# Reddit Posts Scraper (`data_ops_main/reddit-posts-scraper`) Actor Scrapes Reddit posts and comments by searching Google with `site:reddit.com` queries. No Reddit API key needed. Outputs structured post data including title, score, upvote ratio, comments, and top-level replies. - **URL**: https://apify.com/data\_ops\_main/reddit-posts-scraper.md - **Developed by:** [yourlocalhost](https://apify.com/data_ops_main) (community) - **Categories:** Social media, Developer tools, Automation - **Stats:** 16 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 reddit actors 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 Posts Scraper Scrapes **Reddit** posts and comments by searching Google with `site:reddit.com` queries. **No Reddit API key needed.** Outputs structured post data including title, score, upvote ratio, comments, and top-level replies. ### What it does This Actor bypasses Reddit's restrictive API by leveraging Google search with `site:reddit.com` queries. For each keyword, it finds the top Reddit posts via Google, then navigates to each Reddit page using Playwright to extract the full post data — title, author, score, upvote ratio, comment count, subreddit, flair, and a configurable number of top-level comments. No Reddit API credentials required. #### Use cases - **Community sentiment analysis** — understand what real people say about your product or brand - **Trend & product discovery** — mine subreddit discussions for emerging products and ideas - **Brand monitoring** — track mentions across Reddit communities - **Content research** — find popular topics, pain points, and frequently asked questions - **Competitive intelligence** — read honest user reviews and product recommendations ### Input | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `keywords` | array | **Yes** | — | Search keywords — each triggers a `site:reddit.com` Google search | | `maxPostsPerKeyword` | integer | No | `10` | Max Reddit posts per keyword (1–100) | | `maxTopComments` | integer | No | `10` | Max top-level comments per post (0–50) | | `proxyConfiguration` | object | No | No proxy | Apify Proxy — recommended to avoid Google rate limiting | #### Example input ```json { "keywords": ["trends 2025", "best laptops 2024"], "maxPostsPerKeyword": 10, "maxTopComments": 5 } ```` ### Output Each Reddit post is pushed as a separate record to the Apify dataset. | Field | Type | Description | |-------|------|-------------| | `keyword` | string | The search keyword that found this post | | `subreddit` | string | Subreddit name (e.g. `"r/laptops"`) | | `title` | string | Post title | | `author` | string | Post author (e.g. `"u/techreviewer"`) | | `score` | number | Post score (upvotes − downvotes) | | `upvoteRatio` | number | Upvote ratio (0.0–1.0) | | `numComments` | number | Total comment count | | `createdUtc` | string | Post creation date (UTC) | | `flair` | string | Post flair/tag | | `url` | string | Full post URL | | `permalink` | string | Reddit permalink path | | `topComments` | array | Top-level comment texts | | `extracted_at` | string | ISO 8601 date-time of extraction | #### Example output ```json { "keyword": "best laptops 2024", "subreddit": "r/laptops", "title": "What are the best laptops for programming in 2024?", "author": "u/techreviewer", "score": 1842, "upvoteRatio": 0.96, "numComments": 432, "createdUtc": "2024-11-15T08:30:00Z", "flair": "Discussion", "url": "https://www.reddit.com/r/laptops/comments/abc123", "permalink": "/r/laptops/comments/abc123/what_are_the_best_laptops", "topComments": [ "ThinkPad X1 Carbon is unbeatable for dev work", "MacBook Pro M3 if you can afford it", "Framework Laptop 16 for repairability", "Dell XPS 15 still going strong", "Check out the ASUS Zenbook 14 OLED" ], "extracted_at": "2026-03-06T14:30:00.000Z" } ``` ### How to run #### On Apify Platform 1. Go to the Actor's page on [Apify Console](https://console.apify.com) 2. Enter your search keywords and configure limits 3. Click **Start** and wait for the run to finish 4. Download results from the **Dataset** tab in JSON, CSV, or Excel format #### Locally ```bash apify run ``` ### Deploy to Apify ```bash apify login apify push ``` ### Built with - [Apify SDK](https://docs.apify.com/sdk/js/) — actor framework and dataset management - [Playwright](https://playwright.dev/) — browser automation for Google search and Reddit page scraping # Actor input Schema ## `keywords` (type: `array`): List of keywords to search for Reddit posts. Each keyword triggers a Google search with 'site:reddit.com "keyword"'. ## `maxPostsPerKeyword` (type: `integer`): Maximum number of Reddit posts to scrape per keyword. ## `maxTopComments` (type: `integer`): Maximum number of top-level comments to extract per post. ## `proxyConfiguration` (type: `object`): Apify Proxy configuration. Recommended for production to avoid Google rate limiting. ## Actor input object example ```json { "keywords": [ "trends 2025", "best laptops 2024" ], "maxPostsPerKeyword": 10, "maxTopComments": 10, "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 = { "keywords": [ "trends 2025", "best laptops 2024" ] }; // Run the Actor and wait for it to finish const run = await client.actor("data_ops_main/reddit-posts-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 = { "keywords": [ "trends 2025", "best laptops 2024", ] } # Run the Actor and wait for it to finish run = client.actor("data_ops_main/reddit-posts-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 '{ "keywords": [ "trends 2025", "best laptops 2024" ] }' | apify call data_ops_main/reddit-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_ops_main/reddit-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Posts Scraper", "description": "Scrapes Reddit posts and comments by searching Google with `site:reddit.com` queries. No Reddit API key needed. Outputs structured post data including title, score, upvote ratio, comments, and top-level replies.", "version": "1.0", "x-build-id": "41CC7cdat2X8KyD8j" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_ops_main~reddit-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_ops_main-reddit-posts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_ops_main~reddit-posts-scraper/runs": { "post": { "operationId": "runs-sync-data_ops_main-reddit-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_ops_main~reddit-posts-scraper/run-sync": { "post": { "operationId": "run-sync-data_ops_main-reddit-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "Search Keywords", "type": "array", "description": "List of keywords to search for Reddit posts. Each keyword triggers a Google search with 'site:reddit.com \"keyword\"'.", "default": [ "trends 2025" ], "items": { "type": "string" } }, "maxPostsPerKeyword": { "title": "Max Posts Per Keyword", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of Reddit posts to scrape per keyword.", "default": 10 }, "maxTopComments": { "title": "Max Top Comments", "minimum": 0, "maximum": 50, "type": "integer", "description": "Maximum number of top-level comments to extract per post.", "default": 10 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Apify Proxy configuration. Recommended for production to avoid Google rate limiting.", "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 } } } } } } } } } } ```