# Reddit Comment Scraper (`akash9078/reddit-comment-scraper`) Actor The Reddit Comment Scraper allows you to collect comments, replies, and related metadata from Reddit with high efficiency. It supports scraping from specific post URLs, subreddit feeds, or search queries, making it ideal for data analysis, sentiment tracking, lead generation, and research. - **URL**: https://apify.com/akash9078/reddit-comment-scraper.md - **Developed by:** [Akash Kumar Naik](https://apify.com/akash9078) (community) - **Categories:** Developer tools, Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start 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 Comment Scraper API: Fast & Structured Data Extraction The **Reddit Comment Scraper API** is a production-grade Apify Actor designed for high-speed, reliable extraction of comments from any public Reddit post. Optimized for **2026 AI and Search Engine requirements**, this Actor utilizes a specialized bridge architecture to deliver structured JSON data directly to your data pipelines with sub-second processing overhead. Whether you are building **AI agents (AIO)**, performing **sentiment analysis**, or feeding **LLM training sets**, this scraper provides the cleanest and fastest path to Reddit conversational data. --- ### 🚀 Key Benefits & AI Optimization - **Sub-Second Bridge Architecture**: Unlike traditional scrapers that use heavy headless browsers (Puppeteer/Playwright), this Actor acts as an authenticated bridge to a dedicated scraping cluster, resulting in **90% faster execution** and higher reliability. - **LLM-Ready Output (GEO/AIO)**: Data is delivered in a flattened, clean JSON format, perfectly structured for **Retrieval-Augmented Generation (RAG)** and generative AI workflows. - **Pay-Per-Event Pricing (PPE)**: Maximum cost efficiency. You are only charged for successfully processed posts and the actual number of comments retrieved. - **Anti-Blocking & Network Security**: Built-in rotating proxies and browser-fingerprint emulation ensure your requests bypass "network security" blocks that often plague direct scrapers. --- ### 📥 How to Scrape Reddit Comments Using this Actor is simple and requires only a single input. #### Input Parameters | Field | Type | Description | Required | |-------|------|-------------|:---:| | `post_url` | String | The full URL of the Reddit post (e.g., `https://www.reddit.com/r/subreddit/comments/id/title/`) | ✅ | #### Sample Scraper Input ```json { "post_url": "https://www.reddit.com/r/technology/comments/1s66qgy/example_post/" } ```` *** ### 📤 Extracted Reddit Data Structure The scraper returns a rich dataset containing post metadata and a list of all comments. The output is optimized for instant visibility in the Apify Console. #### JSON Output Example ```json { "post_url": "https://www.reddit.com/r/...", "webhook_status": 200, "data": [ { "id": "odffoln", "author": "redditor_123", "body": "This is a comment from the Reddit community.", "score": 15, "created_utc": 1774923322, "permalink": "/r/subreddit/comments/.../id/" } ], "success": true, "processed_at": "2026-05-05T05:27:45.136Z" } ``` *** ### 💰 Flexible Pay-Per-Event Billing This Actor uses Apify's **Pay-Per-Event** pricing model to provide the most transparent and fair billing possible. 1. **Post Processed Event**: A base fee for successfully bridging the request. 2. **Comment Scraped Event**: A granular fee per individual comment successfully returned. *Zero results mean zero charges. You only pay for successful data delivery.* *** ### 🛠️ Advanced Integration for Developers - **REST API Access**: Integrate Reddit scraping into your own apps via standard HTTP calls. - **Webhook Support**: Seamlessly pipe data into your backend or platforms like Zapier, Make, and n8n. - **AI Agent Integration**: This Actor is fully compatible with **LlamaIndex**, **LangChain**, and other AI frameworks for building autonomous Reddit monitors. ### 📝 Support & Reliability This Actor is monitored 24/7. If you encounter any issues or have feature requests, please use the **Issues** tab in the Apify Console. *** *Optimized for SEO: Reddit Scraper, Reddit API, Extract Reddit Comments, Reddit Data Export, Sentiment Analysis Data, Reddit JSON Scraper.* # Actor input Schema ## `post_url` (type: `string`): Full URL of the Reddit post to scrape comments from (e.g., https://www.reddit.com/r/subreddit/comments/abc123/title/) ## Actor input object example ```json { "post_url": "https://www.reddit.com/r/YesIntelligent/comments/1s66qgy/elon_musks_last_cofounder_reportedly_leaves_xai/" } ``` # Actor output Schema ## `results` (type: `string`): Direct link to the scraped data items ## `post_url` (type: `string`): No description ## `success` (type: `string`): No description # 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 = { "post_url": "https://www.reddit.com/r/YesIntelligent/comments/1s66qgy/elon_musks_last_cofounder_reportedly_leaves_xai/" }; // Run the Actor and wait for it to finish const run = await client.actor("akash9078/reddit-comment-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 = { "post_url": "https://www.reddit.com/r/YesIntelligent/comments/1s66qgy/elon_musks_last_cofounder_reportedly_leaves_xai/" } # Run the Actor and wait for it to finish run = client.actor("akash9078/reddit-comment-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 '{ "post_url": "https://www.reddit.com/r/YesIntelligent/comments/1s66qgy/elon_musks_last_cofounder_reportedly_leaves_xai/" }' | apify call akash9078/reddit-comment-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=akash9078/reddit-comment-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Comment Scraper", "description": "The Reddit Comment Scraper allows you to collect comments, replies, and related metadata from Reddit with high efficiency. It supports scraping from specific post URLs, subreddit feeds, or search queries, making it ideal for data analysis, sentiment tracking, lead generation, and research.", "version": "1.0", "x-build-id": "wtPL0LiHkPVaq4nzQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/akash9078~reddit-comment-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-akash9078-reddit-comment-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/akash9078~reddit-comment-scraper/runs": { "post": { "operationId": "runs-sync-akash9078-reddit-comment-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/akash9078~reddit-comment-scraper/run-sync": { "post": { "operationId": "run-sync-akash9078-reddit-comment-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "post_url" ], "properties": { "post_url": { "title": "Reddit Post URL", "type": "string", "description": "Full URL of the Reddit post to scrape comments from (e.g., https://www.reddit.com/r/subreddit/comments/abc123/title/)", "default": "https://www.reddit.com/r/YesIntelligent/comments/1s66qgy/elon_musks_last_cofounder_reportedly_leaves_leaves_xai/" } } }, "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 } } } } } } } } } } ```