# DoorDash Scraper - Restaurants, Menus & Prices (`scrapesage/doordash-scraper`) Actor Scrape DoorDash restaurants & menus by city: name, full address, cuisine, price tier, menu items with prices, rating, reviews and geo. Optional full menu & review enrichment and monitoring. No login or API key. - **URL**: https://apify.com/scrapesage/doordash-scraper.md - **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community) - **Categories:** E-commerce, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 ## DoorDash Scraper — Restaurants, Menus, Prices & Reviews Scrape **[DoorDash](https://www.doordash.com)** — the #1 US food-delivery marketplace — into clean, structured data. Pull every restaurant in a city with **name, full street address, cuisine, price tier, logo, and a menu preview with prices**. Turn on store details for the **complete menu (every section, item & price), star rating, review count, customer reviews and geo coordinates**. Built-in **monitor mode** returns only new restaurants between runs. No API key, no login, no browser automation — fast HTTP straight to the source, with a **0–100 quality score** on every restaurant. ### Why this DoorDash scraper? Most food-delivery scrapers give you a list of names, then break or stop at the listing card. This actor reads DoorDash's own structured (JSON-LD) data and ships the **full record** — including the data that powers menu-pricing and competitive-intelligence use cases: | Data | Typical scrapers | This actor | |---|---|---| | Restaurant name + store URL | ✅ | ✅ | | **Full street address** + city/state | partial | ✅ | | Cuisine(s) + price tier ($–$$$$) | partial | ✅ | | Logo / cover image | ❌ | ✅ | | **Menu preview** (popular items + prices) | ❌ | ✅ | | **Full menu** — every section, item, description & price *(store details)* | ❌ | ✅ | | **Star rating + review count** *(store details)* | ❌ | ✅ | | **Customer reviews** (author, stars, text) *(store details)* | ❌ | ✅ | | **Geo** (lat/long) *(store details)* | ❌ | ✅ | | Filter by city, cuisine, price, rating | partial | ✅ | | **Monitor mode** — only new restaurants | ❌ | ✅ | | Quality score (0–100) | ❌ | ✅ | ### Who uses DoorDash data? - **Restaurant-tech, POS, online-ordering & delivery SaaS** — build prospect lists of restaurants by city and cuisine, with address and menu. - **Food brands, distributors & suppliers** — find and segment restaurants that could carry your products. - **Menu & price intelligence** — benchmark competitor menus, item pricing and price tiers across a market. - **Ghost kitchens & virtual brands** — map the competitive landscape and white space by cuisine. - **Market researchers & analysts** — restaurant density, cuisine mix, ratings and pricing trends by city. - **Investors & real-estate teams** — gauge food-service supply and demand in a trade area. ### 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 **DoorDash Scraper**, enter one or more **cities** ("Austin, TX"), optionally add **cuisines**, 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 { "cities": ["Austin, TX", "New York, NY"], "cuisines": ["pizza", "mexican"], "includeStoreDetails": true, "includeReviews": true, "maxReviewsPerStore": 10, "priceTiers": ["1", "2"], "maxResults": 100 } ```` | Field | Type | Description | |---|---|---| | `cities` | array | Cities to scrape, as "City, ST" (e.g. "Austin, TX"). | | `cuisines` | array | Optional cuisine filters — each is scraped separately per city (~50 restaurants each) to expand coverage. | | `startUrls` | array | DoorDash city pages **or** single `/store//` URLs (auto-routed; store URLs always pull full details). | | `maxResults` | integer | Cap on restaurant records (default 100). | | `includeStoreDetails` | boolean | Open each store page for the full menu, rating, reviews and geo. | | `includeReviews` | boolean | Include customer reviews when store details are on. | | `maxReviewsPerStore` | integer | Max reviews per restaurant. | | `cuisineFilter` | array | Output filter: keep only matching cuisines. | | `priceTiers` | array | Output filter: 1 = $, 2 = $$, 3 = $$$, 4 = $$$$. | | `minRating` / `minReviews` | integer | Output filters (require store details). | | `withMenuOnly` | boolean | Only restaurants that have menu items. | | `monitorMode` | boolean | Emit only restaurants not seen in previous runs. | | `proxyConfiguration` | object | Defaults to Apify **Residential, US** (recommended). | ### Output Each restaurant is one row tagged `type: "restaurant"`: ```json { "type": "restaurant", "storeId": "62014", "name": "The Cheesecake Factory", "url": "https://www.doordash.com/store/the-cheesecake-factory-austin-62014/", "cuisines": ["American", "Dessert"], "primaryCuisine": "American", "priceRange": "$$", "priceTier": 2, "street": "10000 Research Boulevard", "city": "Austin", "state": "TX", "rating": 4.5, "reviewCount": 50, "latitude": 30.39098, "longitude": -97.747569, "menu": [ { "section": "Most Ordered", "items": [ { "name": "Whole Wheat Loaf", "price": 3.5, "priceText": "$3.50" } ] } ], "menuSectionCount": 9, "menuItemCount": 91, "reviews": [ { "author": "Miguel R", "rating": 5, "body": "...delicious!" } ], "leadScore": 88, "scrapedAt": "2026-06-24T01:00:00.000Z" } ``` Without store details, each row carries the city-feed data: `name`, `street`/`city`/`state`, `cuisines`, `priceRange`, `imageUrl`, and a `menuPreview` (popular items with prices). ### Monitor mode Turn on **`monitorMode`** to remember every restaurant (`storeId`) across runs and emit **only restaurants not seen before** — perfect for tracking new restaurant openings in a market. State lives in a named key-value store (`monitorStoreName`, default `doordash-scraper-monitor`); use a different name per tracked market. This is **orthogonal to [Apify Schedules](https://docs.apify.com/platform/schedules)** — the schedule decides *when* to run, monitor mode decides *what's new*. ### Automate & schedule - **[Apify API](https://docs.apify.com/api/v2)** — start runs, fetch datasets, 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 track new restaurants and menu/price changes in a market. - **[Webhooks](https://docs.apify.com/platform/integrations/webhooks)** — trigger downstream actions (CRM import, Slack alert, price-monitoring job) when a run finishes. ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' }); const run = await client.actor('scrapesage/doordash-scraper').call({ cities: ['Austin, TX'], includeStoreDetails: true, maxResults: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### 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 city has 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 the top-rated pizza restaurants in Austin with their menu prices" and let it run this scraper for you. ### More scrapers from scrapesage - **[UberEats Scraper](https://apify.com/scrapesage/ubereats-scraper)** — restaurants, menus and prices from Uber Eats. - **[Wolt Scraper](https://apify.com/scrapesage/wolt-scraper)** — restaurant and store data from Wolt. - **[Zomato Scraper](https://apify.com/scrapesage/zomato-scraper)** — restaurant listings, menus and reviews. - **[Just Eat Scraper](https://apify.com/scrapesage/just-eat-scraper)** — European food-delivery restaurant data. - **[Talabat Scraper](https://apify.com/scrapesage/talabat-scraper)** — MENA food-delivery restaurants and menus. - **[US Restaurant Inspection Scraper](https://apify.com/scrapesage/us-restaurant-inspection-scraper)** — health-inspection scores and violations. - **[Google Maps Scraper](https://apify.com/scrapesage/google-maps-scraper)** — local business leads, emails, phones and reviews. - **[Website Contact Scraper](https://apify.com/scrapesage/website-contact-scraper)** — emails, phones and socials from any website. ### Tips - **Wider coverage per city**: add several `cuisines` (pizza, mexican, sushi, burgers…) — each pulls ~50 more restaurants for the same city. - **Cheapest runs**: leave `includeStoreDetails` off — the city feed already gives name, address, cuisine, price tier and a menu preview. - **Menu/price benchmarking**: turn on `includeStoreDetails` to capture every menu item and price across a market. - **Track new openings**: combine [Schedules](https://docs.apify.com/platform/schedules) with `monitorMode`. ### FAQ **Do I need a DoorDash API key or login?** No. This actor reads the public city and store pages — no key, no login, no browser. **Can I target a specific city?** Yes — the city is set by the URL, so results are reliably localized to the city you enter (unlike IP-based scrapers). **Does it get restaurant phone numbers?** DoorDash routes contact through its platform and does not publish restaurant phone numbers, so phone is not available. You get the full street address, which pairs well with the [Google Maps Scraper](https://apify.com/scrapesage/google-maps-scraper) for phone/email enrichment. **Why Residential proxy?** DoorDash serves clean pages over US residential IPs but challenges datacenter IPs. The default is Apify Residential (US); blocked requests retry automatically on a fresh IP. **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). *** *Not affiliated with or endorsed by DoorDash. Use responsibly and in accordance with applicable laws and terms. Scrapes only publicly available data.* # Actor input Schema ## `cities` (type: `array`): Cities to scrape restaurants in, as "City, ST" — e.g. "Austin, TX", "New York, NY", "Los Angeles, CA". One per row. ## `cuisines` (type: `array`): Optional cuisine filters to expand coverage per city — e.g. pizza, mexican, chinese, sushi, burgers, thai, indian, vegan. Each cuisine is scraped separately per city (~50 restaurants each). Leave empty for the general restaurant list. ## `startUrls` (type: `array`): DoorDash URLs to scrape directly: city pages (https://www.doordash.com/food-delivery/--restaurants/) or single restaurant pages (https://www.doordash.com/store/-/). Store URLs always pull the full menu, rating and reviews. One per row. ## `maxResults` (type: `integer`): Cap on restaurant records across the whole run. ## `includeStoreDetails` (type: `boolean`): Open each restaurant's store page for the complete menu (every section, item & price), star rating, review count, customer reviews and geo coordinates. One extra request per restaurant. Off = a fast, cheap run with the city-feed data (name, address, cuisine, price tier, logo and a popular-items menu preview). ## `includeReviews` (type: `boolean`): When store details are on, also include individual customer reviews (author, star rating, text). ## `maxReviewsPerStore` (type: `integer`): Maximum customer reviews to keep per restaurant (DoorDash exposes a handful of recent reviews). ## `cuisineFilter` (type: `array`): Keep only restaurants whose cuisine matches one of these (case-insensitive substring, e.g. "pizza", "mexican"). Leave empty for all. ## `priceTiers` (type: `array`): Keep only restaurants in these price tiers: 1 = $, 2 = $$, 3 = $$$, 4 = $$$$. Leave empty for all. ## `minRating` (type: `integer`): Keep only restaurants with a star rating at or above this value (1–5). Requires store details on. 0 = no filter. ## `minReviews` (type: `integer`): Keep only restaurants with at least this many reviews. Requires store details on. 0 = no filter. ## `withMenuOnly` (type: `boolean`): Output only restaurants that have menu items. ## `deduplicateStores` (type: `boolean`): Skip a restaurant already emitted earlier in the same run (common when scraping a city across multiple cuisines). ## `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. ## `monitorStoreName` (type: `string`): Named key-value store that holds the 'already seen' store ids for monitoring mode. Use a different name per tracked market to keep histories separate. ## `maxConcurrency` (type: `integer`): Maximum parallel requests. Lower it for very large runs if you see transient blocks; raise it for speed. ## `proxyConfiguration` (type: `object`): Proxy settings. DoorDash serves clean pages over US residential IPs but challenges datacenter IPs, so US Residential is the default and recommended setting. Blocked requests retry automatically on a fresh IP. ## Actor input object example ```json { "cities": [ "Austin, TX" ], "maxResults": 100, "includeStoreDetails": false, "includeReviews": true, "maxReviewsPerStore": 10, "priceTiers": [], "minRating": 0, "minReviews": 0, "withMenuOnly": false, "deduplicateStores": true, "monitorMode": false, "monitorStoreName": "doordash-scraper-monitor", "maxConcurrency": 8, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "countryCode": "US" } } ``` # Actor output Schema ## `results` (type: `string`): All scraped restaurant records in the default dataset — name, address, cuisine, price tier, menu (preview or full), rating, reviews and geo. # 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 = { "cities": [ "Austin, TX" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesage/doordash-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 = { "cities": ["Austin, TX"] } # Run the Actor and wait for it to finish run = client.actor("scrapesage/doordash-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 '{ "cities": [ "Austin, TX" ] }' | apify call scrapesage/doordash-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesage/doordash-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "DoorDash Scraper - Restaurants, Menus & Prices", "description": "Scrape DoorDash restaurants & menus by city: name, full address, cuisine, price tier, menu items with prices, rating, reviews and geo. Optional full menu & review enrichment and monitoring. No login or API key.", "version": "0.1", "x-build-id": "fDxnaS7nSPwizZNki" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesage~doordash-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesage-doordash-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~doordash-scraper/runs": { "post": { "operationId": "runs-sync-scrapesage-doordash-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~doordash-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesage-doordash-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": { "cities": { "title": "Cities", "type": "array", "description": "Cities to scrape restaurants in, as \"City, ST\" — e.g. \"Austin, TX\", \"New York, NY\", \"Los Angeles, CA\". One per row.", "items": { "type": "string" } }, "cuisines": { "title": "Cuisines (optional)", "type": "array", "description": "Optional cuisine filters to expand coverage per city — e.g. pizza, mexican, chinese, sushi, burgers, thai, indian, vegan. Each cuisine is scraped separately per city (~50 restaurants each). Leave empty for the general restaurant list.", "items": { "type": "string" } }, "startUrls": { "title": "Start URLs (city or store)", "type": "array", "description": "DoorDash URLs to scrape directly: city pages (https://www.doordash.com/food-delivery/--restaurants/) or single restaurant pages (https://www.doordash.com/store/-/). Store URLs always pull the full menu, rating and reviews. 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 }, "includeStoreDetails": { "title": "Include full store details (full menu, rating, reviews, geo)", "type": "boolean", "description": "Open each restaurant's store page for the complete menu (every section, item & price), star rating, review count, customer reviews and geo coordinates. One extra request per restaurant. Off = a fast, cheap run with the city-feed data (name, address, cuisine, price tier, logo and a popular-items menu preview).", "default": false }, "includeReviews": { "title": "Include customer reviews (with store details)", "type": "boolean", "description": "When store details are on, also include individual customer reviews (author, star rating, text).", "default": true }, "maxReviewsPerStore": { "title": "Max reviews per restaurant", "minimum": 0, "maximum": 50, "type": "integer", "description": "Maximum customer reviews to keep per restaurant (DoorDash exposes a handful of recent reviews).", "default": 10 }, "cuisineFilter": { "title": "Cuisine filter (output)", "type": "array", "description": "Keep only restaurants whose cuisine matches one of these (case-insensitive substring, e.g. \"pizza\", \"mexican\"). Leave empty for all.", "items": { "type": "string" } }, "priceTiers": { "title": "Price tiers", "type": "array", "description": "Keep only restaurants in these price tiers: 1 = $, 2 = $$, 3 = $$$, 4 = $$$$. Leave empty for all.", "items": { "type": "string", "enum": [ "1", "2", "3", "4" ], "enumTitles": [ "$", "$$", "$$$", "$$$$" ] }, "default": [] }, "minRating": { "title": "Minimum rating (requires store details)", "minimum": 0, "maximum": 5, "type": "integer", "description": "Keep only restaurants with a star rating at or above this value (1–5). Requires store details on. 0 = no filter.", "default": 0 }, "minReviews": { "title": "Minimum reviews (requires store details)", "minimum": 0, "maximum": 100000, "type": "integer", "description": "Keep only restaurants with at least this many reviews. Requires store details on. 0 = no filter.", "default": 0 }, "withMenuOnly": { "title": "Only restaurants with a menu", "type": "boolean", "description": "Output only restaurants that have menu items.", "default": false }, "deduplicateStores": { "title": "Deduplicate restaurants", "type": "boolean", "description": "Skip a restaurant already emitted earlier in the same run (common when scraping a city across multiple cuisines).", "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.", "default": false }, "monitorStoreName": { "title": "Monitor store name", "type": "string", "description": "Named key-value store that holds the 'already seen' store ids for monitoring mode. Use a different name per tracked market to keep histories separate.", "default": "doordash-scraper-monitor" }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum parallel requests. Lower it for very large runs if you see transient blocks; raise it for speed.", "default": 8 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings. DoorDash serves clean pages over US residential IPs but challenges datacenter IPs, so US Residential is the default and recommended setting. Blocked requests retry automatically on a fresh IP.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "countryCode": "US" } } } }, "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 } } } } } } } } } } ```