# Wongnai Scraper - Thailand Restaurants & Businesses (`haketa/wongnai-scraper`) Actor Wongnai scraper & data API for Thailand restaurants & local businesses: search by area, cuisine or keyword and export name, category, rating, review count, price range, address, GPS, opening hours & photos. Thailand F\&B and local market data, lead generation & research — fast, no login. - **URL**: https://apify.com/haketa/wongnai-scraper.md - **Developed by:** [Haketa](https://apify.com/haketa) (community) - **Categories:** Lead generation, Travel - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Wongnai Scraper — Thailand Restaurants, Cafés & Local Businesses Extract **Thailand local business data** from Wongnai at scale — restaurants, cafés, bars, bakeries, and more. Search by keyword, cuisine, or region and export clean, structured data: **name, category, rating, review count, price range, full address, district, GPS, and photos**. No login. No API key. Give it a keyword (Thai or English) and get back a ready-to-use dataset in JSON, CSV, Excel, or via API. > Built for F&B market research, Thailand local lead generation, and delivery/POS competitive intelligence. Thailand's largest restaurant directory — over 2 million businesses. --- ### 🧭 Table of contents - [What this scraper does](#what-this-scraper-does) - [Why use it](#why-use-it) - [Who it's for](#who-its-for) - [What data you get](#what-data-you-get) - [Input options](#input-options) - [Input examples](#input-examples) - [Output example](#output-example) - [How to use (step by step)](#how-to-use-step-by-step) - [Tips for best results](#tips-for-best-results) - [Use cases](#use-cases) - [Integrations & export](#integrations--export) - [Pricing](#pricing) - [FAQ](#faq) --- ### What this scraper does Wongnai is Thailand's leading restaurant and local-business discovery platform, with millions of listings and reviews. This actor turns its results into structured data you can analyze. Give it a **keyword** (e.g. `cafe`, `sushi`, `ก๋วยเตี๋ยว`), optionally narrowed to a **region**, and it pages through the results — returning a rich record for every business, including rating, review count, price range, address, and coordinates. You can also paste Wongnai listing URLs directly. --- ### Why use it - ⚡ **Fast & efficient** — reads embedded data directly, no slow browser rendering. - 🇹🇭 **Thailand-native** — understands Thai categories, addresses, districts, and price ranges. - ⭐ **Ratings & reviews** — average rating and review/rating counts per business. - 🌐 **English-friendly** — category names in English alongside Thai. - 🗺️ **Geo-ready** — every business includes latitude/longitude for mapping. - 💸 **Price & popularity** — price range, bookmarks, and photo counts for demand signals. - 📦 **Export anywhere** — JSON, CSV, Excel, HTML table, or RSS, plus a full REST API and integrations. --- ### Who it's for - **F&B market research** — analyze cuisines, ratings, and price tiers across Thailand. - **Delivery, POS & restaurant-tech vendors** — build prospect lists of restaurants by area. - **Lead generation** — collect business names, locations, and categories at scale. - **Franchises & chains** — monitor competitors and locations by district. - **Data & AI teams** — feed fresh, structured Thai local data into apps and assistants. --- ### What data you get Each business includes (when available): | Field | Description | | --- | --- | | `id` | Wongnai business ID | | `publicId` | Public ID | | `name` | Business name | | `branch` | Branch name | | `url` | Wongnai business URL | | `domain` | Business domain (restaurant, hotel, beauty…) | | `category` | Primary category (English) | | `categories` | All categories | | `rating` | Average rating | | `numberOfReviews` | Number of reviews | | `numberOfRatings` | Number of ratings | | `numberOfBookmarks` | Number of bookmarks | | `numberOfPhotos` | Number of photos | | `priceRange` | Price range | | `lat` / `lng` | GPS coordinates | | `zipcode` | Postal code | | `address` | Street address | | `subDistrict` | Sub-district | | `district` | District | | `province` | Province | | `official` | Official business account | | `premium` | Premium listing | | `verified` | Verification flag | | `ranking` | Ranking info | | `neighborhoods` | Neighborhoods | | `photo` | Main photo URL | | `scrapedAt` | When the record was scraped | --- ### Input options | Option | Type | Description | | --- | --- | --- | | `queries` | array | Search keywords (Thai or English) — cuisine, dish, or business type. | | `regionId` | integer | Optional Wongnai region ID to restrict results (e.g. 9 = Bangkok). | | `searchUrls` | array | Wongnai listing URLs to scrape directly. | | `maxPagesPerQuery` | integer | Result pages to paginate per query/URL (~12 businesses/page). | | `maxItems` | integer | Maximum businesses to save (0 = no limit). | | `maxConcurrency` | integer | Parallelism setting. | | `proxyConfiguration` | object | Residential proxy recommended (Thailand residential works best). | --- ### Input examples #### 1. Cafés in Bangkok ```json { "queries": ["cafe"], "regionId": 9, "maxItems": 200, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` #### 2. Multiple cuisines across all of Thailand ```json { "queries": ["sushi", "ramen", "ก๋วยเตี๋ยว"], "maxPagesPerQuery": 20, "maxItems": 1000, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ``` #### 3. From a Wongnai URL ```json { "searchUrls": ["https://www.wongnai.com/restaurants?regionId=9"] } ``` *** ### Output example ```json { "id": 146581, "name": "Kenji's Lab Thonglor", "url": "https://www.wongnai.com/restaurants/146581Om-kenji-s-lab", "domain": "restaurant", "category": "Japanese", "categories": ["Japanese"], "rating": 4.22, "numberOfReviews": 50, "numberOfRatings": 65, "priceRange": "501 - 1,000 baht", "lat": 13.736727, "lng": 100.5844, "district": "Watthana", "address": "808/13, Soi Thara Rom 2", "official": true, "photo": "https://static.wongnai.com/.../photo.jpg", "scrapedAt": "2026-06-09T10:00:00.000Z" } ``` *** ### How to use (step by step) 1. Open the actor and click **Try for free**. 2. In **Search keywords**, add terms like `cafe`, `sushi`, or a Thai keyword. 3. (Optional) Set a **Region ID** to focus on a city such as Bangkok (9). 4. Set **Max pages per query** and **Max items** to control dataset size. 5. Click **Save & Start**. 6. When the run finishes, open the **Dataset** tab and export to JSON, CSV, or Excel, or pull it via API. *** ### Tips for best results - **Keywords can be Thai or English.** `cafe`, `sushi`, `ก๋วยเตี๋ยว` all work. - **Use a region ID** to focus on a city and get more relevant results. - **Keep the residential proxy** — Thailand residential works best for reliable access at scale. - **Increase `maxPagesPerQuery`** to go deeper; there are millions of businesses available. - **Combine multiple keywords** in one run to cover several cuisines or business types. *** ### Use cases - 🍜 **F\&B market research** — map cuisines, ratings, and price tiers by district. - 🧲 **Lead generation** — build restaurant and café prospect lists by area. - 🚚 **Delivery & POS sales** — target restaurants for onboarding and partnerships. - 📊 **Competitive intelligence** — track competitors' ratings, reviews, and locations. - 🤖 **AI & data products** — feed fresh, structured Thai local data into apps and assistants. *** ### Integrations & export Export as **JSON, CSV, Excel, HTML table, or RSS**, or fetch results through the **API**. Connect to **Make, Zapier, n8n, Google Sheets, Slack, GitHub**, and more, or schedule runs to keep your dataset fresh. *** ### Pricing This actor runs on a simple pay-per-result model — you only pay for the businesses you collect. Start small with the free tier and scale up as needed. *** ### FAQ **What keywords can I use?** Any cuisine, dish, or business type in Thai or English — `cafe`, `sushi`, `ก๋วยเตี๋ยว`, `bakery`, and more. **How do I focus on one city?** Set a Region ID (e.g. 9 for Bangkok), or paste a region-specific Wongnai URL. **Do I get ratings and reviews?** Yes — each business includes its average rating and review/rating counts. **Do I need an account or key?** No login or API key is required. **Is the category in English?** Yes — category names are provided in English alongside the Thai originals. **How many businesses can I scrape?** As many as you need — there are over 2 million listings. Increase `maxPagesPerQuery` and `maxItems`. **Why is a residential proxy recommended?** Wongnai uses bot protection; a residential proxy (Thailand works best) ensures reliable access at scale. *** Need another Thailand data source, full review text, or a custom field? Open an issue on the actor's **Issues** tab — feedback and feature requests are welcome. # Actor input Schema ## `queries` (type: `array`): Keywords to search on Wongnai — cuisine, dish, or business type (Thai or English), e.g. cafe, sushi, ก๋วยเตี๋ยว. Optionally narrowed by Region ID below. ## `regionId` (type: `integer`): Wongnai region ID to restrict the search (e.g. 9 = Bangkok). Leave empty for all of Thailand. ## `searchUrls` (type: `array`): Wongnai listing URLs to scrape directly (e.g. a region, cuisine or search results page). ## `maxPagesPerQuery` (type: `integer`): How many result pages to paginate per query / URL (about 12 businesses per page). ## `maxItems` (type: `integer`): Maximum businesses to save. 0 = no limit. ## `maxConcurrency` (type: `integer`): Maximum parallel page requests. ## `proxyConfiguration` (type: `object`): Wongnai is behind Cloudflare; a residential proxy is recommended (Thailand residential works best at scale). ## Actor input object example ```json { "queries": [ "cafe", "sushi" ], "maxPagesPerQuery": 10, "maxItems": 200, "maxConcurrency": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `businesses` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "cafe" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("haketa/wongnai-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": ["cafe"], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("haketa/wongnai-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "cafe" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call haketa/wongnai-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=haketa/wongnai-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wongnai Scraper - Thailand Restaurants & Businesses", "description": "Wongnai scraper & data API for Thailand restaurants & local businesses: search by area, cuisine or keyword and export name, category, rating, review count, price range, address, GPS, opening hours & photos. Thailand F&B and local market data, lead generation & research — fast, no login.", "version": "0.1", "x-build-id": "vOWcpjJ2dfAhP08lC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/haketa~wongnai-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-haketa-wongnai-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/haketa~wongnai-scraper/runs": { "post": { "operationId": "runs-sync-haketa-wongnai-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/haketa~wongnai-scraper/run-sync": { "post": { "operationId": "run-sync-haketa-wongnai-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "queries": { "title": "Search keywords", "type": "array", "description": "Keywords to search on Wongnai — cuisine, dish, or business type (Thai or English), e.g. cafe, sushi, ก๋วยเตี๋ยว. Optionally narrowed by Region ID below.", "items": { "type": "string" } }, "regionId": { "title": "Region ID (optional)", "type": "integer", "description": "Wongnai region ID to restrict the search (e.g. 9 = Bangkok). Leave empty for all of Thailand." }, "searchUrls": { "title": "Search / listing URLs", "type": "array", "description": "Wongnai listing URLs to scrape directly (e.g. a region, cuisine or search results page).", "items": { "type": "string" } }, "maxPagesPerQuery": { "title": "Max pages per query", "minimum": 1, "maximum": 200, "type": "integer", "description": "How many result pages to paginate per query / URL (about 12 businesses per page).", "default": 10 }, "maxItems": { "title": "Max items", "type": "integer", "description": "Maximum businesses to save. 0 = no limit.", "default": 200 }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 15, "type": "integer", "description": "Maximum parallel page requests.", "default": 5 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Wongnai is behind Cloudflare; a residential proxy is recommended (Thailand residential works best at scale).", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```