# Reddit Promoted Posts Scraper (`codingfrontend/reddit-ad-library-scraper`) Actor Collects promoted (sponsored) posts from Reddit feeds — advertiser, title, ad text, destination, CTA, media, and campaign metadata. - **URL**: https://apify.com/codingfrontend/reddit-ad-library-scraper.md - **Developed by:** [Coding Frontned](https://apify.com/codingfrontend) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 ## Reddit Promoted Posts Scraper Apify actor to scrape promoted ad posts (sponsored content) from the Reddit feed. Uses Reddit's `` custom HTML elements to extract rich ad data including advertiser info, campaign IDs, country codes, and media URLs. > **Note**: Reddit does not expose a public ad library like Google or Meta. This actor scrapes promoted posts directly from the live Reddit feed (homepage and subreddits). Results depend on which ads Reddit shows to the browser session at scrape time. ### Features - Extracts promoted posts from the Reddit feed using `` elements - Captures advertiser name, ad title, body text, subreddit, and CTA - Collects media URLs (images/videos), outbound link URLs, and destination domain - Returns campaign IDs, post IDs, and country codes from ad attributes - Optional keyword filter to match ads by advertiser or ad text - Automatic scrolling to load more promoted posts - Proxy support for reliable scraping ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `query` | string | `""` | Optional keyword to filter ads (matches advertiser name or ad text). Leave empty for all promoted posts. | | `maxItems` | integer | `50` | Maximum number of promoted posts to scrape (1–500) | | `proxyConfiguration` | object | Apify Proxy | Proxy settings for the crawler | #### Example Input ```json { "query": "technology", "maxItems": 10 } ```` ### Output Each scraped promoted post contains: | Field | Type | Description | |-------|------|-------------| | `position` | integer | Result position index | | `advertiserName` | string | Reddit username of the advertiser | | `advertiserProfileUrl` | string | URL to the advertiser's Reddit profile | | `adTitle` | string | Headline / title of the promoted post | | `adText` | string | Body copy of the ad | | `destinationDomain` | string | Domain of the ad landing page | | `outboundLinkUrl` | string | Full click-through URL (may be a tracking URL) | | `ctaText` | string | Call-to-action button text (e.g. "Learn More") | | `adType` | string | Ad type attribute (e.g. "display") | | `mediaUrl` | string | URL of the ad image or video creative | | `subreddit` | string | Subreddit where the ad was shown | | `createdAt` | string | Timestamp from the ad element | | `permalink` | string | Reddit permalink to the promoted post | | `postId` | string | Reddit post ID (e.g. "t3\_abc123") | | `campaignId` | string | Advertiser campaign ID | | `countryCode` | string | Country code from the ad attributes | | `scrapedAt` | string | ISO timestamp of when the data was scraped | #### Example Output ```json { "position": 1, "advertiserName": "example-brand", "advertiserProfileUrl": "https://www.reddit.com/user/example-brand/", "adTitle": "Your creation. Your timestamp. Your proof.", "adText": "Secure your creative work with blockchain timestamps.", "destinationDomain": "example.com", "outboundLinkUrl": "https://alb.reddit.com/cr?creative_id=...", "ctaText": "Learn More", "adType": "display", "mediaUrl": "https://preview.redd.it/example-ad-image.png", "subreddit": "technology", "createdAt": "2025-01-15T10:00:00.000Z", "permalink": "https://www.reddit.com/r/technology/comments/abc123/", "postId": "t3_abc123", "campaignId": "2491339872271957999", "countryCode": "US", "scrapedAt": "2025-01-15T10:30:00.000Z" } ``` ### Usage #### Apify Console 1. Go to the actor's page on Apify Console 2. Set the input parameters 3. Click "Start" #### API ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_TOKEN' }); const run = await client.actor('your-username/reddit-ad-library-scraper').call({ query: 'technology', maxItems: 50, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Local Development ```bash npm install npm start ``` ### Project Structure ``` src/ ├── main.js # Actor entry point — reads input, configures crawler ├── constants.js # Shared constants (URLs, selectors, limits) ├── routes.js # Crawler route handlers (SEARCH) └── utils/ ├── extraction.js # Ad data extraction from page DOM └── scrolling.js # Infinite scroll / load-more helpers ``` # Actor input Schema ## `subreddits` (type: `array`): Subreddit names to also scrape (homepage always included). ## `query` (type: `string`): Optional filter: only keep ads where advertiser name, title, or text contains this keyword. ## `maxItems` (type: `integer`): Max promoted posts to collect. ## `proxyConfiguration` (type: `object`): Proxy settings for the crawler. Use Apify Proxy or custom proxies. ## Actor input object example ```json { "subreddits": [], "query": "", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "subreddits": [], "query": "", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("codingfrontend/reddit-ad-library-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 = { "subreddits": [], "query": "", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("codingfrontend/reddit-ad-library-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 '{ "subreddits": [], "query": "", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true } }' | apify call codingfrontend/reddit-ad-library-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codingfrontend/reddit-ad-library-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Promoted Posts Scraper", "description": "Collects promoted (sponsored) posts from Reddit feeds — advertiser, title, ad text, destination, CTA, media, and campaign metadata.", "version": "1.0", "x-build-id": "diBGYmEkxAU3SYsu5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codingfrontend~reddit-ad-library-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codingfrontend-reddit-ad-library-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/codingfrontend~reddit-ad-library-scraper/runs": { "post": { "operationId": "runs-sync-codingfrontend-reddit-ad-library-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/codingfrontend~reddit-ad-library-scraper/run-sync": { "post": { "operationId": "run-sync-codingfrontend-reddit-ad-library-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "subreddits": { "title": "Subreddits", "type": "array", "description": "Subreddit names to also scrape (homepage always included).", "default": [], "items": { "type": "string" } }, "query": { "title": "Keyword Filter", "type": "string", "description": "Optional filter: only keep ads where advertiser name, title, or text contains this keyword.", "default": "" }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 500, "type": "integer", "description": "Max promoted posts to collect.", "default": 50 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the crawler. Use Apify Proxy or custom proxies." } } }, "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 } } } } } } } } } } ```