# Reddit Scraper Lite — Fast Reddit Data Extraction (`oneary/reddit-scraper-lite`) Actor Lightweight Reddit scraper for fast extraction of posts, comments, and subreddit data. Minimal dependencies, maximum speed. Extract titles, scores, authors from any subreddit. - **URL**: https://apify.com/oneary/reddit-scraper-lite.md - **Developed by:** [Luan M.](https://apify.com/oneary) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 45.2% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $12.00 / 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 Lite — Fast Reddit Post Extractor Fast, lightweight Reddit scraper that extracts posts, scores, comments, flair, and metadata from subreddits and user profiles. Uses Crawlee with Playwright for reliable extraction from Reddit's JS-heavy SPA. ### Features - Extract post titles, URLs, authors, scores, comment counts, flairs, and timestamps - Works with subreddit pages, user profiles, and post listings - Handles Reddit's dynamic rendering automatically - Apify proxy integration with automatic fallback - Graceful error handling — won't crash on individual failures - Enriched output with scrape metadata (`scrapedAt`, `sourceUrl`) ### Input | Field | Type | Description | Required | |-------|------|-------------|----------| | `startUrls` | array | Reddit URLs to scrape (e.g., `https://www.reddit.com/r/programming/`) | ✅ | | `maxPosts` | integer | Maximum number of posts to extract per page (1–500, default: 25) | ❌ | | `proxyConfiguration` | object | Proxy settings to avoid rate limiting (Apify Proxy recommended) | ❌ | ### Output Each dataset item contains: | Field | Description | |-------|-------------| | `title` | Post title | | `url` | Post URL | | `author` | Reddit username | | `subreddit` | Subreddit name | | `score` | Upvote count | | `comments` | Comment count | | `flair` | Post flair text | | `postId` | Reddit post ID (t3_xxx) | | `createdAt` | Post timestamp (ISO 8601) | | `scrapedAt` | When this data was scraped (ISO 8601) | | `sourceUrl` | Page URL where this post was found | ### Usage 1. Add one or more Reddit URLs (subreddit pages, user profiles, listings) to **Start URLs**. 2. Optionally adjust **Max Posts** (default: 25, max: 500). 3. Optionally configure proxy settings (Apify Proxy recommended for larger scrapes). 4. Run the actor and retrieve results from the default dataset. ### Tips - **Use Apify Proxy** to avoid Reddit's rate limiting, especially when scraping multiple pages. - **Start small** with maxPosts=25 to test, then increase for production runs. - **Subreddit URLs** work best: `https://www.reddit.com/r/programming/`, `https://www.reddit.com/r/programming/top/`, etc. # Actor input Schema ## `startUrls` (type: `array`): Reddit URLs to scrape (e.g., https://www.reddit.com/r/programming/) ## `maxPosts` (type: `integer`): Maximum number of posts to scrape ## `proxyConfiguration` (type: `object`): Proxy settings for the scraper ## Actor input object example ```json { "startUrls": [ { "url": "https://www.reddit.com/r/programming/" } ], "maxPosts": 25, "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 = { "startUrls": [ { "url": "https://www.reddit.com/r/programming/" } ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("oneary/reddit-scraper-lite").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 = { "startUrls": [{ "url": "https://www.reddit.com/r/programming/" }], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("oneary/reddit-scraper-lite").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 '{ "startUrls": [ { "url": "https://www.reddit.com/r/programming/" } ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call oneary/reddit-scraper-lite --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=oneary/reddit-scraper-lite", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper Lite — Fast Reddit Data Extraction", "description": "Lightweight Reddit scraper for fast extraction of posts, comments, and subreddit data. Minimal dependencies, maximum speed. Extract titles, scores, authors from any subreddit.", "version": "1.1", "x-build-id": "31bc2AuBiVmMxxOwK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/oneary~reddit-scraper-lite/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-oneary-reddit-scraper-lite", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/oneary~reddit-scraper-lite/runs": { "post": { "operationId": "runs-sync-oneary-reddit-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/oneary~reddit-scraper-lite/run-sync": { "post": { "operationId": "run-sync-oneary-reddit-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "Reddit URLs to scrape (e.g., https://www.reddit.com/r/programming/)", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxPosts": { "title": "Max Posts", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of posts to scrape", "default": 25 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the scraper" } } }, "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 } } } } } } } } } } ```