# Facebook B2b Email Scraper (`scrapeflux/facebook-b2b-email-scraper`) Actor 🚀 Facebook B2B Email Scraper extracts business emails from Facebook profiles & pages to power targeted lead generation. 🏢 Build cleaner prospect lists faster—perfect for sales, marketing, and recruitment. 📩 Extract, export, grow. - **URL**: https://apify.com/scrapeflux/facebook-b2b-email-scraper.md - **Developed by:** [ScrapeFlux](https://apify.com/scrapeflux) (community) - **Categories:** Lead generation, Social media, Automation - **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 ### Facebook B2b Email Scraper ⚡ Struggling to find real business emails from Facebook for outreach takes hours of manual searching and copying. **Facebook B2b Email Scraper** automates the job by extracting business contact emails tied to your keywords and targeting options, so you can build B2B lead email lists faster. It’s ideal for anyone doing Facebook B2B email scraper prospecting, from Facebook page email scraper work to automated Facebook email scraping for marketing leads. Sales teams, lead gen specialists, and researchers use it to turn public Facebook content into structured email-domain results at scale—often in minutes, not days. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "keyword": "fitness", "title": "Acme Fitness Group", "url": "https://www.facebook.com/acmefitnessgroup/", "description": "We provide coaching, programs, and support. Contact us via email.", "email": "hello@acmefitness.com", "email_domain": "acmefitness.com", "scrape_from": "Groups", "country": "United States", "status": "success", "error_message": null } ```` | Field | Type | What It Tells You | |---|---|---| | `keyword` | string | The keyword that helped surface this contact, so you can segment leads by campaign theme (e.g., fitness vs. gym). | | `title` | string | The Facebook entity’s title/name connected to the scraped email record. | | `url` | string | A direct link back to the source profile/page/group so you can verify quickly. | | `description` | string | Context captured alongside the email to help analysts judge relevance fast. | | `email` | string | The extracted business email address you can add to outreach workflows. | | `email_domain` | string | The company domain—useful for deduping and building domain-level scoring for B2B prospecting email list from Facebook. | | `scrape_from` | string | Where the email was scraped from (for example, Profiles, Posts, Groups, Videos, Marketplace). | | `country` | string | The targeted country to match results with your market research or lead requirements. | | `status` | string | Indicates whether the actor produced a successful record (useful for downstream filtering). | | `error_message` | string | Contains error details when something goes wrong, otherwise `null`. | 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 { "keywords": ["fitness", "gym", "workout"], "country": "United States", "scrapeFrom": "All", "engine": "legacy", "maxEmails": 50 } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | Enter one or more keywords to search for on Facebook. | | `country` | ✅ | Choose a country to target for the run. | | `scrapeFrom` | ✅ | Choose what type of Facebook content to scrape: All, Profiles, Reels, Posts, Groups, Videos, Photos, Events, or Marketplace. | | `engine` | ⬜ | Pick the scraping engine. `legacy` is described as more reliable but slower and more expensive, while `cost-effective` is described as faster/cheaper using residential proxies with async requests. | | `maxEmails` | ✅ | Cap how many emails to collect in this run (from 1 to 10000). | *** ### What It Does **Facebook B2b Email Scraper** extracts business emails from Facebook and writes structured results to your dataset. #### Extract B2B emails tied to your keywords Run it with one or more `keywords` and the actor collects matching business email contacts from publicly available Facebook content. It’s built for Facebook B2B email scraper workflows where you want lead emails, not just profiles. #### Target the exact Facebook content types you care about Use `scrapeFrom` to control where results come from—whether you want a broad scrape across everything (`All`) or focused extraction like Profiles, Groups, Posts, Marketplace, and more. This makes it a practical Facebook group email scraping tool and also a Facebook page email scraper when you narrow the scope. #### Cost control with a clear results cap `maxEmails` lets you define how many email records you want per run, so you can test quickly or scale up for B2B lead generation email scraper projects without uncontrolled output. #### Clean, integration-ready dataset records Each dataset row includes fields like `keyword`, `title`, `url`, `description`, `email`, `email_domain`, `scrape_from`, and `country`. This structure is easy to map into CRMs, enrichment steps, or outreach list builders for Facebook outreach email list builder use cases. #### Uses built-in resilience for more reliable runs The actor is designed to be robust with a chosen `engine`, and it aims to keep scraping dependable as it collects results. If you’re doing automated Facebook email scraping for larger lead batches, this helps reduce the “stop-and-restart” pain. Overall, **Facebook B2b Email Scraper** turns publicly available Facebook content into a ready-to-use B2B email list with predictable structure and output fields for downstream work. *** ### Why Facebook B2b Email Scraper? There are plenty of ways to pull data from Facebook—here’s why Facebook B2b Email Scraper stands out. #### Focused email output (not just discovery) Instead of returning raw posts/pages only, Facebook B2b Email Scraper is built specifically to extract email addresses and keep them connected to where they were found. That’s what makes it a true Facebook contact email finder for B2B prospecting email list from Facebook. #### Flexible targeting for your outreach strategy With `keywords`, `country`, and `scrapeFrom`, you can tailor discovery to your ICP and content preferences, whether you’re extracting emails from Facebook profiles or mining emails from Groups and Marketplace. This flexibility supports Facebook marketing lead scraper emails without extra manual filtering work. #### Built for scale with predictable limits You control runtime output using `maxEmails`, so **Facebook B2b Email Scraper** fits both small validation runs and larger B2B outreach email list builder jobs. *** ### Real-World Use Cases Here's how different teams put Facebook B2b Email Scraper to work: **B2B Sales Teams**\ Your reps need fresh prospects for outbound, but searching Facebook for contact emails manually kills momentum. You run Facebook B2b Email Scraper with your niche keywords and set `scrapeFrom` to capture the types of pages/groups that match your market, then import `email` and `email_domain` into your outreach system. **Marketing Agencies**\ A client campaign wants targeted lead generation email scraper results for a specific country and industry theme. You collect structured email records with the matching `keyword` and `scrape_from` so you can report back on which content types produced the best-quality domains. **Freelance Researchers**\ Instead of spending days collecting scattered contact details, you generate a dataset with `url`, `title`, and `description` alongside each email. That context helps you quickly validate relevance before you deliver a clean prospect list to your stakeholders. **Automation & Data Ops**\ You want repeatable lead-building runs without manual steps. You trigger Facebook B2b Email Scraper, ingest the dataset fields (`email`, `email_domain`, `scrape_from`, `country`) into your pipeline, then run deduping and enrichment downstream. **Growth Teams Building Outbound Lists**\ You test new messaging angles by segmenting emails by the `keyword` that found them. Over multiple runs, you refine which search themes perform best for Facebook group email scraping tool style lead extraction. *** ### 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 on Apify at https://console.apify.com. 2. **Enter your inputs**\ Add `keywords`, choose a `country`, set `scrapeFrom`, and set `maxEmails` (optionally choose `engine`). 3. **Configure proxy settings (optional, recommended)**\ If your account uses Apify Proxy or other network settings, enable what you typically use for reliable scraping. 4. **Start the run and watch the live log**\ Monitor progress directly in the Apify UI to confirm the actor is extracting records. 5. **Open the Dataset tab**\ As the run proceeds, review captured fields like `email`, `email_domain`, `url`, `scrape_from`, and `country`. 6. **Export your results**\ Download your dataset from the dashboard in your preferred format (JSON, CSV, or Excel). The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Facebook B2b Email Scraper fits directly into your existing workflow. Export the dataset from the Apify dashboard as JSON, CSV, or Excel, then import it into your CRM or spreadsheets. You can also connect your results to other tools using no-code automation (for example via Zapier/Make) or use the Apify API to fetch dataset results programmatically for your own pipelines and scheduled lead-building jobs. If your team needs downstream actions when a run completes, you can trigger follow-up steps using your normal Apify integration approach (webhook-based or API polling—depending on your setup). *** ### Pricing Facebook B2b Email Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. On sign-up, you get $5 platform credits, which are typically enough for several real test runs. If you scale, pricing is pay-as-you-go based on Actor compute unit (CU) usage, so you only pay for the platform resources consumed during runs. Start free at https://apify.com — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Rate limits | Uses a selectable `engine` and run-time controls to improve success when scraping is constrained. | | Proxy support | Supports running with proxy configurations for reliability. | | Output control | `maxEmails` caps results so runs don’t exceed your budget or testing needs. | | Error handling | Includes error details in `error_message` when something goes wrong. | | Partial results | You’ll still get whatever records were successfully captured during the run. | | Scale limits | You control volume with `maxEmails` (up to 10000). | **Limitations:** This actor extracts emails from publicly available Facebook content and won’t access login-gated or private material. If a target entity doesn’t publish business contact emails, you won’t get results for that entity. 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 with monthly usage credits so you can run Facebook B2b Email Scraper for testing before scaling. #### Do I need to log in or create an account on Facebook? No. The actor is designed to work with publicly available Facebook content, so you don’t need a Facebook account for the scraping job. #### How accurate is the extracted data? Accuracy depends on what email addresses are publicly shown in the source content. The actor extracts and outputs the email fields it finds, and stores `email_domain` to help you validate and segment results. #### How many results can I get per run? You control the output volume using `maxEmails`, which ranges from 1 to 10000. If you set it lower, you’ll collect fewer emails for faster testing. #### How fresh is the data? The data reflects what’s publicly available when you run the actor. For fresher results, schedule more frequent runs using your preferred automation approach. #### Is this legal? Does it comply with GDPR / CCPA? The actor is designed to use **publicly available data**. It’s still your responsibility to ensure your usage complies with GDPR/CCPA, spam regulations, and applicable platform Terms of Service. #### Can I export to Google Sheets or Excel? Yes. You can export your dataset as JSON, CSV, or Excel from the Apify dashboard. From there, you can import into Google Sheets or other tools that accept CSV/Excel. #### Can I schedule this to run automatically? Yes. You can run actors on a schedule using Apify’s automation capabilities (for example, recurring runs), depending on your account setup. #### Can I access results via the API? Yes. Apify supports accessing actor runs and datasets via its API, so you can integrate Facebook B2b Email Scraper into your own data pipelines programmatically. #### What happens when the actor encounters an error? When errors occur, the dataset includes an `error_message` field for failure details. You can use `status` and `error_message` to filter successful records and handle exceptions in your workflow. *** ### Get Help & Use Responsibly Got a question about Facebook B2b Email Scraper or a feature you'd like added? Reach out at . We welcome requests and ideas, and we actively maintain the actor based on user feedback. **publicly available data** only. It does not access private accounts, login-gated pages, or password-protected content. Please ensure your use complies with GDPR, CCPA, and Facebook’s Terms of Service. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): Enter one or more keywords to search for on Facebook. ## `country` (type: `string`): Specify the country to target for Google search results. ## `scrapeFrom` (type: `string`): Choose one option — All, Profiles, Reels, Posts, Groups, Videos, Photos, Events, or Marketplace. ## `engine` (type: `string`): Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `maxEmails` (type: `integer`): Enter the maximum number of emails to collect. ## Actor input object example ```json { "keywords": [ "fitness", "gym", "workout" ], "country": "United States", "scrapeFrom": "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 = { "keywords": [ "fitness", "gym", "workout" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeflux/facebook-b2b-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 = { "keywords": [ "fitness", "gym", "workout", ] } # Run the Actor and wait for it to finish run = client.actor("scrapeflux/facebook-b2b-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 '{ "keywords": [ "fitness", "gym", "workout" ] }' | apify call scrapeflux/facebook-b2b-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeflux/facebook-b2b-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook B2b Email Scraper", "description": "🚀 Facebook B2B Email Scraper extracts business emails from Facebook profiles & pages to power targeted lead generation. 🏢 Build cleaner prospect lists faster—perfect for sales, marketing, and recruitment. 📩 Extract, export, grow.", "version": "1.0", "x-build-id": "BrOWjRxN4a6ASUeor" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeflux~facebook-b2b-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeflux-facebook-b2b-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeflux~facebook-b2b-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapeflux-facebook-b2b-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeflux~facebook-b2b-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapeflux-facebook-b2b-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords", "country", "scrapeFrom", "maxEmails" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "Enter one or more keywords to search for on Facebook.", "items": { "type": "string" } }, "country": { "title": "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": "Specify the country to target for Google search results.", "default": "United States" }, "scrapeFrom": { "title": "Scrape From", "enum": [ "All", "Profiles", "Reels", "Posts", "Groups", "Videos", "Photos", "Events", "Marketplace" ], "type": "string", "description": "Choose one option — All, Profiles, Reels, Posts, Groups, Videos, Photos, Events, or Marketplace.", "default": "All" }, "engine": { "title": "Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "maxEmails": { "title": "Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Enter the maximum 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 } } } } } } } } } } ```