# Zillow Scraper Pro (`tonyaka_educational_watermill/zillow-scraper-pro`) Actor Scrape Zillow property listings and deep details by ZIP code or URL. Returns address, price, beds, baths, sqft, Zestimate, price history, tax records, school ratings, and agent info. Anti-bot resilient via residential proxies and fingerprint spoofing. Supports for\_sale, for\_rent, and recently\_sold. - **URL**: https://apify.com/tonyaka\_educational\_watermill/zillow-scraper-pro.md - **Developed by:** [Tony](https://apify.com/tonyaka_educational_watermill) (community) - **Categories:** Lead generation, Real estate, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 search-page-processeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Zillow Scraper Pro — Zillow API with Built-In MCP Server for AI Agents **The Zillow scraper built for AI agents, real estate investors, and data teams.** Extract Zillow property listings, Zestimates, price history, tax records, school ratings, and agent contact info from any ZIP code, city, or Zillow search URL — with a built-in [MCP server](https://modelcontextprotocol.io/) that plugs straight into Claude, GPT, Cursor, and other LLM agents. Unlike every other Zillow scraper on Apify, this one is **designed to be called by AI** — not just by humans. It ships with a full JSON Schema, a two-tier pricing model (fast summary vs. deep detail), and anti-bot resilience tuned for Zillow's Imperva / PerimeterX WAF. > **Use cases:** real estate lead generation, MLS-style listing monitoring, Zestimate data extraction, property investor comp analysis, rental market research, AI-powered real estate agents, bulk Zillow data export, house price history tracking. --- ### Why Zillow Scraper Pro | Feature | Zillow Scraper Pro | Typical Apify Zillow Scrapers | |---|---|---| | **MCP server built in** | ✅ Native Claude / LLM integration | ❌ | | **Two-tier pricing** | ✅ Fast summary + deep detail | ❌ One price fits all | | **Zestimate transparency** | ✅ `zestimateStatus` + comp-based fallback for new construction | ❌ Null zestimates with no context | | **Anti-bot resilience** | ✅ TLS fingerprinting + pre-warmed session pool | ⚠️ Breaks on every Zillow update | | **Rent Zestimate** | ✅ Included | ⚠️ Sometimes | | **School ratings + walk score** | ✅ Included in detail mode | ⚠️ Usually extra cost | | **ZIP code, URL, and city search** | ✅ All three | ⚠️ Usually one | | **For Sale / For Rent / Recently Sold** | ✅ All three | ⚠️ Usually for-sale only | --- ### What it scrapes from Zillow **Search inputs:** - Scrape Zillow by **ZIP code** — e.g. `["10001", "90210", "78701"]` - Scrape Zillow by **city or neighborhood** URL — e.g. `https://www.zillow.com/austin-tx/` - Scrape Zillow by **custom filtered search URL** — price, beds, sqft, property type, etc. - Listing types: `for_sale`, `for_rent`, `recently_sold` **Data extracted per property (detail mode):** - **Pricing:** list price, Zestimate, Rent Zestimate, price/sqft, price history, tax assessed value - **Property facts:** beds, baths, sqft, lot size, year built, property type, stories, HOA fee - **Location:** full address, ZIP code, latitude, longitude - **Real estate context:** days on market, listing status, MLS name, MLS ID - **Agent & broker:** agent name, phone, broker name, broker phone - **School data:** school name, rating (GreatSchools), grades served, distance, public/private - **Walkability:** Walk Score, Transit Score, Bike Score - **Tax history:** year-by-year tax paid and assessed value - **Rich media:** hi-res photo URLs, floor plans where available - **Property description:** full listing description text - **resoFacts:** appliances, flooring, cooling, heating, parking, and every structured field Zillow publishes --- ### Built for AI agents (MCP-native) Most Zillow scrapers output JSON and stop there. Zillow Scraper Pro publishes a full **Model Context Protocol** schema so LLM agents (Claude, GPT, Cursor, LangChain, LlamaIndex) can reason about the data before calling it. #### Three ways to use with AI **1. Via the Apify MCP server (no code)** ```` Server URL: https://mcp.apify.com/mcp ```` Add to Claude Desktop, then ask naturally: *"Find 3-bed houses under $500K in Austin listed in the last 30 days."* Claude calls the actor, filters the results, and answers. No code, no SDK. **2. Via the built-in local MCP server** ```bash node src/mcp-server.js ```` Runs a standards-compliant MCP server on your machine, exposing `search_zillow`, `get_property_details`, and `bulk_scrape_zip` as callable tools. Connect any MCP client. **3. Via the Apify API** Same actor, standard REST/JS client. Use when you want a traditional scraper API without the AI layer. #### Agent-friendly output fields Every record includes three fields specifically for agent reasoning: | Field | Purpose | |---|---| | `dataDepth` | `summary` | `detail` | `summary_fallback` — tells the agent whether to re-request with `scrapeDetails: true` | | `zestimateStatus` | `available` | `new_construction` | `not_published` — explains *why* a Zestimate is null instead of hiding it | | `estimatedValuePPSF` | Comp-based valuation fallback computed from the median price-per-sqft in the same search. Useful when Zillow won't publish a Zestimate (new construction, coops, luxury). | | `scrapedAt` | ISO 8601 — lets the agent assess data freshness | | `source` | Always `"zillow"` — for multi-source pipelines | *** ### Anti-bot: why this one doesn't break Zillow runs **Imperva / PerimeterX** with TLS fingerprinting, JavaScript canvas/WebGL fingerprinting, `navigator.webdriver` detection, and behavioral heuristics. Most Zillow scrapers on the market break within hours of a Zillow deploy. This actor uses: 1. **HTTP-only stealth with Chrome TLS fingerprinting** (`got-scraping`) — sub-second requests, no browser overhead, no JavaScript runtime to fingerprint 2. **Residential proxy routing** via Apify's residential pool — datacenter IPs are blocked at the edge 3. **Pre-warmed session pool** with session affinity — survives rate-limit bursts that kill fresh-session scrapers 4. **`__NEXT_DATA__` + `gdpClientCache` extraction** — pulls data from Zillow's embedded JSON payloads, so layout changes don't break selectors 5. **Auto-retry on PerimeterX challenges** — detects challenge pages and retries with a fresh residential IP (up to 4 retries, with exponential backoff) 6. **Configurable human-like delays** — 3–8 second jitter between requests (tunable per run) The result: sub-minute runs at 20-property scale, and weeks between block incidents instead of hours. *** ### Input | Field | Type | Default | Description | |---|---|---|---| | `zipCodes` | string\[] | `[]` | ZIP codes to search — e.g. `["10001", "90210"]` | | `startUrls` | URL\[] | `[]` | Any Zillow search or listing URL | | `listingType` | string | `for_sale` | `for_sale`, `for_rent`, or `recently_sold` | | `maxListings` | integer | `100` | Max properties to collect per run | | `scrapeDetails` | boolean | `true` | Visit each listing for deep data (priced higher per property) | | `maxConcurrency` | integer | `2` | Parallel requests — keep 1–3 for Zillow safety | | `requestDelayMs` | integer | `4000` | Delay between requests (3000–8000ms recommended) | | `proxyConfig` | object | RESIDENTIAL | Apify proxy settings — datacenter proxies will fail | **Minimum input:** one `zipCode` or `startUrl`. *** ### Output schema Each dataset item is one property. `dataDepth` tells you which tier the item came from. #### Summary fields (all runs, `dataDepth: "summary"`) ```json { "zpid": "12345678", "url": "https://www.zillow.com/homedetails/...", "address": "123 Main St, New York, NY 10001", "price": 850000, "beds": 3, "baths": 2, "sqft": 1400, "propertyType": "condo", "listingType": "FOR_SALE", "listingStatus": "For Sale", "daysOnMarket": 12, "zestimate": 860000, "zestimateStatus": "available", "rentZestimate": 4200, "estimatedValuePPSF": null, "latitude": 40.7128, "longitude": -74.006, "yearBuilt": 1985, "imgSrc": "https://...", "scrapedAt": "2026-04-15T12:00:00.000Z", "source": "zillow", "dataDepth": "summary" } ``` #### Detail fields (`scrapeDetails: true`, `dataDepth: "detail"`) All summary fields plus: ```json { "lotSizeSqft": 2500, "stories": 3, "description": "Bright corner unit...", "monthlyHoaFee": 450, "taxAssessedValue": 720000, "pricePerSqft": 607, "priceHistory": [ { "date": "2023-03-15", "price": 795000, "event": "Listed for sale", "pricePerSqft": 568 } ], "taxHistory": [ { "year": 2023, "taxPaid": 9800, "value": 700000 } ], "schools": [ { "name": "PS 1 Tottenville", "rating": 7, "grades": "K-5", "distance": 0.3, "type": "public" } ], "agent": { "agentName": "Jane Smith", "agentPhoneNumber": "212-555-0100", "brokerName": "Compass", "mlsName": "REBNY", "mlsId": "REBNY-123456" }, "walkScore": 98, "transitScore": 100, "bikeScore": 85, "resoFacts": { "appliances": ["Dishwasher", "Refrigerator"], "flooring": ["Hardwood"], "heating": ["Forced air"], "cooling": ["Central"] }, "photos": ["https://..."], "dataDepth": "detail" } ``` *** ### Pricing — two-tier pay-per-event This actor uses **pay-per-event (PPE)** pricing. You pay only for what you actually use, and you get two distinct tiers so you never overpay for depth you didn't need. | Event | Price | When you pay | Use when | |---|---|---|---| | `apify-actor-start` | **$0.00005** (first 5 seconds waived) | Once per run — Apify platform event, effectively free for almost all runs | Automatic | | `search-page-processed` | **$0.002** | Per ZIP / search URL handled | Always — covers the anti-bot cost of the search endpoint | | `property-summary-returned` | **$0.003** | Per property with ~20 core fields (address, price, **Zestimate**, beds, baths, sqft, yearBuilt, agent, photos) | **Monitoring, alerting, bulk exports** — when you need breadth over depth | | `property-detail-enriched` | **$0.015** | Per property with 40+ fields (full description, resoFacts, HOA, tax, walk/transit scores, price history, schools) | **Comp analysis, lead generation, due diligence** — when you need depth over breadth | **Example costs:** - Daily monitoring sweep of 200 ZIP codes × 50 properties summary = $30.40 / day → **$912 / month** - Weekly deep comp analysis of 100 properties with full detail = $1.50 / week → **$6 / month** - One-time market report: 500 properties detail-mode = $7.50 Compare to single-tier competitors: typical detail-scrapers charge $0.003–$0.005 per property regardless of depth, so you pay the same for shallow fields as for the full resoFacts + schools + tax stack. With Zillow Scraper Pro you only pay the premium when you actually need the premium data. *** ### Usage examples #### Scrape all Zillow for-sale listings in a ZIP code ```json { "zipCodes": ["10001"], "listingType": "for_sale", "maxListings": 200, "scrapeDetails": true } ``` #### Monitor a city in summary mode (cheapest possible) ```json { "startUrls": [{ "url": "https://www.zillow.com/new-york-ny/homes-for-sale/" }], "maxListings": 500, "scrapeDetails": false } ``` #### Nightly rental-market sweep across multiple ZIPs ```json { "zipCodes": ["90210", "90036", "90024"], "listingType": "for_rent", "maxListings": 300, "scrapeDetails": true, "requestDelayMs": 5000 } ``` #### Recently sold comps for an investor's target ZIP ```json { "zipCodes": ["78701"], "listingType": "recently_sold", "maxListings": 100, "scrapeDetails": true } ``` *** ### Deployment #### Prerequisites - [Apify CLI](https://docs.apify.com/cli): `npm install -g apify-cli` - Apify account with residential proxy access #### Steps ```bash cd zillow-scraper-pro npm install apify login apify run ## local test apify push ## deploy to Apify Store ``` #### Local testing input Create `.actor/input.json`: ```json { "zipCodes": ["10001"], "listingType": "for_sale", "maxListings": 10, "scrapeDetails": true, "requestDelayMs": 3000 } ``` *** ### Troubleshooting **Empty results?** Zillow may have shipped a change. Patches ship within 48 hours of a confirmed break — file an Issue on the actor page. **Getting blocked?** Confirm `proxyConfig` is set to `RESIDENTIAL`. Datacenter IPs are blocked at Zillow's edge immediately. **Null `zestimate`?** Check `zestimateStatus`. It will be one of: - `available` — Zillow published a value (in the `zestimate` field) - `new_construction` — property built in the last 5 years; Zillow doesn't publish Zestimates for these. Use `estimatedValuePPSF` as a comp-based fallback. - `not_published` — coops, mixed-use, or luxury listings where Zillow itself declines to publish. Fallback also available when sqft is known. **Slow runs?** `requestDelayMs` of 3000–8000ms is the safe range for Zillow. Lowering below 2000ms significantly increases block rates. **Running into the $5 Apify free-tier limit?** Start with `scrapeDetails: false` and a small `maxListings` to explore the schema. Detail mode is designed for production use where the depth justifies the per-property price. *** ### Frequently asked questions **Q: How is this different from `maxcopell/zillow-scraper`?** A: That scraper is search-only at $0.002/property; no detail pages, no MCP, no Zestimate transparency. Zillow Scraper Pro gives you both tiers in one actor plus AI-agent integration. **Q: Does this work for Zillow rentals?** A: Yes. Set `listingType: "for_rent"`. Both Zestimate and Rent Zestimate are extracted in detail mode. **Q: Can it handle recently sold properties?** A: Yes. Set `listingType: "recently_sold"` to pull sold comps for investor analysis. **Q: Does this bypass Zillow's login wall?** A: This actor only scrapes publicly accessible Zillow pages. It does not access logged-in-only data, scrape personal information beyond what Zillow publishes, or violate authenticated-only features. **Q: Is scraping Zillow legal?** A: Web scraping public pages is generally permitted under the hiQ v. LinkedIn precedent for publicly available data, but you are responsible for complying with Zillow's Terms of Service and applicable laws in your jurisdiction. This actor is provided for legitimate research, due diligence, and AI tool-use scenarios. **Q: Can I use this commercially?** A: Yes. Output is yours; usage is subject to Apify's terms and Zillow's ToS. The actor source is Apache-2.0 licensed. *** ### Changelog **v2.9 (April 2026)** — Added `zestimateStatus` transparency field, `estimatedValuePPSF` comp-based fallback, `rentZestimate` extraction, tiered pay-per-event pricing, built-in MCP server. *** ### License Apache 2.0 *** *Keywords: Zillow scraper, Zillow API, Zillow data extraction, Zestimate API, real estate scraper, real estate data API, property data extraction, MLS scraper, home listings scraper, Zillow for sale, Zillow for rent, Zillow recently sold, bulk Zillow export, ZIP code property search, Zillow scraper with MCP, Claude real estate agent, AI real estate tool, property scraper with Zestimate, rental listings scraper, house price history API, real estate lead generation.* # Actor input Schema ## `zipCodes` (type: `array`): List of ZIP codes to search. E.g. \["10001", "90210"]. Uses Zillow's search API for fast results. ## `startUrls` (type: `array`): Zillow search or listing URLs to scrape directly. Accepts any Zillow search page URL or individual property detail URLs. ## `listingType` (type: `string`): Type of listings to scrape. ## `maxListings` (type: `integer`): Maximum number of property listings to collect. ## `scrapeDetails` (type: `boolean`): Fetch each listing's detail page for rich data (price history, tax records, schools, agent info). Slightly slower but yields much richer data. ## `proxyConfig` (type: `object`): Apify proxy configuration. Residential proxies are strongly recommended. ## Actor input object example ```json { "zipCodes": [ "10001", "90210" ], "startUrls": [ { "url": "https://www.zillow.com/new-york-ny/" } ], "listingType": "for_sale", "maxListings": 100, "scrapeDetails": true, "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("tonyaka_educational_watermill/zillow-scraper-pro").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 = { "proxyConfig": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], } } # Run the Actor and wait for it to finish run = client.actor("tonyaka_educational_watermill/zillow-scraper-pro").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 '{ "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call tonyaka_educational_watermill/zillow-scraper-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=tonyaka_educational_watermill/zillow-scraper-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zillow Scraper Pro", "description": "Scrape Zillow property listings and deep details by ZIP code or URL. Returns address, price, beds, baths, sqft, Zestimate, price history, tax records, school ratings, and agent info. Anti-bot resilient via residential proxies and fingerprint spoofing. Supports for_sale, for_rent, and recently_sold.", "version": "2.0", "x-build-id": "XE3PHiIET9KUHWMKu" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/tonyaka_educational_watermill~zillow-scraper-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-tonyaka_educational_watermill-zillow-scraper-pro", "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/tonyaka_educational_watermill~zillow-scraper-pro/runs": { "post": { "operationId": "runs-sync-tonyaka_educational_watermill-zillow-scraper-pro", "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/tonyaka_educational_watermill~zillow-scraper-pro/run-sync": { "post": { "operationId": "run-sync-tonyaka_educational_watermill-zillow-scraper-pro", "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": { "zipCodes": { "title": "ZIP Codes", "type": "array", "description": "List of ZIP codes to search. E.g. [\"10001\", \"90210\"]. Uses Zillow's search API for fast results.", "items": { "type": "string" } }, "startUrls": { "title": "Start URLs", "type": "array", "description": "Zillow search or listing URLs to scrape directly. Accepts any Zillow search page URL or individual property detail URLs.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "listingType": { "title": "Listing Type", "enum": [ "for_sale", "for_rent", "recently_sold" ], "type": "string", "description": "Type of listings to scrape.", "default": "for_sale" }, "maxListings": { "title": "Max Listings", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of property listings to collect.", "default": 100 }, "scrapeDetails": { "title": "Scrape Property Details", "type": "boolean", "description": "Fetch each listing's detail page for rich data (price history, tax records, schools, agent info). Slightly slower but yields much richer data.", "default": true }, "proxyConfig": { "title": "Proxy Configuration", "type": "object", "description": "Apify proxy configuration. Residential proxies are strongly recommended." } } }, "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 } } } } } } } } } } ```