# Reddit Full Scraper (`hermesexp/reddit-scraper`) Actor Scrape Reddit posts, comments, and search results with full metadata. Get scores, awards, subreddit data, and comment threads without API key. - **URL**: https://apify.com/hermesexp/reddit-scraper.md - **Developed by:** [Dima Radov](https://apify.com/hermesexp) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Full Scraper Scrapes Reddit posts (and optionally comments) using Reddit's free public JSON API. No authentication required. Fast and lightweight — built with **httpx**, no browser, no Playwright. ### Features - **Subreddit listings** — scrape posts from any subreddit (hot, new, top, rising, controversial) - **Individual post URLs** — scrape a single post with full details - **Search queries** — search Reddit by keyword, optionally restricted to a subreddit - **Comment extraction** — optionally extract comments (including nested replies) - **Pagination** — automatically paginates through all available results up to your limit - **Time filters** — for top/controversial sorting: hour, day, week, month, year, all - **No auth required** — uses Reddit's public JSON API, no API key needed - **Rate-limit aware** — automatic retry with backoff on 429 responses ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `subredditUrls` | array of strings | `[]` | Subreddit URLs to scrape (e.g., `["https://www.reddit.com/r/python/"]`) | | `postUrls` | array of strings | `[]` | Individual post URLs (e.g., `["https://www.reddit.com/r/python/comments/abc123/"]`) | | `searchQueries` | array of strings | `[]` | Search terms to find posts | | `searchSubreddit` | string | `null` | Restrict search to a specific subreddit (e.g., `"python"`). Only used with `searchQueries`. | | `sort` | string | `"hot"` | Sort order for listings and search: `hot`, `new`, `top`, `rising`, `controversial`, `relevance` | | `timeFilter` | string | `"all"` | Time filter for top/controversial: `hour`, `day`, `week`, `month`, `year`, `all` | | `maxPosts` | integer | `100` | Maximum number of posts to scrape per subreddit/search | | `extractComments` | boolean | `false` | If true, extract comments when scraping individual post URLs | | `maxComments` | integer | `50` | Maximum number of top-level comments to extract per post | ### Output Each result is a dataset item with these fields: | Field | Type | Description | |-------|------|-------------| | `id` | string | Reddit post ID | | `subreddit` | string | Subreddit name | | `title` | string | Post title | | `author` | string | Author username | | `score` | integer | Upvote score | | `upvoteRatio` | number | Upvote ratio (e.g., 0.95) | | `numComments` | integer | Number of comments | | `content` | string | Post body text (selftext) or link URL | | `url` | string | Full Reddit post URL | | `permalink` | string | Relative permalink path | | `timestamp` | number | Unix timestamp (UTC) | | `isSelf` | boolean | Is a self/text post | | `domain` | string | Domain for link posts | | `linkFlairText` | string | Flair text | | `over18` | boolean | NSFW flag | | `spoiler` | boolean | Spoiler flag | | `stickied` | boolean | Stickied/pinned flag | | `thumbnail` | string | Thumbnail URL | | `awardCount` | integer | Total awards received | | `comments` | array | (Only if `extractComments=true`) List of comment objects with `id`, `author`, `body`, `score`, `timestamp`, `depth`, `replies` | ### Example Usage **Scrape a subreddit:** ```json { "subredditUrls": ["https://www.reddit.com/r/python/"], "sort": "top", "timeFilter": "week", "maxPosts": 50 } ```` **Scrape specific posts with comments:** ```json { "postUrls": [ "https://www.reddit.com/r/python/comments/abc123/", "https://www.reddit.com/r/javascript/comments/def456/" ], "extractComments": true, "maxComments": 100 } ``` **Search all of Reddit:** ```json { "searchQueries": ["python tutorial", "machine learning"], "sort": "relevance", "maxPosts": 25 } ``` **Search within a subreddit:** ```json { "searchQueries": ["async"], "searchSubreddit": "python", "sort": "top", "timeFilter": "year", "maxPosts": 30 } ``` ### Technical Details - Built with **httpx** (async HTTP) — fast and lightweight - Runs on `apify/actor-python:3.12` Docker image - No API key, no OAuth, no browser required - Automatically handles Reddit's rate limiting with exponential backoff - Polite pagination with small delays between requests - Supports old.reddit.com, new.reddit.com, and www.reddit.com URL formats # Actor input Schema ## `urls` (type: `array`): Subreddit URLs (e.g., https://www.reddit.com/r/wallstreetbets/), post URLs, or search queries ## `maxResults` (type: `integer`): Maximum number of posts to scrape ## `includeComments` (type: `boolean`): Whether to scrape comments for each post ## `sortBy` (type: `string`): Sort order for the subreddit posts ## Actor input object example ```json { "urls": [ "https://www.reddit.com/r/wallstreetbets/" ], "maxResults": 25, "includeComments": true, "sortBy": "hot" } ``` # 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 = { "urls": [ "https://www.reddit.com/r/wallstreetbets/" ] }; // Run the Actor and wait for it to finish const run = await client.actor("hermesexp/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 = { "urls": ["https://www.reddit.com/r/wallstreetbets/"] } # Run the Actor and wait for it to finish run = client.actor("hermesexp/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 '{ "urls": [ "https://www.reddit.com/r/wallstreetbets/" ] }' | apify call hermesexp/reddit-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hermesexp/reddit-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Full Scraper", "description": "Scrape Reddit posts, comments, and search results with full metadata. Get scores, awards, subreddit data, and comment threads without API key.", "version": "1.0", "x-build-id": "cLSqttid5XuEeRXV9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hermesexp~reddit-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hermesexp-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/hermesexp~reddit-scraper/runs": { "post": { "operationId": "runs-sync-hermesexp-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/hermesexp~reddit-scraper/run-sync": { "post": { "operationId": "run-sync-hermesexp-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": [ "urls" ], "properties": { "urls": { "title": "URLs or Search Queries", "type": "array", "description": "Subreddit URLs (e.g., https://www.reddit.com/r/wallstreetbets/), post URLs, or search queries", "items": { "type": "string" } }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of posts to scrape", "default": 25 }, "includeComments": { "title": "Include Comments", "type": "boolean", "description": "Whether to scrape comments for each post", "default": true }, "sortBy": { "title": "Sort By", "enum": [ "hot", "new", "top", "rising" ], "type": "string", "description": "Sort order for the subreddit posts", "default": "hot" } } }, "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 } } } } } } } } } } ```