# Chope Scraper - Singapore & Asia Restaurant Leads (`scrapesage/chope-scraper`) Actor Scrape Chope restaurants across Singapore and Asia: name, phone, full address, area, cuisine, price band, ratings, geo, menus, photos and reviews. Turn dining venues into B2B leads. Export to JSON, CSV or Excel. - **URL**: https://apify.com/scrapesage/chope-scraper.md - **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community) - **Categories:** Lead generation, Travel, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 1,000 restaurant scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Chope Scraper — Singapore & Asia Restaurant Leads, Ratings & Reservations Extract **complete restaurant data from [Chope](https://www.chope.co)** — Asia's largest restaurant-reservation platform — by market, by cuisine, or by URL. Get every venue's **name, phone, full street address, area/neighbourhood, cuisine, price band, rating, review count, geo-coordinates, menus, photos** and optional **diner reviews**. Every dining venue is a ready-to-use **B2B lead**: a contactable restaurant with phone, address, location and a quality score. No login, no cookies, no browser — this actor reads Chope's own public restaurant pages directly, so the output is first-party and reliable. ### Why this Chope scraper? Most restaurant scrapers return a name and a star rating and call it done. This actor pulls the **full venue record from Chope's directory and profile pages** and ships the **richest dataset in the category** — including the contact fields that turn a listing into a lead: | Data | Typical scrapers | This actor | |---|---|---| | Restaurant name, cuisine, price band | ✅ | ✅ | | Chope rating + number of reviews | partial | ✅ | | **Phone number** | ❌ | ✅ | | **Full street address + postal code** | partial | ✅ | | **Area / neighbourhood** | ❌ | ✅ | | Latitude / longitude | ❌ | ✅ | | **Menus** (Chope-hosted menu files) | ❌ | ✅ when published | | Photo gallery | partial | ✅ | | **Diner reviews** (author, rating, date, full text) | ❌ | ✅ opt-in | | Reservation link | ❌ | ✅ | | Multi-market: Singapore, Malaysia, Indonesia, Thailand | ❌ | ✅ | | Lead score (0–100) per venue | ❌ | ✅ | | One clean dataset, no empty columns | ❌ | ✅ | ### Use cases - **Lead generation** — restaurants are active buyers of POS, reservation, marketing, delivery, payroll, supply and insurance products. Score them by quality and reach (`leadScore`, `phone`, `address`) and export straight to your CRM. - **Market & competitive research** — map a city's dining scene by cuisine, price band, area and rating; benchmark venues and track new openings across Singapore and Southeast Asia. - **Sales territory planning** — pull every Chope restaurant in a market with full addresses and geo-coordinates for route and territory planning. - **Directory & app enrichment** — power restaurant guides, concierge tools and travel apps with standardized records, menus, photos and coordinates. - **Reputation & review intelligence** — collect ratings, review counts and full diner review text to monitor sentiment for a venue or a whole market. ### How to use 1. [Sign up for Apify](https://console.apify.com/sign-up) — the free plan is enough to try this actor. 2. Open the **Chope Scraper**, select one or more **Markets** (e.g. `singapore`), optionally add **Search terms** (e.g. `omakase`), and click **Start**. 3. Watch results stream into the dataset table. 4. **Export** as JSON, CSV, Excel, XML or RSS — or pull results programmatically via the [Apify API](https://docs.apify.com/api/v2). ### Input ```json { "countries": ["singapore"], "searchQueries": ["steakhouse", "omakase"], "maxResults": 100, "includeDetails": true, "includeReviews": false, "cuisines": ["japanese"], "priceTiers": ["3", "4"], "areaFilter": ["orchard"], "minRating": 4, "monitorMode": false } ```` - **countries** — Chope markets to scrape every restaurant in: `singapore`, `kuala-lumpur`, `bali`, `jakarta`, `bandung`, `surabaya`, `bangkok`, `phuket`. Singapore has the deepest coverage. One per row. - **searchQueries** — keep only restaurants whose name or cuisine matches one of these (e.g. `italian`, `omakase`, `Marriott`). Leave empty for every restaurant. - **startUrls** — direct Chope restaurant URLs (`https://www.chope.co/singapore-restaurants/restaurant/10-scotts`). - **maxResults** *(default 100)* — cap on restaurant records for the whole run. - **includeDetails** *(default true)* — open each restaurant's Chope profile for the full lead record (phone, full address, area, geo, price band, rating, menus, photos). One fast extra request per restaurant. Off = a quick, cheap directory pass (name, cuisine, market, profile URL). - **includeReviews** *(default false)* — also extract visible diner reviews (author, star rating, date, full text). No extra request — parsed from the same profile page. - **cuisines / priceTiers / areaFilter / minRating** — keep only venues matching these filters. - **monitorMode** *(default false)* — emit only restaurants not seen in previous runs (see below). ### Output One record per restaurant (`type: "restaurant"`): ```json { "type": "restaurant", "chopeRid": "10scotts2282sg", "slug": "10-scotts", "name": "10|SCOTTS", "profileUrl": "https://www.chope.co/singapore-restaurants/restaurant/10-scotts", "phone": "+6567321234", "address": "10 Scotts Road Lobby Level Grand Hyatt Singapore Singapore (228211)", "area": "Orchard", "city": "Singapore", "region": "Singapore", "postalCode": "228211", "country": "Singapore", "countryCode": "SG", "market": "Singapore", "latitude": 1.3062616, "longitude": 103.8334004, "cuisines": ["Bar", "Mediterranean", "Coffee", "High Tea"], "primaryCuisine": "Bar", "priceTier": 3, "priceRange": "$$$", "rating": 4.1, "reviewCount": 11, "acceptsReservations": true, "reservationUrl": "https://www.chope.co/singapore-restaurants/restaurant/10-scotts", "imageUrl": "https://static.chope.co/uploads/2025/09/Group-Shot-1-1-1757584197.jpg", "photos": ["https://static.chope.co/uploads/..."], "menus": [{ "name": "À La Carte Menu", "url": "https://static.chope.co/uploads/...pdf" }], "leadScore": 70, "scrapedAt": "2026-06-26T12:00:00.000Z" } ``` With **includeReviews** on, each record also carries `reviews` (author, rating, date, text) and `reviewsScraped`. Use the **Restaurants**, **Leads** and **Locations** dataset views to switch between column sets. #### What to expect (field coverage) With `includeDetails` on, across a market you can typically expect: | Field | Coverage | |---|---| | name, market, cuisine, profile URL | ~100% | | **phone**, full address, area, latitude/longitude, price band | ~95–100% | | rating + review count | present for venues with ≥1 diner review (newly-listed venues have none) | | menus, photos | present when the venue publishes them on Chope | | reviews | present (opt-in) for venues that have diner reviews | | restaurant's own website | not published by Chope (it keeps users on-platform) | A blank field means Chope doesn't publish that value for that venue — not that scraping failed. Nothing is dropped, so you always get the richest record available. ### Monitoring mode — only new restaurants Turn on **monitorMode** to make the actor remember which restaurants it has already returned and emit **only restaurants not seen in previous runs** — perfect for tracking new restaurant openings in a market. It stores seen restaurant ids in a named key-value store (`monitorStoreName`, one per tracked market). This **complements [Apify Schedules](https://docs.apify.com/platform/schedules)** and does not conflict with them: Schedules decide *when* the actor runs (e.g. every morning), and monitoring mode decides *what is new* in each run. Use both together to get a daily feed of just-opened restaurants in your target markets. ### Automate & schedule Run this actor on autopilot and pull results into your own stack: - **[Apify API](https://docs.apify.com/api/v2)** — start runs, fetch datasets, and manage schedules over REST. - **[apify-client for JavaScript](https://docs.apify.com/api/client/js/)** and **[apify-client for Python](https://docs.apify.com/api/client/python/)** — official SDKs. - **[Schedules](https://docs.apify.com/platform/schedules)** — run it daily/weekly to monitor new restaurant openings or to refresh ratings and contacts. - **[Webhooks](https://docs.apify.com/platform/integrations/webhooks)** — trigger downstream actions (CRM import, Slack alert, email sequence) the moment a run finishes. ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' }); const run = await client.actor('scrapesage/chope-scraper').call({ countries: ['singapore'], maxResults: 200, includeDetails: true, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(`Got ${items.length} restaurants`); ``` ### Integrate with any app Connect the dataset to 5,000+ apps — no code required: - **[Make](https://docs.apify.com/platform/integrations/make)** — multi-step automation scenarios. - **[Zapier](https://docs.apify.com/platform/integrations/zapier)** — push new restaurant leads straight into your CRM. - **[Slack](https://docs.apify.com/platform/integrations/slack)** — get notified when a monitored market adds new restaurants. - **[Google Drive / Sheets](https://docs.apify.com/platform/integrations/drive)** — auto-export every run to a spreadsheet. - **[Airbyte](https://docs.apify.com/platform/integrations/airbyte)** — pipe results into your data warehouse. - **[GitHub](https://docs.apify.com/platform/integrations/github)** — trigger runs from commits or releases. ### Use with AI assistants (MCP) The output is clean, LLM-ready JSON. Call this actor from Claude, ChatGPT, or any agent framework through the **[Apify MCP server](https://docs.apify.com/platform/integrations/mcp)** — ask your assistant to "list every Chope restaurant in Singapore with phone and area" and let it run the scraper for you. ### More scrapers from scrapesage Build a complete **restaurant & local-business lead-gen stack**: - **[Resy Scraper](https://apify.com/scrapesage/resy-scraper)** — premium US restaurants, ratings, contacts and reservation availability. - **[Burpple Scraper](https://apify.com/scrapesage/burpple-scraper)** — Singapore restaurant, cafe and hawker discovery with reviews. - **[DoorDash Scraper](https://apify.com/scrapesage/doordash-scraper)** — restaurants, full menus and prices by city. - **[UberEats Scraper](https://apify.com/scrapesage/ubereats-scraper)** — restaurants, menus and delivery data. - **[Foodpanda Scraper](https://apify.com/scrapesage/foodpanda-scraper)** — restaurants and menus across Asia. - **[Zomato Scraper](https://apify.com/scrapesage/zomato-scraper)** — restaurants, ratings and reviews. - **[Google Maps Scraper](https://apify.com/scrapesage/google-maps-scraper)** — local businesses with phone, website and reviews. - **[Website Contact Scraper](https://apify.com/scrapesage/website-contact-scraper)** — emails, phones and socials from any website. ### Tips - **Whole-market coverage**: put the market in `countries` (e.g. `singapore`) and leave the filters empty to pull every restaurant in that market. - **Cuisine by market**: combine `countries` with `cuisines` or `searchQueries` for the most precise targeting. - **Cost control**: turn off `includeDetails` for a fast, cheap directory pass (name, cuisine, market, URL); turn it on to add phone, address, area, geo, rating, menus and photos. - **Best leads first**: sort the dataset by `leadScore` to surface contactable, rated, well-located venues at the top. - **Recurring monitoring**: combine [Schedules](https://docs.apify.com/platform/schedules) with `monitorMode` to capture only newly listed restaurants. ### FAQ **How do I scrape every restaurant in a market?** Put the market in `countries` (e.g. `singapore`) and leave the filters empty. The actor reads Chope's full A-Z directory for that market. **Does it need a Chope account or API key?** No. This actor reads Chope's own public restaurant pages — the same data the website shows — with no login, cookie or key. **Where do the phone and address come from?** From the restaurant's own Chope profile page. Phone and full address are present on nearly every venue. **Can I get the restaurant's own website?** Chope keeps users on-platform and does not publish a venue's external website on its profile, so that field is not available. Phone, address and area are. **Can I get individual diner reviews?** Yes — turn on `includeReviews` to capture the visible reviews (author, star rating, date and full text). Chope also reports an aggregate rating and review count, which are always included with details. **Which countries are supported?** Singapore (deepest coverage), Malaysia (Kuala Lumpur), Indonesia (Jakarta, Bali, Bandung, Surabaya) and Thailand (Bangkok, Phuket). **Can I export to Google Sheets, CSV, or Excel?** Yes — one click in the dataset view, or automatically on every run via the [Google Drive integration](https://docs.apify.com/platform/integrations/drive). **How do I monitor new restaurant openings?** Turn on `monitorMode` and create a [Schedule](https://docs.apify.com/platform/schedules); each run returns only restaurants not seen before. Add a [webhook](https://docs.apify.com/platform/integrations/webhooks) to push them into your CRM. **Is scraping Chope legal?** This actor collects publicly available data only. You are responsible for using the data in compliance with applicable laws (e.g. PDPA/GDPR for personal data) and Chope's terms. ### Need help? Open an issue on the actor's **Issues** tab, or visit the [Apify help center](https://help.apify.com/). Feature requests are welcome — this actor is actively maintained. # Actor input Schema ## `countries` (type: `array`): Chope markets to scrape every restaurant in. Pick one or more: singapore, kuala-lumpur, bali, jakarta, bandung, surabaya, bangkok, phuket. Singapore is the flagship market with the deepest coverage. One per row. ## `searchQueries` (type: `array`): Keep only restaurants whose name or cuisine matches one of these (case-insensitive), e.g. "italian", "steakhouse", "omakase", "Marriott". Each term is matched against every restaurant in the selected markets. Leave empty to get every restaurant. One per row. ## `startUrls` (type: `array`): Direct Chope restaurant URLs to scrape, e.g. https://www.chope.co/singapore-restaurants/restaurant/10-scotts . Scraped in addition to any selected markets. One per row. ## `maxResults` (type: `integer`): Cap on restaurant records across the whole run. ## `includeDetails` (type: `boolean`): Open each restaurant's Chope profile for the complete lead record: phone, full street address, area/neighbourhood, geo-coordinates, price band, rating + review count, menus and photos. One fast extra request per restaurant. Off = a quick, cheap directory pass (name, cuisine, market, profile URL only). ## `includeReviews` (type: `boolean`): Also extract the visible diner reviews on each profile (author, star rating, date and full review text). Requires 'Enrich with full details'. No extra request — parsed from the same profile page. ## `maxReviews` (type: `integer`): Upper bound on reviews captured per restaurant when 'Include diner reviews' is on. ## `cuisines` (type: `array`): Keep only restaurants whose cuisine matches one of these (case-insensitive substring, e.g. "japanese", "seafood", "bar"). Leave empty for all cuisines. ## `priceTiers` (type: `array`): Keep only restaurants in these price bands: 1 = $, 2 = $$, 3 = $$$, 4 = $$$$. Requires 'Enrich with full details'. Leave empty for all. ## `areaFilter` (type: `array`): Keep only restaurants in these areas (case-insensitive substring on Chope's area label, e.g. "orchard", "chinatown", "tanjong pagar"). Requires 'Enrich with full details'. Leave empty for all areas. ## `minRating` (type: `integer`): Keep only restaurants with a Chope rating at or above this value (1–5). Requires 'Enrich with full details'. 0 = no filter. ## `deduplicate` (type: `boolean`): Skip a restaurant already emitted earlier in the same run (common when scraping several markets at once). ## `monitorMode` (type: `boolean`): Remember which restaurants were already returned and emit ONLY restaurants not seen in previous runs. Pairs with Apify Schedules to track new restaurant openings in a market over time (it does not conflict with Schedules — Schedules decide when to run, this decides what is new). ## `monitorStoreName` (type: `string`): Named key-value store that holds the 'already seen' restaurant ids for monitoring mode. Use a different name per tracked market to keep histories separate. ## `maxConcurrency` (type: `integer`): Maximum parallel requests. Lower it if you see transient blocks; raise it for speed. ## `proxyConfiguration` (type: `object`): Proxy settings. Chope's public pages are read over standard Apify Proxy with automatic IP rotation; the default works well. Blocked requests retry automatically on a fresh IP. ## Actor input object example ```json { "countries": [ "singapore" ], "maxResults": 100, "includeDetails": true, "includeReviews": false, "maxReviews": 20, "priceTiers": [], "minRating": 0, "deduplicate": true, "monitorMode": false, "monitorStoreName": "chope-scraper-monitor", "maxConcurrency": 10, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): All scraped restaurant records in the default dataset. Switch between the Restaurants, Leads and Locations views to focus the columns. # 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 = { "countries": [ "singapore" ], "maxResults": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesage/chope-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 = { "countries": ["singapore"], "maxResults": 100, } # Run the Actor and wait for it to finish run = client.actor("scrapesage/chope-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 '{ "countries": [ "singapore" ], "maxResults": 100 }' | apify call scrapesage/chope-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesage/chope-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Chope Scraper - Singapore & Asia Restaurant Leads", "description": "Scrape Chope restaurants across Singapore and Asia: name, phone, full address, area, cuisine, price band, ratings, geo, menus, photos and reviews. Turn dining venues into B2B leads. Export to JSON, CSV or Excel.", "version": "0.1", "x-build-id": "1BrKwRuG7hEhZB5r2" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesage~chope-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesage-chope-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/scrapesage~chope-scraper/runs": { "post": { "operationId": "runs-sync-scrapesage-chope-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/scrapesage~chope-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesage-chope-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": { "countries": { "title": "Markets (countries / cities)", "type": "array", "description": "Chope markets to scrape every restaurant in. Pick one or more: singapore, kuala-lumpur, bali, jakarta, bandung, surabaya, bangkok, phuket. Singapore is the flagship market with the deepest coverage. One per row.", "items": { "type": "string", "enum": [ "singapore", "kuala-lumpur", "bali", "jakarta", "bandung", "surabaya", "bangkok", "phuket" ], "enumTitles": [ "Singapore", "Kuala Lumpur (Malaysia)", "Bali (Indonesia)", "Jakarta (Indonesia)", "Bandung (Indonesia)", "Surabaya (Indonesia)", "Bangkok (Thailand)", "Phuket (Thailand)" ] }, "default": [ "singapore" ] }, "searchQueries": { "title": "Search terms (optional)", "type": "array", "description": "Keep only restaurants whose name or cuisine matches one of these (case-insensitive), e.g. \"italian\", \"steakhouse\", \"omakase\", \"Marriott\". Each term is matched against every restaurant in the selected markets. Leave empty to get every restaurant. One per row.", "items": { "type": "string" } }, "startUrls": { "title": "Chope restaurant URLs (optional)", "type": "array", "description": "Direct Chope restaurant URLs to scrape, e.g. https://www.chope.co/singapore-restaurants/restaurant/10-scotts . Scraped in addition to any selected markets. One per row.", "items": { "type": "string" } }, "maxResults": { "title": "Max results (restaurants)", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Cap on restaurant records across the whole run.", "default": 100 }, "includeDetails": { "title": "Enrich with full details (phone, address, geo, rating, menus, photos)", "type": "boolean", "description": "Open each restaurant's Chope profile for the complete lead record: phone, full street address, area/neighbourhood, geo-coordinates, price band, rating + review count, menus and photos. One fast extra request per restaurant. Off = a quick, cheap directory pass (name, cuisine, market, profile URL only).", "default": true }, "includeReviews": { "title": "Include diner reviews", "type": "boolean", "description": "Also extract the visible diner reviews on each profile (author, star rating, date and full review text). Requires 'Enrich with full details'. No extra request — parsed from the same profile page.", "default": false }, "maxReviews": { "title": "Max reviews per restaurant", "minimum": 1, "maximum": 100, "type": "integer", "description": "Upper bound on reviews captured per restaurant when 'Include diner reviews' is on.", "default": 20 }, "cuisines": { "title": "Cuisine filter (optional)", "type": "array", "description": "Keep only restaurants whose cuisine matches one of these (case-insensitive substring, e.g. \"japanese\", \"seafood\", \"bar\"). Leave empty for all cuisines.", "items": { "type": "string" } }, "priceTiers": { "title": "Price bands", "type": "array", "description": "Keep only restaurants in these price bands: 1 = $, 2 = $$, 3 = $$$, 4 = $$$$. Requires 'Enrich with full details'. Leave empty for all.", "items": { "type": "string", "enum": [ "1", "2", "3", "4" ], "enumTitles": [ "$", "$$", "$$$", "$$$$" ] }, "default": [] }, "areaFilter": { "title": "Area / neighbourhood filter (optional)", "type": "array", "description": "Keep only restaurants in these areas (case-insensitive substring on Chope's area label, e.g. \"orchard\", \"chinatown\", \"tanjong pagar\"). Requires 'Enrich with full details'. Leave empty for all areas.", "items": { "type": "string" } }, "minRating": { "title": "Minimum rating", "minimum": 0, "maximum": 5, "type": "integer", "description": "Keep only restaurants with a Chope rating at or above this value (1–5). Requires 'Enrich with full details'. 0 = no filter.", "default": 0 }, "deduplicate": { "title": "Deduplicate restaurants", "type": "boolean", "description": "Skip a restaurant already emitted earlier in the same run (common when scraping several markets at once).", "default": true }, "monitorMode": { "title": "Monitoring mode — only new restaurants", "type": "boolean", "description": "Remember which restaurants were already returned and emit ONLY restaurants not seen in previous runs. Pairs with Apify Schedules to track new restaurant openings in a market over time (it does not conflict with Schedules — Schedules decide when to run, this decides what is new).", "default": false }, "monitorStoreName": { "title": "Monitor store name", "type": "string", "description": "Named key-value store that holds the 'already seen' restaurant ids for monitoring mode. Use a different name per tracked market to keep histories separate.", "default": "chope-scraper-monitor" }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum parallel requests. Lower it if you see transient blocks; raise it for speed.", "default": 10 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings. Chope's public pages are read over standard Apify Proxy with automatic IP rotation; the default works well. Blocked requests retry automatically on a fresh IP.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```