# Reddit Comments Scraper: Body, Author, Score & Depth (`scrapers_lat/reddit-comments-scraper`) Actor Scrape every comment from any Reddit post or subreddit, including nested replies. Extract body text, author, score, awards, controversiality, depth and parentId to rebuild the thread. Export to JSON, CSV or Excel. No API key. - **URL**: https://apify.com/scrapers\_lat/reddit-comments-scraper.md - **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community) - **Categories:** Social media, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 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. 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/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 Comments Scraper: Body, Author, Score & Depth](https://scrapers.lat/banners/reddit-comments-scraper.png)](https://console.apify.com/actors/aufsURfBwo2u5pYqc/input) ## Reddit Comments Scraper: Body, Author, Score & Depth > Extract every comment from any Reddit post or subreddit, including deeply nested replies, with full text, author, score, awards and thread depth. **๐Ÿ“ฅ [Input](https://apify.com/scrapers_lat/reddit-comments-scraper/input-schema) ยท ๐Ÿ“ค [Output](https://apify.com/scrapers_lat/reddit-comments-scraper/output-schema) ยท ๐Ÿ’ฐ [Pricing](https://apify.com/scrapers_lat/reddit-comments-scraper/pricing) ยท โ–ถ๏ธ [Examples](https://apify.com/scrapers_lat/reddit-comments-scraper/examples)** ![Apify](https://img.shields.io/badge/Platform-Apify-1CE1CE?logo=apify&logoColor=white) ![Coverage](https://img.shields.io/badge/Coverage-All%20Reddit-blue) ![Maintained](https://img.shields.io/badge/Maintained-Yes-brightgreen) ![Output](https://img.shields.io/badge/Output-JSON%20%7C%20CSV%20%7C%20Excel-orange) ### What you get One record per comment, dedicated to comments only. The full reply tree is walked recursively, so nested replies six or more levels deep come back too, each tagged with its `depth` and `parentId` so you can rebuild the thread. - **body** the full comment text, the field that matters most - **id**, **permalink**, **createdAt**, **edited** - **author**, **authorFullname**, **isSubmitter** - **score**, **controversiality**, **totalAwards** - **postId**, **postTitle**, **subreddit** - **parentId**, **isTopLevel**, **depth**, **isStickied** - **observedAt** ### Two ways to scrape | Input | Use it for | |---|---| | `postUrls` | Pull every comment from specific Reddit threads | | `subreddits` | Pull comments from a subreddit's recent posts | Combine both in one run. `maxItems` caps the total comments (nested replies count toward it). `maxDepth` limits how deep into reply chains the actor walks (leave it empty to walk every level). `sort` controls comment ordering: best, top, new, controversial, old or Q&A. ### Example output ```json { "id": "ndjizcc", "body": "\"I think empathy is a made up New Age term...\" - Charlie Kirk", "author": "JoshHartsMilkMustach", "authorFullname": "t2_15ut8f4aap", "score": 7090, "controversiality": 0, "totalAwards": 0, "postId": "1ndskqc", "postTitle": "Why do you think President Trump ordered all US Flags at half staff...", "subreddit": "AskReddit", "parentId": "t1_ndjf38m", "isTopLevel": false, "depth": 2, "isSubmitter": false, "isStickied": false, "edited": false, "permalink": "https://www.reddit.com/r/AskReddit/comments/1ndskqc/.../ndjizcc/", "createdAt": "2025-09-10T23:29:15.000Z", "observedAt": "2026-06-26T15:14:47.391Z", "error": null } ```` ### Frequently Asked Questions **Does it capture nested replies, not just top-level comments?** Yes. The actor walks the full comment tree recursively and expands collapsed "load more comments" branches, so replies many levels deep are returned. Each record carries `depth` (0 = top level) and `parentId` so you can reconstruct the thread. **How do I get only top-level comments?** Set `maxDepth` to `0`. Set it to `1` for top-level plus direct replies, and so on. Leave it empty to walk every level. **Can I pull comments from a whole subreddit?** Yes. Pass subreddit names in `subreddits` and the actor collects comments from the subreddit's recent posts, up to your `maxItems`. **Is the full comment text included?** Yes. Every record carries the complete `body` text. Comments that Reddit has deleted or removed (which have no text) are skipped so the body is always present. **Do I need a proxy or API key?** No API key. The actor uses residential proxies by default, so you do not need to configure anything. You can supply your own proxy configuration if you prefer. ### Example use cases Ready-to-run example tasks, each preconfigured for a common scenario. Open one and press run, or use it as a template: - [Reddit AskReddit Top Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-askreddit-top): Scrape top comments from r/AskReddit threads with author, score, depth and timestamp. - [Reddit AmItheAsshole Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-aita-verdicts): Scrape r/AmItheAsshole comment threads with verdicts, author, score and depth. - [Reddit WallStreetBets Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-wallstreetbets): Scrape r/wallstreetbets discussion comments with author, score and timestamp for market sentiment. - [Reddit Technology Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-technology-news): Scrape r/technology comment threads with author, score and depth for tech opinion mining. - [Reddit PersonalFinance Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-personalfinance): Scrape r/personalfinance advice comments with author, score and depth. - [Reddit Relationship Advice Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-relationship-advice): Scrape r/relationship\_advice comment threads with author, score, depth and timestamp. - [Reddit BuildAPC Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-buildapc): Scrape r/buildapc comments with author, score and depth for PC hardware recommendations. - [Reddit SkincareAddiction Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-skincareaddiction): Scrape r/SkincareAddiction comments with author, score and depth for product mentions. - [Reddit Gaming Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-gaming-discussion): Scrape r/gaming comment threads with author, score, depth and timestamp for game sentiment. - [Reddit ELI5 Comments](https://apify.com/scrapers_lat/reddit-comments-scraper/examples/reddit-comments-explainlikeimfive): Scrape r/explainlikeimfive top explanations and comments with author, score and depth. ### Export, API and AI agents (x402 + MCP) Export the scraped data to **JSON, CSV or Excel**, pull it as a **dataset** through the Apify **API**, or wire it into your app with **no code**. This web scraper and data extractor also works for bulk data extraction and scheduled runs. For AI agents: this Actor is available on **x402**, Apify's agentic payment standard built with Coinbase. An AI agent can discover, pay for and run it on its own with a funded wallet and a single HTTP request: no account, no subscription, no API key and no human in the loop. It also runs as an **MCP** tool inside Claude, Cursor and other AI clients out of the box. Learn more about [x402 agentic payments on Apify](https://docs.apify.com/platform/integrations/x402). ### Related scrapers Need data from the same space? Here are other scrapers we build and maintain: - [Reddit Posts & Comments Scraper](https://apify.com/scrapers_lat/reddit-scraper): Extract Reddit posts and comments from subreddits and search results using the public Reddit feeds. - [X (Twitter) Profiles & Tweets Scraper](https://apify.com/scrapers_lat/x-twitter-scraper): Extract public X (Twitter) tweets by tweet ID: text, author, likes, replies, media and timestamps. - [Instagram Profile & Posts Scraper](https://apify.com/scrapers_lat/instagram-scraper): Extract public Instagram profiles and recent posts by username without login. - [YouTube Scraper](https://apify.com/scrapers_lat/youtube-scraper): Scrape YouTube videos and channels by search query, video URL or channel URL. - [TikTok Creative Center Top Ads Scraper](https://apify.com/scrapers_lat/tiktok-creative-center-scraper): Scrape top-performing TikTok ads from the public Creative Center by country, time period and more. - [App Store Reviews Scraper](https://apify.com/scrapers_lat/app-store-reviews-scraper): Extract Apple App Store reviews and ratings for any app by id, URL or search term. ### More scrapers at scrapers.lat This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for Latin American and US public platforms: real estate, jobs, e-commerce, company registries and government data. Browse the full catalog, see live sample output for each one, or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat). *** > This actor is an independent tool and has no affiliation with Reddit Inc. It only accesses data that is publicly available on Reddit. Use it in accordance with Reddit's terms of service. # Actor input Schema ## `maxComments` (type: `integer`): Maximum number of comments to collect. Optional. ## `maxDepth` (type: `integer`): How deep to walk reply threads. 0 = top-level comments only, 1 = top-level plus direct replies, and so on. Leave empty to walk every level. ## `postUrls` (type: `array`): Reddit post permalinks to pull comments from (https://www.reddit.com/r//comments//...). ## `subreddits` (type: `array`): Subreddit names (with or without r/) to pull comments from their recent posts. ## `sort` (type: `string`): How to sort comments within each post. ## Actor input object example ```json { "maxComments": 50, "postUrls": [ "https://www.reddit.com/r/AskReddit/comments/1ndskqc/" ], "subreddits": [], "sort": "top" } ``` # Actor output Schema ## `results` (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 = { "maxComments": 50, "postUrls": [ "https://www.reddit.com/r/AskReddit/comments/1ndskqc/" ], "subreddits": [] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapers_lat/reddit-comments-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "maxComments": 50, "postUrls": ["https://www.reddit.com/r/AskReddit/comments/1ndskqc/"], "subreddits": [], } # Run the Actor and wait for it to finish run = client.actor("scrapers_lat/reddit-comments-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxComments": 50, "postUrls": [ "https://www.reddit.com/r/AskReddit/comments/1ndskqc/" ], "subreddits": [] }' | apify call scrapers_lat/reddit-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers_lat/reddit-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Comments Scraper: Body, Author, Score & Depth", "description": "Scrape every comment from any Reddit post or subreddit, including nested replies. Extract body text, author, score, awards, controversiality, depth and parentId to rebuild the thread. Export to JSON, CSV or Excel. No API key.", "version": "0.1", "x-build-id": "vvVHGJWTXc2AV6b4n" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers_lat~reddit-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers_lat-reddit-comments-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapers_lat~reddit-comments-scraper/runs": { "post": { "operationId": "runs-sync-scrapers_lat-reddit-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapers_lat~reddit-comments-scraper/run-sync": { "post": { "operationId": "run-sync-scrapers_lat-reddit-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "maxComments": { "title": "Max comments", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Maximum number of comments to collect. Optional." }, "maxDepth": { "title": "Max reply depth", "minimum": 0, "maximum": 100, "type": "integer", "description": "How deep to walk reply threads. 0 = top-level comments only, 1 = top-level plus direct replies, and so on. Leave empty to walk every level." }, "postUrls": { "title": "Post URLs", "type": "array", "description": "Reddit post permalinks to pull comments from (https://www.reddit.com/r//comments//...).", "items": { "type": "string" } }, "subreddits": { "title": "Subreddits", "type": "array", "description": "Subreddit names (with or without r/) to pull comments from their recent posts.", "items": { "type": "string" } }, "sort": { "title": "Comment sort", "enum": [ "best", "top", "new", "controversial", "old", "qa" ], "type": "string", "description": "How to sort comments within each post.", "default": "top" } } }, "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 } } } } } } } } } } ```