react-native-data-detector

Cross-platform text data detection for React Native. Uses NSDataDetector on iOS and ML Kit Entity Extraction on Android to detect phone numbers, URLs, emails, dates, and addresses — returning structured results to JavaScript.

Features

• Phone numbers — Detect and extract phone numbers
• URLs — Detect web links
• Emails — Detect email addresses
• Addresses — Detect street addresses with parsed components (iOS)
• Dates — Detect dates and times with ISO 8601 output
• Native accuracy — Uses battle-tested platform APIs instead of regex
• Expo Modules API — Built with the modern Expo native module system

Installation

npm install react-native-data-detector

iOS

npx pod-install

Android

The ML Kit entity extraction model (~5.6MB) is downloaded on the user's device at runtime. You can control when this happens using downloadModel() — for example, calling it at app startup to ensure detect() works offline later. If you don't call it explicitly, the model will be downloaded automatically on the first detect() call.

Usage

import { detect, downloadModel } from 'react-native-data-detector';

// Pre-download the ML Kit model at app startup (Android only, no-op on iOS)
await downloadModel();

// Detect all entity types
const entities = await detect('Call me at 555-1234 or email [email protected]');
// [
//   { type: 'phoneNumber', text: '555-1234', start: 14, end: 22, data: { phoneNumber: '555-1234' } },
//   { type: 'email', text: '[email protected]', start: 32, end: 48, data: { email: '[email protected]' } }
// ]

// Detect only specific types
const phones = await detect('Call 555-1234 or visit https://example.com', {
  types: ['phoneNumber'],
});
// [
//   { type: 'phoneNumber', text: '555-1234', start: 5, end: 13, data: { phoneNumber: '555-1234' } }
// ]

API

downloadModel()

Pre-downloads the ML Kit entity extraction model on Android. On iOS, this is a no-op that resolves immediately — NSDataDetector is built into the OS and requires no model download.

Call this at app startup or before the first detect() call to ensure the model is available offline.

Returns: Promise<boolean> — true when the model is ready.

| Platform | Behavior | |----------|----------| | iOS | No-op, resolves true immediately | | Android | Downloads the ML Kit model (~5.6MB) if not already cached. Requires internet on first call. |

detect(text, options?)

Detects entities in the given text using native platform APIs.

Parameters:

| Parameter | Type | Description | |-----------|------|-------------| | text | string | The text to analyze | | options | DetectOptions | Optional configuration |

DetectOptions:

| Property | Type | Default | Description | |----------|------|---------|-------------| | types | DetectionType[] | All types | Which entity types to detect |

DetectionType: 'phoneNumber' | 'link' | 'email' | 'address' | 'date'

Returns: Promise<DetectedEntity[]>

DetectedEntity

| Property | Type | Description | |----------|------|-------------| | type | DetectionType | The type of detected entity | | text | string | The matched text substring | | start | number | Start index in the original string | | end | number | End index (exclusive) in the original string | | data | Record<string, string> | Additional structured data (see below) |

Entity Data by Type

| Type | Data fields | |------|-------------| | phoneNumber | { phoneNumber } | | link | { url } | | email | { email } | | address | { street, city, state, zip, country } (iOS) / { address } (Android) | | date | { date } ISO 8601 string |

Platform Differences

| Feature | iOS | Android | |---------|-----|---------| | Engine | NSDataDetector | ML Kit Entity Extraction | | Offline | Always | After downloadModel() or first detect() call | | Model download | Not needed | ~5.6MB, on-device at runtime | | Address parsing | Structured components | Raw string | | Date output | ISO 8601 | ISO 8601 |

Requirements

• iOS 15.1+
• Android API 24+ (minSdk)
• Expo SDK 50+ or bare React Native with expo-modules-core

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

MIT