# Reddit Scraper - Posts, Comments, Scores & Subreddits (`thirdwatch/reddit-scraper`) Actor Scrape Reddit posts, comments, and subreddits. Search globally or within specific subreddits. Get post title, body, score, comments, author, flair, awards, and media URLs. Ultra-fast HTTP-only scraper using Reddit's built-in JSON API. - **URL**: https://apify.com/thirdwatch/reddit-scraper.md - **Developed by:** [Thirdwatch](https://apify.com/thirdwatch) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.70 / 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 ## Reddit Scraper - Posts, Comments, Scores & Subreddits > Scrape Reddit posts, comments, and subreddits. Search globally or browse specific subreddits with full pagination. ### What you get Extract structured Reddit data including post content, scores, comments, media, awards, and flair. Search across all of Reddit by keyword or browse specific subreddits. Optionally fetch top comments for each post. ### Output fields | Field | Description | |-------|-------------| | `title` | Post title | | `author` | Post author | | `subreddit` | Subreddit name | | `url` | External URL (if link post) | | `permalink` | Reddit post URL | | `selftext` | Post body text | | `score` | Net upvotes | | `upvoteRatio` | Percentage of upvotes | | `numComments` | Comment count | | `created` | Post timestamp | | `isNSFW` | NSFW flag | | `mediaUrl` | Media URL (images, videos) | | `awards` | Awards received | | `flair` | Post flair | | `topComments` | Top comments (when enabled) | ### Example output ```json { "title": "I built a web scraper that...", "author": "username123", "subreddit": "programming", "url": "https://example.com/article", "permalink": "https://www.reddit.com/r/programming/comments/1jx3abc/...", "selftext": "Full post body text here...", "score": 1542, "upvoteRatio": 0.95, "numComments": 87, "created": "2026-04-10T14:30:00+00:00", "flair": "Discussion" } ```` ### Input parameters | Parameter | Required | Description | |-----------|----------|-------------| | `queries` | Yes | Search terms or subreddit names (prefix with `r/` for subreddits) | | `searchType` | No | "posts" or "subreddits" (default: posts) | | `sort` | No | Sort: hot, new, top, rising, relevance (default: hot) | | `timeFilter` | No | Time range for top/relevance: hour, day, week, month, year, all | | `maxResults` | No | Max posts per query, up to 1,000 (default: 100) | | `includeComments` | No | Fetch top comments per post (default: false) | ### Use cases - **Market researchers**: Track brand mentions and sentiment across subreddits - **Content creators**: Find trending topics and popular discussions - **Community managers**: Monitor subreddit activity and engagement - **Product teams**: Gather user feedback and feature requests - **Academic researchers**: Study online communities and discourse ### Limitations - Up to 1,000 results per query (Reddit API limit) - Including comments adds ~2 seconds per post - Private subreddits are not accessible # Actor input Schema ## `queries` (type: `array`): List of search terms or subreddit names. For subreddits, prefix with 'r/' (e.g., 'r/python'). For global search, just type keywords (e.g., 'web scraping'). Examples: \['r/programming', 'python async', 'r/datascience']. ## `searchType` (type: `string`): What to search for. 'posts' searches for posts (default). 'subreddits' browses subreddit listings. ## `sort` (type: `string`): How to sort results. 'hot' = trending now, 'new' = most recent, 'top' = highest score, 'rising' = gaining traction, 'relevance' = best match (search only). ## `timeFilter` (type: `string`): Time range for 'top' and 'relevance' sort. Only applies when sort is 'top' or 'relevance'. ## `maxResults` (type: `integer`): Maximum number of posts to return per query. ## `includeComments` (type: `boolean`): Fetch top-level comments for each post. Adds ~2 seconds per post due to rate limiting. Disabled by default. ## Actor input object example ```json { "queries": [ "r/programming" ], "searchType": "posts", "sort": "hot", "timeFilter": "all", "maxResults": 100, "includeComments": 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 = { "queries": [ "r/programming" ], "maxResults": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("thirdwatch/reddit-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 = { "queries": ["r/programming"], "maxResults": 100, } # Run the Actor and wait for it to finish run = client.actor("thirdwatch/reddit-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 '{ "queries": [ "r/programming" ], "maxResults": 100 }' | apify call thirdwatch/reddit-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=thirdwatch/reddit-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper - Posts, Comments, Scores & Subreddits", "description": "Scrape Reddit posts, comments, and subreddits. Search globally or within specific subreddits. Get post title, body, score, comments, author, flair, awards, and media URLs. Ultra-fast HTTP-only scraper using Reddit's built-in JSON API.", "version": "1.0", "x-build-id": "0H1pdgfEFbgfMBdBm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/thirdwatch~reddit-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-thirdwatch-reddit-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/thirdwatch~reddit-scraper/runs": { "post": { "operationId": "runs-sync-thirdwatch-reddit-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/thirdwatch~reddit-scraper/run-sync": { "post": { "operationId": "run-sync-thirdwatch-reddit-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": [ "queries" ], "properties": { "queries": { "title": "Search Queries or Subreddits", "type": "array", "description": "List of search terms or subreddit names. For subreddits, prefix with 'r/' (e.g., 'r/python'). For global search, just type keywords (e.g., 'web scraping'). Examples: ['r/programming', 'python async', 'r/datascience'].", "default": [], "items": { "type": "string" } }, "searchType": { "title": "Search Type", "enum": [ "posts", "subreddits" ], "type": "string", "description": "What to search for. 'posts' searches for posts (default). 'subreddits' browses subreddit listings.", "default": "posts" }, "sort": { "title": "Sort Order", "enum": [ "hot", "new", "top", "rising", "relevance" ], "type": "string", "description": "How to sort results. 'hot' = trending now, 'new' = most recent, 'top' = highest score, 'rising' = gaining traction, 'relevance' = best match (search only).", "default": "hot" }, "timeFilter": { "title": "Time Filter", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Time range for 'top' and 'relevance' sort. Only applies when sort is 'top' or 'relevance'.", "default": "all" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of posts to return per query.", "default": 100 }, "includeComments": { "title": "Include Top Comments", "type": "boolean", "description": "Fetch top-level comments for each post. Adds ~2 seconds per post due to rate limiting. Disabled by default.", "default": 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 } } } } } } } } } } ```