# Facebook Ads Scraper (`rover-omniscraper/facebook-ads-scraper`) Actor Facebook Ads Library Scraper - Lightning Fast Edition | Extract Active Facebook Ads Data Instantly. Scrape ads by country & keyword with ultra-fast HTML parsing. Perfect for marketing research, competitor analysis & lead generation. Headless browser automation with Playwright & Apify. - **URL**: https://apify.com/rover-omniscraper/facebook-ads-scraper.md - **Developed by:** [Rover Omniscraper](https://apify.com/rover-omniscraper) (community) - **Categories:** Automation, Lead generation, Real estate - **Stats:** 183 total users, 12 monthly users, 100.0% runs succeeded, 6 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Ads Scraper - Apify Actor A high-performance Facebook Ads Library scraper built for the Apify platform using Playwright. This actor efficiently scrapes Facebook's Ad Library for ads based on country-keyword pairs with optimized resource usage. ### 🚀 Features - **High Performance**: Optimized for Apify platform with minimal resource consumption - **Batch Processing**: Controlled concurrency to prevent memory issues - **Comprehensive Data**: Extracts detailed ad information including: - Ad status and Library ID - Page name and start date - Primary text and Call-to-Action (CTA) - External links and image URLs - Raw ad content - **Robust Error Handling**: Continues processing even if individual ads fail - **Real-time Output**: Results are saved to Apify dataset immediately ### 📋 Input Schema The actor accepts the following input parameters: ```json { "targets": [ { "country": "United States", "keyword": "rental properties" }, { "country": "Canada", "keyword": "vacation homes" } ], "adsLimit": 1000, "scrollCount": 3, "headless": true, "maxConcurrency": 1, "delay": 2000 } ```` #### Parameters - **targets** (required): Array of country-keyword pairs to scrape - **adsLimit** (optional): Maximum ads per target (default: 1000) - **scrollCount** (optional): Number of scroll actions to load more ads (default: 3) - **headless** (optional): Run browser in headless mode (default: true) - **maxConcurrency** (optional): Maximum concurrent browser instances (default: 1) - **delay** (optional): Delay between actions in milliseconds (default: 2000) ### 📊 Output Format Each scraped ad contains: ```json { "country": "United States", "keyword": "rental properties", "ads": [ { "status": "Active", "library_id": "123456789", "started": "Started running on Jan 1, 2024", "page": "Example Page", "primary_text": "Find your dream rental property...", "cta": "Learn More", "links": [ { "type": "link", "url": "https://example.com", "text": "Visit Website" } ], "image_urls": ["https://example.com/image.jpg"], "raw_text": "Full ad text content...", "scraped_at": "2024-01-01T12:00:00.000Z" } ], "ads_count": 150, "processed_at": "2024-01-01T12:00:00.000Z" } ``` ### 🛠️ Technical Details #### Architecture - **Runtime**: Node.js 18 with Playwright - **Browser**: Chromium with optimized launch arguments - **Concurrency**: Configurable batch processing - **Memory**: Optimized for low memory usage on Apify #### Key Optimizations - Single browser instance with multiple contexts - Immediate data saving to prevent loss - Progressive scroll delays to avoid rate limiting - Efficient XPath selectors for fast element detection - Minimal DOM queries with smart caching #### Error Handling - Graceful handling of missing elements - Automatic retry on transient failures - Detailed error logging for debugging - Continues processing even if individual ads fail ### 📝 Usage Examples #### Basic Usage ```json { "targets": [ {"country": "United States", "keyword": "real estate"}, {"country": "Canada", "keyword": "homes for sale"} ] } ``` #### Advanced Configuration ```json { "targets": [ {"country": "United Kingdom", "keyword": "property investment"}, {"country": "Australia", "keyword": "vacation rentals"} ], "adsLimit": 500, "scrollCount": 5, "headless": false, "maxConcurrency": 2, "delay": 3000 } ``` ### ⚠️ Important Notes 1. **Rate Limiting**: The scraper includes delays to respect Facebook's rate limits 2. **Resource Usage**: Optimized for Apify's resource constraints 3. **Data Quality**: Filters out Facebook-internal links and duplicates 4. **Authentication**: Designed to work without login (public Ad Library) *** Built with ❤️ for the Apify platform # Actor input Schema ## `targets` (type: `array`): Array of country-keyword pairs to scrape ads for ## `adsLimit` (type: `integer`): Maximum number of ads to scrape per country-keyword pair ## `scrollCount` (type: `integer`): Number of times to scroll down to load more ads ## `headless` (type: `boolean`): Run browser in headless mode for better performance ## `maxConcurrency` (type: `integer`): Maximum number of concurrent browser instances (optimize for memory) ## `delay` (type: `integer`): Delay in milliseconds between actions to avoid rate limiting ## Actor input object example ```json { "targets": [ { "country": "United States", "keyword": "rental properties" }, { "country": "Ukraine", "keyword": "rental apartments" } ], "adsLimit": 100, "scrollCount": 1, "headless": true, "maxConcurrency": 1, "delay": 2000 } ``` # 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 = { "targets": [ { "country": "United States", "keyword": "rental properties" }, { "country": "Ukraine", "keyword": "rental apartments" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("rover-omniscraper/facebook-ads-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 = { "targets": [ { "country": "United States", "keyword": "rental properties", }, { "country": "Ukraine", "keyword": "rental apartments", }, ] } # Run the Actor and wait for it to finish run = client.actor("rover-omniscraper/facebook-ads-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 '{ "targets": [ { "country": "United States", "keyword": "rental properties" }, { "country": "Ukraine", "keyword": "rental apartments" } ] }' | apify call rover-omniscraper/facebook-ads-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=rover-omniscraper/facebook-ads-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Ads Scraper", "description": "Facebook Ads Library Scraper - Lightning Fast Edition | Extract Active Facebook Ads Data Instantly. Scrape ads by country & keyword with ultra-fast HTML parsing. Perfect for marketing research, competitor analysis & lead generation. Headless browser automation with Playwright & Apify.", "version": "0.0", "x-build-id": "oss0YvZdiCJKzVh35" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/rover-omniscraper~facebook-ads-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-rover-omniscraper-facebook-ads-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/rover-omniscraper~facebook-ads-scraper/runs": { "post": { "operationId": "runs-sync-rover-omniscraper-facebook-ads-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/rover-omniscraper~facebook-ads-scraper/run-sync": { "post": { "operationId": "run-sync-rover-omniscraper-facebook-ads-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": [ "targets" ], "properties": { "targets": { "title": "Target Pairs", "type": "array", "description": "Array of country-keyword pairs to scrape ads for" }, "adsLimit": { "title": "Ads Limit", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of ads to scrape per country-keyword pair", "default": 100 }, "scrollCount": { "title": "Scroll Count", "minimum": 1, "maximum": 10, "type": "integer", "description": "Number of times to scroll down to load more ads", "default": 1 }, "headless": { "title": "Headless Mode", "type": "boolean", "description": "Run browser in headless mode for better performance", "default": true }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 3, "type": "integer", "description": "Maximum number of concurrent browser instances (optimize for memory)", "default": 1 }, "delay": { "title": "Delay Between Requests", "minimum": 1000, "maximum": 10000, "type": "integer", "description": "Delay in milliseconds between actions to avoid rate limiting", "default": 2000 } } }, "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 } } } } } } } } } } ```