "company",
},
// If "company" is empty for the user (e.g. if they are logged out)
// The experiment will be skipped and fall through to this next rule
{
force: "A",
},
],
},
},
});
```
##### Filters
Sometimes you want to run multiple conflicting experiments at the same time. You can use the `filters` setting to run mutually exclusive experiments.
We do this using deterministic hashing to assign users a value between 0 and 1 for each filter.
```js theme={null}
{
"feature1": {
rules: [
// Will include 60% of users - ones with a hash between 0 and 0.6
{
variations: [false, true],
filters: [
{
seed: "pricing",
attribute: "id",
ranges: [[0, 0.6]]
}
]
}
]
},
"feature2": {
rules: [
// Will include the other 40% of users - ones with a hash between 0.6 and 1
{
variations: [false, true],
filters: [
{
seed: "pricing",
attribute: "id",
ranges: [[0.6, 1.0]]
}
]
},
]
}
}
```
**Note** - If a user is excluded from an experiment due to a filter, the rule will be skipped and the next matching rule will be used instead.
## Examples
* [Typescript example app with strict typing ](https://github.com/growthbook/examples/tree/main/vanilla-typescript).
## Supported Features