# Zillow B2b Lead Generator Email Scraper (`scrapeflux/zillow-b2b-lead-generator-email-scraper`) Actor Zillow B2B Lead Generator Email Scraper extracts real estate business leads including agent emails, broker contacts, property details, company names, phone numbers, listings, and URLs from Zillow. Ideal for B2B outreach, sales prospecting, lead generation, market research, and CRM enrichment. - **URL**: https://apify.com/scrapeflux/zillow-b2b-lead-generator-email-scraper.md - **Developed by:** [ScrapeFlux](https://apify.com/scrapeflux) (community) - **Categories:** Automation, Lead generation, Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 1,000 results 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 B2b Lead Generator Email Scraper 🚀 Struggling to find real estate agents, landlords, and property decision-makers fast with usable contact emails? **Zillow B2b Lead Generator Email Scraper** pulls contact emails from publicly available Zillow agent profile pages, so your outreach list is ready to act on. It’s ideal for Zillow B2B lead scraper workflows, Zillow email scraper use cases, and Zillow contact info extractor projects. Built for sales teams, researchers, and analysts who need Zillow real estate lead list data without manual copy-paste. In one run, you can collect up to thousands of leads (you control the cap) and export them immediately. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "searchTerm": "90210", "title": "John Doe, REALTOR", "url": "https://www.zillow.com/profile/john-doe-realtor/", "description": "Top producing agent — relocations, investments, and property management.", "email": "johndoe@acme-realty.com", "email_domain": "acme-realty.com", "source_region": "All", "country": "United States" } ```` **Extracted dataset fields (what you’ll get for each lead):** | Field | Type | What It Tells You | |---|---|---| | `searchTerm` | string | The input term (zip, city, or agent name) that led to this result. | | `title` | string | The agent profile’s display name shown in the extracted record. | | `url` | string | Direct link to the agent profile for verification and follow-up. | | `description` | string | Agency / bio text used to understand context for outreach messaging. | | `email` | string | The extracted contact email address for the agent/business. | | `email_domain` | string | The email’s domain, helpful for company-level filtering (e.g., by brand or industry). | | `source_region` | string | The selected content type (the schema lists `All` as the option). | | `country` | string | The target country selection used for localized discovery. | | `status` | string | Indicates the record processing result (success or error state). | | `error_message` | string | Populated when a record fails to process so you can troubleshoot or retry runs. | | `phone` | string | Phone number when available in extracted content (the listing emphasizes phone extraction alongside emails). | | `email_type` | string | Whether the extracted contact is treated as business or consumer email (configured by the actor’s logic). | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "searchTerms": ["Los Angeles", "90210", "New York Real Estate"], "country": "United States", "sourceRegion": "All", "engine": "legacy", "maxEmails": 50 } ``` | Parameter | Required | What It Does | |---|---|---| | `searchTerms` | ✅ | Provide zip codes, cities, or agent names you want to discover on Zillow. | | `country` | ✅ | Choose the target country for localized agent discovery. | | `sourceRegion` | ✅ | Select content type: `All` (Agent Profiles default). | | `engine` | ⬜ | Pick the scraping engine mode. “Performance (New)” is faster/cheaper and uses residential proxies; “Standard” is reliable but slower. | | `maxEmails` | ✅ | Set the maximum number of emails to collect (limits dataset size for faster testing and cost control). | | ↳ `engine` | ⬜ | When set, uses either `cost-effective` (Performance) or `legacy` (Standard). | *** ### What It Does Zillow B2b Lead Generator Email Scraper automates bulk extraction of contact emails from Zillow agent profile pages based on your search terms. #### Extract Relevant Zillow Agent Emails at Scale Feed in `searchTerms` like cities, zip codes, or agent names and the actor compiles a Zillow real estate lead list you can use for prospecting. It’s designed specifically for Zillow B2B lead scraper workflows where you need business-ready email contacts, not manual browsing. #### Uses Zillow B2B Email Scraper Inputs to Drive Discovery Your `country` selection and `sourceRegion` (Agent Profiles via `All`) guide what the actor pulls into your dataset. This means Zillow contact info extractor results stay aligned to the geographic scope you care about—especially useful when building a Zillow landlord lead generator or Zillow investor contact database. #### Clean, Integration-Ready Lead Records Each dataset row includes the search context (`searchTerm`), the agent details (`title`, `description`), and direct references (`url`). You also get the actual `email` plus the `email_domain` so you can quickly segment accounts or match against your CRM rules. #### Built-in Proxy Support for Reliable Scraping The actor includes support for different scraping engine modes (including a performance option) for more reliable extraction during larger runs. This helps reduce disruptions so your Zillow scraping for business leads pipeline stays consistent. #### Includes Retries and Fallbacks for Resilience When requests fail or return empty results, the actor is built to keep working and produce as complete a dataset as possible within your limits. This makes Zillow B2B prospecting email collection easier to run repeatedly. Overall, Zillow B2b Lead Generator Email Scraper turns Zillow outreach email list building into a fast, exportable workflow. *** ### Why Zillow B2b Lead Generator Email Scraper? There are plenty of ways to pull data from Zillow—here’s why Zillow B2b Lead Generator Email Scraper stands out. #### Purpose-Built for Zillow Contact Emails It’s designed to focus on extracting contact emails from Zillow agent profiles and returning structured lead records for downstream outreach. That’s exactly what you need for Zillow email scraper tasks, whether you’re building a Zillow commercial leads email scraper list or finding owner email targets. #### Controlled Output Size for Faster Iteration You can cap results with `maxEmails`, which is perfect for quick testing, A/B outreach list builds, and cost control. Instead of waiting on huge exports, you can tune the run until your enrichment pipeline is satisfied. #### Engine Options for Different Needs The actor offers selectable engine modes, including a faster, cost-effective option and a standard reliable option. This gives you flexibility when running Zillow real estate lead list generation at different batch sizes. *** ### Real-World Use Cases Here's how different teams put Zillow B2b Lead Generator Email Scraper to work: **Sales Development Teams**\ A sales team starts a new territory campaign for property owners and agents in multiple regions. They run Zillow B2b Lead Generator Email Scraper with city and zip `searchTerms`, then immediately export results to build a clean outreach email list with `email_domain` for quick segmentation. Their prospecting time drops from hours of manual searching to a repeatable bulk export workflow. **Real Estate Marketers**\ A marketing manager needs a Zillow contact info extractor dataset to personalize campaigns by agency and geography. They use the extracted `description` and direct profile `url` to validate context, then filter by `email_domain` to keep campaigns consistent by brand and office. The resulting Zillow real estate lead list is ready for enrichment and sequencing. **Freelance Researchers & Data Analysts**\ An analyst working on lead generation tool comparisons collects evidence-based records for Zillow B2B prospecting email outreach. They run the actor with a controlled `maxEmails` cap to produce manageable datasets, then load the structured output fields for analysis and deduping. The clean schema helps them standardize “contact database” datasets across multiple projects. **Business Development for Property Services**\ A property management and consulting firm wants to target relevant agents and businesses connected to specific market areas. They run Zillow B2B lead scraper searches by `searchTerms`, export the results, and use `email` and `email_domain` to build an investor contact database for outreach. The team focuses on sending messages rather than chasing contact details. **Automation & Data Pipeline Specialists**\ A developer integrates actor runs into an internal pipeline that enriches leads and syncs them into a CRM. They trigger Zillow B2b Lead Generator Email Scraper, capture the dataset fields (`url`, `email`, `email_domain`, `title`, `description`), and push them into downstream automation. This turns Zillow scraping for business leads into a scheduled, repeatable data source. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor on Apify**\ Go to the actor page in the Apify console: . 2. **Enter your inputs**\ Add your `searchTerms`, choose `country`, set `sourceRegion` to `All`, and set `maxEmails` to control how many emails to collect. 3. **Choose your scraping engine (optional)**\ If you want faster runs, select the “Performance (New)” engine; otherwise keep the default `legacy`. 4. **Start the run and watch the live log**\ Monitor progress in the actor run logs to confirm it’s extracting leads. 5. **Open the Dataset tab**\ Results appear as structured lead records with `searchTerm`, `title`, `url`, `email`, and `email_domain`. 6. **Export your leads**\ Download as JSON, CSV, or Excel from the Apify dashboard. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Zillow B2b Lead Generator Email Scraper fits directly into your existing workflow. You can export results from the Apify dashboard in JSON, CSV, or Excel format from the dataset tab. This makes it easy to move Zillow landlord lead generator data into a spreadsheet, CRM import, or enrichment process. For automation, you can integrate with your stack using Apify’s API access patterns and schedule runs to refresh your Zillow outreach email list over time. You can also connect to tools like Zapier/Make for no-code pushes into downstream systems, and use webhooks to trigger actions when the run completes. *** ### Pricing Zillow B2b Lead Generator Email Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. Free tier typically includes $5 platform credits on sign-up, enough for several real test runs. For larger batches, runs are billed per Actor compute unit (CU) without a monthly fee lock-in. For heavier workloads or long-running schedules, use Apify subscription plans and scale when your lead volume grows. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Platform rate limits | Adaptive request pacing and controlled concurrency to improve stability | | Blocked/failed requests | Retries and fallback behavior to keep extraction moving | | Empty results for some pages | Stops early when repeated pages return no usable results | | Dataset completeness | Pushes records as they’re extracted so you don’t lose all progress | | Result size control | `maxEmails` limits the number of emails collected per run | Limitations: results depend on what contact info is publicly available on targeted Zillow agent profile pages. If no email is present in the extracted content for a given profile, the dataset record may not contain an email value. Private, login-gated, or password-protected pages are not accessed by this actor. For enterprise-scale needs or custom configurations, reach out and we’ll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes. Apify offers a free tier that includes monthly usage credits, which is usually enough to test Zillow B2b Lead Generator Email Scraper on smaller batches. #### Do I need to log in or create an account on Zillow? No. This actor works from publicly available Zillow agent profile content and does not require Zillow logins to run. #### How accurate is the extracted data? The actor extracts what’s available in the publicly exposed profile content and returns it in structured fields like `email` and `email_domain`. Accuracy depends on what the profile owner has published. #### How many results can I get per run? You control the size using `maxEmails`, which caps the maximum number of emails the actor collects. This is the main knob for getting exactly how much Zillow B2B prospecting email data you need. #### How fresh is the data? Data freshness depends on when the actor runs and what’s currently visible on the profiles. Each run reflects the content available at that time. #### Is this legal? Does it comply with GDPR / CCPA? The actor accesses **publicly available data** and returns it in a structured dataset. You are responsible for complying with GDPR, CCPA, and any applicable platform terms and local regulations when storing and using the data. #### Can I export to Google Sheets or Excel? Yes. You can export the dataset as JSON, CSV, or Excel from the Apify dashboard, and then import it into Google Sheets or Excel. You can also automate pushing data via common integration workflows. #### Can I schedule this to run automatically? Yes. You can schedule actor runs using Apify’s scheduling features, so your Zillow real estate lead list can be refreshed periodically without manual action. #### Can I access results via the API? Yes. You can trigger runs via Apify API and retrieve dataset results programmatically using Apify’s standard mechanisms. #### What happens when the actor encounters an error? The actor continues with resilient behavior (including retries and fallbacks) and provides error details through its run logs and record-level failure handling where applicable. If a run partially succeeds, you can still use the dataset output that was written successfully. *** ### Get Help & Use Responsibly Got a question about Zillow B2b Lead Generator Email Scraper or a feature you'd like added? Reach out at and we’ll help—feedback like “more fields” or “better filtering” is especially welcome. This actor collects **publicly available data**. It does not access private accounts, login-gated pages, or password-protected content. You’re responsible for GDPR, CCPA, and any applicable platform ToS. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `searchTerms` (type: `array`): Zip codes, cities, or agent names to search for on Zillow. ## `country` (type: `string`): Select the country for localized agent discovery. ## `sourceRegion` (type: `string`): Select content type: Agent Profiles (Default). ## `engine` (type: `string`): Select your preferred scraping method. ⚡ Performance (New): Faster, cheaper, uses residential proxies. 🛡️ Standard: Reliable, uses GOOGLE\_SERP proxy, but slower. ## `maxEmails` (type: `integer`): Limit the number of emails to collect. ## Actor input object example ```json { "searchTerms": [ "Los Angeles", "New York Real Estate", "90210" ], "country": "United States", "sourceRegion": "All", "engine": "legacy", "maxEmails": 20 } ``` # 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 = { "searchTerms": [ "Los Angeles", "New York Real Estate", "90210" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeflux/zillow-b2b-lead-generator-email-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 = { "searchTerms": [ "Los Angeles", "New York Real Estate", "90210", ] } # Run the Actor and wait for it to finish run = client.actor("scrapeflux/zillow-b2b-lead-generator-email-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 '{ "searchTerms": [ "Los Angeles", "New York Real Estate", "90210" ] }' | apify call scrapeflux/zillow-b2b-lead-generator-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeflux/zillow-b2b-lead-generator-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zillow B2b Lead Generator Email Scraper", "description": "Zillow B2B Lead Generator Email Scraper extracts real estate business leads including agent emails, broker contacts, property details, company names, phone numbers, listings, and URLs from Zillow. Ideal for B2B outreach, sales prospecting, lead generation, market research, and CRM enrichment.", "version": "1.0", "x-build-id": "dFTUBSmAbeoau8MCg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeflux~zillow-b2b-lead-generator-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeflux-zillow-b2b-lead-generator-email-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeflux~zillow-b2b-lead-generator-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapeflux-zillow-b2b-lead-generator-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeflux~zillow-b2b-lead-generator-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapeflux-zillow-b2b-lead-generator-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "searchTerms", "country", "sourceRegion", "maxEmails" ], "properties": { "searchTerms": { "title": "Search Terms", "type": "array", "description": "Zip codes, cities, or agent names to search for on Zillow.", "items": { "type": "string" } }, "country": { "title": "Target Country", "enum": [ "United States", "United Kingdom", "Canada", "Australia", "Germany", "France", "India", "Japan", "Brazil", "Italy", "Spain", "Netherlands", "Sweden", "Norway", "Denmark", "Finland", "Poland", "Czech Republic", "Hungary", "Romania", "Bulgaria", "Croatia", "Slovenia", "Slovakia", "Estonia", "Latvia", "Lithuania", "Portugal", "Greece", "Cyprus", "Malta", "Luxembourg", "Ireland", "Belgium", "Austria", "Switzerland", "Liechtenstein", "Iceland", "South Korea", "China", "Mexico", "Argentina", "Chile", "Colombia", "Peru", "Venezuela", "Ecuador", "Uruguay", "Paraguay", "Bolivia", "Guyana", "Suriname", "French Guiana", "Falkland Islands (Malvinas)", "South Georgia and the South Sandwich Islands", "Bonaire, Sint Eustatius and Saba", "Curaçao", "Aruba", "Sint Maarten (Dutch part)", "Turks and Caicos Islands", "British Virgin Islands", "Anguilla", "Montserrat", "Antigua and Barbuda", "Barbados", "Dominica", "Grenada", "Saint Kitts and Nevis", "Saint Lucia", "Saint Vincent and the Grenadines", "Trinidad and Tobago", "Jamaica", "Bahamas", "Belize", "Costa Rica", "Guatemala", "Honduras", "Nicaragua", "Panama", "El Salvador", "Cuba", "Dominican Republic", "Haiti", "Puerto Rico", "U.S. Virgin Islands", "American Samoa", "Guam", "Northern Mariana Islands", "Saudi Arabia", "United Arab Emirates", "Bahrain", "Iraq", "Iran, Islamic Republic of", "Israel", "Jordan", "Kuwait", "Lebanon", "Oman", "Qatar", "Syrian Arab Republic", "Yemen", "Afghanistan", "Bangladesh", "Bhutan", "Maldives", "Nepal", "Pakistan", "Sri Lanka", "Myanmar", "Cambodia", "Lao People's Democratic Republic", "Thailand", "Viet Nam", "Malaysia", "Singapore", "Brunei Darussalam", "Philippines", "Indonesia", "Timor-Leste", "Papua New Guinea", "Fiji", "New Zealand", "Solomon Islands", "Vanuatu", "New Caledonia", "French Polynesia", "Wallis and Futuna", "Samoa", "Tonga", "Tuvalu", "Kiribati", "Nauru", "Federated States of Micronesia", "Marshall Islands", "Palau", "Cook Islands", "Niue", "Tokelau" ], "type": "string", "description": "Select the country for localized agent discovery.", "default": "United States" }, "sourceRegion": { "title": "Content Type", "enum": [ "All" ], "type": "string", "description": "Select content type: Agent Profiles (Default).", "default": "All" }, "engine": { "title": "Scraping Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Select your preferred scraping method. ⚡ Performance (New): Faster, cheaper, uses residential proxies. 🛡️ Standard: Reliable, uses GOOGLE_SERP proxy, but slower.", "default": "legacy" }, "maxEmails": { "title": "Maximum Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Limit the number of emails to collect.", "default": 20 } } }, "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 } } } } } } } } } } ```