# Meta Ads Page Scraper (`thenetaji/meta-ads-page`) Actor Two ways to work with a Facebook advertiser in Meta Ad Library: find a Page (and its Page ID) by brand or company name, or browse every public ad from a known Page ID. Browsed ads can be enriched with full details. No Facebook login or Meta API key required. - **URL**: https://apify.com/thenetaji/meta-ads-page.md - **Developed by:** [The Netaji](https://apify.com/thenetaji) (community) - **Categories:** Social media, Lead generation, Developer tools - **Stats:** 1 total users, 0 monthly users, 40.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 **Meta Ads Page Scraper finds Facebook advertiser Pages by name, or browses every public ad from a known Page ID in Meta Ad Library, with optional per-ad detail enrichment.** Use this Actor to work with a specific advertiser in Meta Ad Library. Pick a function: find an advertiser Page (and its Page ID) by brand or company name, or browse every public ad from a Page ID you already have. It is built for competitor tracking, page-level ad libraries, and recurring watchlists. Browsed ads can be enriched with full details. ### What is Meta Ad Library? Meta Ad Library is Meta's public ad transparency database. It lists ads running across Facebook, Instagram, Messenger, and the Audience Network, including the advertiser page, media, and active status. You can browse it at https://www.facebook.com/ads/library/ without a Facebook login. ### What data can I extract with Meta Ads Page Scraper? Meta Ads Page Scraper extracts the following data from Meta Ad Library: - **Ad identity** - Ad archive IDs, page IDs, advertiser references, and dataset records for each returned ad. - **Advertiser and page data** - Facebook page IDs, matching advertiser pages, and page-level records returned by page search and page browsing modes. - **Ad creative and performance** - Ad status, start and end dates, publisher platforms, currency, spend and reach estimates, and the creative snapshot (body, title, call to action, images, and videos). - **Enriched ad details** - When enrichment is enabled, each ad row also includes the full ad-details payload for that ad. You can collect all of this without an API key, rate limits, or code. ### How can I use Meta Ad Library data? - **Competitor ad research** - Monitor competitor creatives, messages, offers, landing pages, and advertiser activity across Meta platforms. - **Market research** - Track how brands position products, which categories are active, and how campaign messaging changes by country or season. - **Ad intelligence** - Build datasets for creative analysis, copywriting research, campaign monitoring, and paid social reporting. - **Lead generation** - Find active advertisers and pages that are currently investing in Meta ads. - **AI and analytics workflows** - Export structured ad data to train classifiers, enrich internal dashboards, or feed automated research agents. ### How to scrape Meta Ad Library #### Step 1: Choose your input Enter the Meta Ad Library search terms, IDs, or filters supported by this Actor. #### Step 2: Set filters and limits Adjust country, status, date, platform, page size, and max item settings to control the dataset and cost. #### Step 3: Run the Actor Start the run in Apify Console or call it through the Apify API. #### Step 4: Export your data Download results in JSON, CSV, Excel, XML, or HTML, or consume them through the Apify Dataset API. ### Meta Ads Page Scraper features - **Search, browse, and enrich** - Search ads by keyword or Ad Library URL, browse every ad from an advertiser Page, find advertiser Pages by name, and optionally enrich each ad with full details. - **Apify-ready datasets** - Results are saved to the default Apify dataset and can be downloaded as JSON, CSV, Excel, XML, or HTML. - **Country and content filters** - Filter by country, ad status, ad type, media type, date range, language, publisher platform, and page IDs. - **Pagination and limits** - Use page size, cursors, and max item limits to control run size and cost. - **Automation support** - Run manually, schedule recurring runs, call the Actor through the Apify API, or trigger workflows with webhooks. Built for reliable runs at scale: requests use proxy rotation, automatic retries, and pagination handling so large Meta Ad Library scrapes finish without manual babysitting. ### Input Configure the run on the Actor's Input tab. Set the fields for your chosen mode, then start the run. #### Find advertiser page Set Function to "Find advertiser page" and enter a brand or company name to get matching Pages and their Page IDs. | Field | Type | Required | Description | | --- | --- | --- | --- | | `scraperType` | string | Yes | Choose whether to find an advertiser Page by name, or browse ads from a known Page ID. | | `q` | string | No | Used by "Find advertiser page": the brand or company name to look up (e.g. Nike). | | `country` | string | No | ISO 3166-1 alpha-2 country code to target, e.g. US, IN, GB. | | `ad_type` | string | No | Limit results to a specific ad category, such as political and issue ads. | | `maxItems` | integer | No | Maximum number of results to return. Set 0 for no limit. | #### Browse page ads Set Function to "Browse page ads" and provide a Page ID to scrape that advertiser's ads. | Field | Type | Required | Description | | --- | --- | --- | --- | | `scraperType` | string | Yes | Choose whether to find an advertiser Page by name, or browse ads from a known Page ID. | | `page_id` | string | No | Numeric ID of the advertiser's Facebook Page whose ads you want. Don't know it? Use the "Find advertiser page" mode to look it up by brand name. | | `country` | string | No | ISO 3166-1 alpha-2 country code to target, e.g. US, IN, GB. | | `active_status` | string | No | Return all ads, or only currently active or inactive ones. | | `media_type` | string | No | Limit results to a creative format: images, videos, or memes. | | `publisher_platforms` | array | No | Only include ads shown on the selected Meta platforms. | | `date_min` | string | No | Only include ads active on or after this date (YYYY-MM-DD). | | `date_max` | string | No | Only include ads active on or before this date (YYYY-MM-DD). | | `maxItems` | integer | No | Maximum number of results to return. Set 0 for no limit. | | `enrichAdDetails` | boolean | No | Fetch full details for every returned ad (one extra request per ad — slower and billed as an ad-details enrichment). Leave off for fast, lightweight runs. | #### Example input ```json { "scraperType": "page", "page_id": "102988293558", "country": "US", "active_status": "all", "maxItems": 50, "enrichAdDetails": false } ```` ### Output Download results as JSON, CSV, Excel, XML, or HTML, or pull them from the Apify Dataset API. #### 🏢 Matching pages | Field | Type | Description | | --- | --- | --- | | `pageId` | string,null | Facebook Page ID of a matching advertiser. | | `name` | string,null | Name of the matching advertiser Page. | | `category` | string,null | Facebook category of the advertiser Page. | | `likes` | number,null | Number of likes on the advertiser Page. | | `verification` | string,null | Verification status of the advertiser Page. | | `instagramUsername` | string,null | Linked Instagram username of the advertiser, if any. | #### 📄 Page ads | Field | Type | Description | | --- | --- | --- | | `ad_archive_id` | string,null | Unique ID of the ad in the Meta Ad Library. | | `page_id` | string,null | Numeric ID of the advertiser's Facebook Page. | | `page_name` | string,null | Name of the advertiser's Facebook Page. | | `is_active` | boolean,null | Whether the ad is currently running. | | `start_date` | number,null | Unix timestamp when the ad started running. | | `snapshot` | object,null | Ad creative: body text, title, call to action, images, videos, and link. | #### Example output ```json { "pageId": "15087023444", "name": "Nike", "category": "Sportswear shop", "likes": 39599603, "verification": "BLUE_VERIFIED", "instagramUsername": "nike" } ``` ### How much does it cost to scrape Meta Ad Library? This Actor uses Apify pay-per-result pricing. You are charged for successful dataset results according to the Actor pricing shown on the Apify Pricing tab. Single-result modes return one dataset item, while search and page modes can return many items. Apify's free plan includes monthly credits, which may cover small test runs and up to the free result allowance configured for the Actor. Use the max item limit before large runs so you can control spend while testing keywords, countries, and advertiser pages. ### Meta Ads Page Scraper FAQ #### I don't know the Page ID. How do I find it? Set Function to "Find advertiser page" and enter the brand or company name. The Actor returns matching Pages with their Page IDs, which you can then use in "Browse page ads". #### How do I scrape ads from one Facebook Page? Set Function to "Browse page ads", enter the Page ID, choose a country and optional filters, then run. Use Max Results to limit how many ads are saved, and enable enrichment for full per-ad details. #### Can I export Meta Ads data to CSV or Excel? Yes. Apify datasets can be downloaded as JSON, CSV, Excel, XML, HTML, or accessed through the Dataset API. #### Do I need a Meta API key? No. You configure the Actor input in Apify and run it without providing a Meta developer API key. #### Can I schedule recurring Meta Ads monitoring? Yes. Use Apify schedules to run the Actor hourly, daily, weekly, or at any custom interval supported by Apify. #### How do I control run cost? Set maxItems for search and page browsing runs, keep page\_size conservative while testing, and expand limits after you confirm the input returns the data you need. ### Can I integrate Meta Ads Page Scraper with other apps? Yes. Meta Ads Page Scraper works with Apify integrations and can send results to common automation, spreadsheet, database, and AI workflows. - **Make, Zapier, and n8n** - Send ad results into campaign monitoring, CRM, enrichment, or reporting workflows. - **Google Sheets and Airtable** - Keep competitor ad libraries and advertiser lists in shared tables. - **Slack and email** - Notify your team when scheduled monitoring runs finish. - **Apify API and webhooks** - Trigger runs from code and react to completed datasets automatically. - **Apify MCP Server** - Let AI agents query fresh Meta Ads data through Apify. ### Can I use Meta Ads Page Scraper with the Apify API? Yes. Meta Ads Page Scraper can be run programmatically with the Apify API. You can also schedule recurring runs, trigger runs with webhooks, and export data through the Dataset API. #### Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_API_TOKEN") run = client.actor("thenetaji/meta-ads-page").call(run_input={ "scraperType": "page", "page_id": "102988293558", "country": "US", "active_status": "all", "maxItems": 50, "enrichAdDetails": false }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` #### Node.js ```javascript import { ApifyClient } from "apify-client"; const client = new ApifyClient({ token: "YOUR_APIFY_API_TOKEN" }); const run = await client.actor("thenetaji/meta-ads-page").call({ "scraperType": "page", "page_id": "102988293558", "country": "US", "active_status": "all", "maxItems": 50, "enrichAdDetails": false }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Can I use Meta Ads Page Scraper through an MCP server? Yes. AI agents can call this Actor through the Apify MCP server. Point your MCP client at the Apify MCP server (https://mcp.apify.com) and enable the Actor as a tool so agents can pull fresh Meta Ad Library data on demand. ### Is it legal to scrape Meta Ad Library? This Actor extracts publicly available information from Meta Ad Library pages and related public ad transparency data. It does not require a Facebook login and should not be used to collect private user data. Your results may still contain personal data or regulated advertising information, so make sure your use case complies with GDPR, other privacy laws, Meta terms, and your own legal obligations. If you are unsure, consult a qualified lawyer. ### Your feedback Use the Issues tab on the Actor page for bug reports, missing fields, and feature requests. ### You might also like - [Instagram Scraper](https://apify.com/apify/instagram-scraper) - Scrape Instagram profiles, posts, comments, hashtags, and places. - [Facebook Posts Scraper](https://apify.com/apify/facebook-posts-scraper) - Extract public Facebook posts and engagement data. - [Google Search Results Scraper](https://apify.com/apify/google-search-scraper) - Collect organic and paid Google search result data. *Last updated:* 2026-07-02 *Keywords:* Meta Ads Page Scraper, Facebook Page ads scraper, find Facebook Page ID, scrape ads from Facebook page, Meta advertiser page ads # Actor input Schema ## `scraperType` (type: `string`): Choose whether to find an advertiser Page by name, or browse ads from a known Page ID. ## `q` (type: `string`): Used by "Find advertiser page": the brand or company name to look up (e.g. Nike). ## `page_id` (type: `string`): Numeric ID of the advertiser's Facebook Page whose ads you want. Don't know it? Use the "Find advertiser page" mode to look it up by brand name. ## `country` (type: `string`): ISO 3166-1 alpha-2 country code to target, e.g. US, IN, GB. ## `maxItems` (type: `integer`): Maximum number of results to return. Set 0 for no limit. ## `enrichAdDetails` (type: `boolean`): Fetch full details for every returned ad (one extra request per ad — slower and billed as an ad-details enrichment). Leave off for fast, lightweight runs. ## `active_status` (type: `string`): Return all ads, or only currently active or inactive ones. ## `ad_type` (type: `string`): Limit results to a specific ad category, such as political and issue ads. ## `media_type` (type: `string`): Limit results to a creative format: images, videos, or memes. ## `publisher_platforms` (type: `array`): Only include ads shown on the selected Meta platforms. ## `content_languages` (type: `string`): Comma-separated ISO 639-1 language codes to include, e.g. en,hi,es. ## `date_min` (type: `string`): Only include ads active on or after this date (YYYY-MM-DD). ## `date_max` (type: `string`): Only include ads active on or before this date (YYYY-MM-DD). ## `sort_mode` (type: `string`): Order results by a metric. Leave empty for the default order. ## `sort_direction` (type: `string`): Direction to sort in when Sort By is set. ## Actor input object example ```json { "scraperType": "page", "q": "Nike", "page_id": "15087023444", "country": "US", "maxItems": 10, "enrichAdDetails": false, "active_status": "all", "ad_type": "ALL", "media_type": "all", "content_languages": "en,hi", "date_min": "2024-01-01", "date_max": "2024-12-31" } ``` # Actor output Schema ## `dataset` (type: `string`): Dataset containing all scraped data # 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 = { "q": "Nike", "page_id": "15087023444", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("thenetaji/meta-ads-page").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 = { "q": "Nike", "page_id": "15087023444", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("thenetaji/meta-ads-page").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 '{ "q": "Nike", "page_id": "15087023444", "maxItems": 10 }' | apify call thenetaji/meta-ads-page --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=thenetaji/meta-ads-page", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Meta Ads Page Scraper", "description": "Two ways to work with a Facebook advertiser in Meta Ad Library: find a Page (and its Page ID) by brand or company name, or browse every public ad from a known Page ID. Browsed ads can be enriched with full details. No Facebook login or Meta API key required.", "version": "0.1", "x-build-id": "QwA5lQOqIAl2jT10U" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/thenetaji~meta-ads-page/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-thenetaji-meta-ads-page", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/thenetaji~meta-ads-page/runs": { "post": { "operationId": "runs-sync-thenetaji-meta-ads-page", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/thenetaji~meta-ads-page/run-sync": { "post": { "operationId": "run-sync-thenetaji-meta-ads-page", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "scraperType" ], "properties": { "scraperType": { "title": "Function", "enum": [ "searchPages", "page" ], "type": "string", "description": "Choose whether to find an advertiser Page by name, or browse ads from a known Page ID.", "default": "page" }, "q": { "title": "Company or Brand Name", "type": "string", "description": "Used by \"Find advertiser page\": the brand or company name to look up (e.g. Nike)." }, "page_id": { "title": "Facebook Page ID", "type": "string", "description": "Numeric ID of the advertiser's Facebook Page whose ads you want. Don't know it? Use the \"Find advertiser page\" mode to look it up by brand name." }, "country": { "title": "Country", "type": "string", "description": "ISO 3166-1 alpha-2 country code to target, e.g. US, IN, GB.", "default": "US" }, "maxItems": { "title": "Max Results", "minimum": 0, "type": "integer", "description": "Maximum number of results to return. Set 0 for no limit.", "default": 50 }, "enrichAdDetails": { "title": "Enrich with ad details", "type": "boolean", "description": "Fetch full details for every returned ad (one extra request per ad — slower and billed as an ad-details enrichment). Leave off for fast, lightweight runs.", "default": false }, "active_status": { "title": "Ad Status", "enum": [ "all", "active", "inactive" ], "type": "string", "description": "Return all ads, or only currently active or inactive ones.", "default": "all" }, "ad_type": { "title": "Ad Category", "enum": [ "ALL", "POLITICAL_AND_ISSUE_ADS", "HOUSING_ADS", "EMPLOYMENT_ADS", "CREDIT_ADS" ], "type": "string", "description": "Limit results to a specific ad category, such as political and issue ads.", "default": "ALL" }, "media_type": { "title": "Creative Format", "enum": [ "all", "image", "video", "meme" ], "type": "string", "description": "Limit results to a creative format: images, videos, or memes.", "default": "all" }, "publisher_platforms": { "title": "Platforms", "type": "array", "description": "Only include ads shown on the selected Meta platforms.", "items": { "type": "string", "enum": [ "FACEBOOK", "INSTAGRAM", "AUDIENCE_NETWORK", "MESSENGER" ], "enumTitles": [ "Facebook", "Instagram", "Audience Network", "Messenger" ] } }, "content_languages": { "title": "Ad Languages", "type": "string", "description": "Comma-separated ISO 639-1 language codes to include, e.g. en,hi,es." }, "date_min": { "title": "Start Date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Only include ads active on or after this date (YYYY-MM-DD)." }, "date_max": { "title": "End Date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Only include ads active on or before this date (YYYY-MM-DD)." }, "sort_mode": { "title": "Sort By", "enum": [ "total_impressions" ], "type": "string", "description": "Order results by a metric. Leave empty for the default order." }, "sort_direction": { "title": "Sort Direction", "enum": [ "desc" ], "type": "string", "description": "Direction to sort in when Sort By is set." } } }, "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 } } } } } } } } } } ```