# Reddit Scraper (`moving_beacon-owner1/my-actor-55`) Actor Easily collect Reddit data from multiple subreddits with support for sorting, image extraction, links, flair, and safe rate-limited scraping. Multi-subreddit scraping Images, links, and metadata No API key required Safe & reliable - **URL**: https://apify.com/moving\_beacon-owner1/my-actor-55.md - **Developed by:** [Jamshaid Arif](https://apify.com/moving_beacon-owner1) (community) - **Categories:** Social media, Developer tools, Automation - **Stats:** 4 total users, 3 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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. 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 Scraper β€” Apify Actor Scrape posts, images, and metadata from any public subreddit using Reddit's built-in feeds. Zero API keys required β€” just provide subreddit names and go. --- ### Features | Capability | Description | |---|---| | **Multi-subreddit** | Scrape many subreddits in a single run | | **Sort options** | Hot, New, Top, Rising | | **Image extraction** | Pulls direct URLs from `i.redd.it` and `preview.redd.it` | | **Link extraction** | Optionally collects all external links in post bodies | | **Flair / category** | Captures post flair when available | | **Content snippet** | Plain-text preview of post body (500 chars) | | **Image-only filter** | Optionally skip text-only posts | | **Rate-limit safe** | Configurable delay between subreddit requests | | **Error resilient** | Gracefully handles 404, 403, 429 per-subreddit | --- ### Input Parameters | Field | Type | Default | Description | |---|---|---|---| | `subreddits` | `string[]` | `["Python"]` | Subreddit names (no `r/` prefix) | | `sort` | `string` | `hot` | `hot`, `new`, `top`, or `rising` | | `maxPostsPerSubreddit` | `integer` | `25` | Posts per subreddit (max ~100) | | `extractImages` | `boolean` | `true` | Parse and collect image URLs | | `onlyWithImages` | `boolean` | `false` | Skip posts without images | | `extractLinks` | `boolean` | `false` | Collect external links from post body | | `requestDelay` | `number` | `1.0` | Seconds between subreddit fetches | | `proxyConfiguration` | `object` | β€” | Apify proxy settings | #### Example Input ```json { "subreddits": ["EarthPorn", "CityPorn", "ArchitecturePorn"], "sort": "top", "maxPostsPerSubreddit": 50, "extractImages": true, "onlyWithImages": true, "requestDelay": 1.5 } ```` *** ### Output Each record in the dataset: ```json { "subreddit": "EarthPorn", "title": "Misty morning in the Swiss Alps [OC] [4000x3000]", "url": "https://www.reddit.com/r/EarthPorn/comments/...", "author": "/u/photographer_jane", "updated": "2026-03-30T14:22:00+00:00", "category": "OC", "images": [ "https://i.redd.it/abc123.jpg" ], "imageCount": 1, "contentSnippet": "Taken last week near Lauterbrunnen valley…", "sort": "top", "externalLinks": ["https://example.com/full-gallery"] } ``` > `externalLinks` is only present when `extractLinks` is enabled. A `RUN_SUMMARY` key is written to the key-value store with per-subreddit counts. *** ### Usage via Apify API ```bash curl -X POST "https://api.apify.com/v2/acts//runs?token=" \ -H "Content-Type: application/json" \ -d '{ "subreddits": ["Python", "MachineLearning"], "sort": "hot", "maxPostsPerSubreddit": 25 }' ``` *** ### License MIT # Actor input Schema ## `subreddits` (type: `array`): List of subreddit names to scrape (without the r/ prefix). Each subreddit is fetched independently. ## `sort` (type: `string`): How posts are sorted within each subreddit. ## `maxPostsPerSubreddit` (type: `integer`): Maximum number of posts to fetch from each subreddit. Reddit RSS caps at ~100. ## `extractImages` (type: `boolean`): Parse post content to extract direct image URLs (i.redd.it, preview.redd.it). ## `onlyWithImages` (type: `boolean`): If enabled, only posts that contain at least one image are included in the dataset. ## `extractLinks` (type: `boolean`): Parse post content to extract all external URLs found in the post body. ## `requestDelay` (type: `number`): Delay between subreddit requests to respect rate limits. ## `proxyConfiguration` (type: `object`): Apify proxy configuration. Useful if requests are being rate-limited. ## Actor input object example ```json { "subreddits": [ "Python", "MachineLearning", "technology" ], "sort": "hot", "maxPostsPerSubreddit": 25, "extractImages": true, "onlyWithImages": false, "extractLinks": false, "requestDelay": 1, "proxyConfiguration": { "useApifyProxy": false } } ``` # 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": [ "Python", "MachineLearning", "technology" ], "sort": "hot", "maxPostsPerSubreddit": 25, "extractImages": true, "onlyWithImages": false, "extractLinks": false, "requestDelay": 1, "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("moving_beacon-owner1/my-actor-55").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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": [ "Python", "MachineLearning", "technology", ], "sort": "hot", "maxPostsPerSubreddit": 25, "extractImages": True, "onlyWithImages": False, "extractLinks": False, "requestDelay": 1, "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("moving_beacon-owner1/my-actor-55").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "subreddits": [ "Python", "MachineLearning", "technology" ], "sort": "hot", "maxPostsPerSubreddit": 25, "extractImages": true, "onlyWithImages": false, "extractLinks": false, "requestDelay": 1, "proxyConfiguration": { "useApifyProxy": false } }' | apify call moving_beacon-owner1/my-actor-55 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=moving_beacon-owner1/my-actor-55", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper", "description": "Easily collect Reddit data from multiple subreddits with support for sorting, image extraction, links, flair, and safe rate-limited scraping.\nMulti-subreddit scraping\nImages, links, and metadata\nNo API key required\nSafe & reliable", "version": "0.0", "x-build-id": "AO29UKi6W0NpupueO" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/moving_beacon-owner1~my-actor-55/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-moving_beacon-owner1-my-actor-55", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/moving_beacon-owner1~my-actor-55/runs": { "post": { "operationId": "runs-sync-moving_beacon-owner1-my-actor-55", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/moving_beacon-owner1~my-actor-55/run-sync": { "post": { "operationId": "run-sync-moving_beacon-owner1-my-actor-55", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "subreddits" ], "properties": { "subreddits": { "title": "Subreddits", "type": "array", "description": "List of subreddit names to scrape (without the r/ prefix). Each subreddit is fetched independently.", "default": [ "Python" ], "items": { "type": "string" } }, "sort": { "title": "Sort Order", "enum": [ "hot", "new", "top", "rising" ], "type": "string", "description": "How posts are sorted within each subreddit.", "default": "hot" }, "maxPostsPerSubreddit": { "title": "Max Posts per Subreddit", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of posts to fetch from each subreddit. Reddit RSS caps at ~100.", "default": 25 }, "extractImages": { "title": "Extract Images", "type": "boolean", "description": "Parse post content to extract direct image URLs (i.redd.it, preview.redd.it).", "default": true }, "onlyWithImages": { "title": "Only Posts with Images", "type": "boolean", "description": "If enabled, only posts that contain at least one image are included in the dataset.", "default": false }, "extractLinks": { "title": "Extract External Links", "type": "boolean", "description": "Parse post content to extract all external URLs found in the post body.", "default": false }, "requestDelay": { "title": "Request Delay (seconds)", "minimum": 0.5, "maximum": 10, "type": "number", "description": "Delay between subreddit requests to respect rate limits.", "default": 1 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Apify proxy configuration. Useful if requests are being rate-limited.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```