# Reddit Post Comments Scraper | $2.5/1K Comments (`ethereal_wool/reddit-post-comments`) Actor Extract Reddit post comments data — title, author, engagement, and more. Scrape by keyword, URL or ID. Export to JSON, CSV & Excel, use the API, schedule runs and integrate. No code required. - **URL**: https://apify.com/ethereal\_wool/reddit-post-comments.md - **Developed by:** [Jackie Chen](https://apify.com/ethereal_wool) (community) - **Categories:** Social media, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $2.50 / 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 Post Comments Scraper ![reddit-post-comments](https://api.apify.com/v2/key-value-stores/48FFrfZnw5XqzUC1C/records/reddit-post-comments__hero) Scrape the **full comment forest of any Reddit post**. Give one or more post IDs and the Actor returns one clean, structured item per comment: the comment text (markdown), score, author, depth, parent ID, timestamps, and removed / locked / stickied flags. It can optionally follow "load more replies" to expand deep nested threads and attach the post's metadata to every comment. > **Unofficial.** This Actor is not affiliated with, authorized, or endorsed by Reddit, Inc. > It is an independent tool that retrieves publicly available data via a third-party API. > Use it in compliance with Reddit's terms and all applicable laws; you are responsible for > how you use the retrieved data. ### What it does - **Comment forest** — for each post, fetches the comment tree sorted by Best / Top / New / Controversial / Old / Q&A. - **Nested replies (optional)** — follows each thread's "load more replies" cursor to pull deeper comments that aren't in the initial response. - **Post metadata (optional)** — fetches the post's title, subreddit, author, score and comment count once and attaches a `post` object to every comment item. ### Input | Field | Type | Default | Description | |---|---|---|---| | `postIds` | string[] | `["t3_bawfcs"]` | Reddit post fullnames (`t3_…`). A bare id or a full post URL is also accepted. | | `sortType` | enum | `CONFIDENCE` | `CONFIDENCE` (Best) / `TOP` / `NEW` / `CONTROVERSIAL` / `OLD` / `QA`. | | `maxItems` | integer | `50` | Max total comments across all posts. | | `expandReplies` | boolean | `false` | Follow "load more" cursors to fetch deeper nested replies. | | `includePostInfo` | boolean | `false` | Attach post metadata (title, subreddit, author, score) to each comment. | #### Example input ```json { "postIds": ["t3_bawfcs", "https://www.reddit.com/r/AskReddit/comments/abc123/some_thread/"], "sortType": "TOP", "maxItems": 500, "expandReplies": true, "includePostInfo": true } ```` ### Output One dataset item per comment: ```json { "id": "t1_ekf5nop", "postId": "t3_bawfcs", "parentId": null, "depth": 0, "childCount": 12, "content": "There was one I saw a while ago where it was ...", "score": 3633, "author": "Cobalt-Royal", "authorId": "t2_pr5g8", "createdAt": "2019-04-08T21:29:42.750000+0000", "editedAt": "2019-04-09T00:06:28.303000+0000", "isRemoved": false, "isLocked": false, "isStickied": false, "isArchived": true, "distinguishedAs": null, "permalink": "/r/AskReddit/comments/bawfcs/.../ekf5nop/", "url": "https://www.reddit.com/r/AskReddit/comments/bawfcs/.../ekf5nop/", "hasMoreReplies": true, "post": { "id": "t3_bawfcs", "title": "What's the creepiest Ask Reddit thread you have come across?", "subreddit": "r/AskReddit", "author": null, "score": null, "commentCount": 1234 } } ``` (`post` is present only when `includePostInfo` is enabled.) ### Notes - Comment IDs are de-duplicated within a run. - Data is sourced live; Reddit's edge occasionally rate-limits, so the Actor retries transient blocks with exponential backoff. - `post_id` must reference the `t3_` post fullname; the Actor normalizes bare ids and URLs for you. ### Quick start 1. Open the Actor and press **Run** — the default input works out of the box. 2. Adjust the input fields below to your target (keywords, IDs, or URLs) and set `maxItems` to cap spend. 3. Grab results from the **Dataset** tab as JSON / CSV / Excel, or pull them via the [Apify API](https://docs.apify.com/api/v2) and MCP from your own code. No proxies to configure, no cookies to paste, no login — the Actor handles everything server-side. ### Why teams switch to this Reddit comments scraper Comment trees are where Reddit's real signal lives, but they're the part most scrapers handle worst — browser-based actors time out on big threads and charge $15–20 per 1,000 comments. This Actor walks the thread via a direct HTTP API and returns the tree as flat, parent-linked JSON at **$2.50 per 1,000 comments**. ### What people build with it - **Sentiment analysis** — feed a product-launch thread's comments to an LLM and get a structured verdict on how it landed, weighted by comment score. - **Voice-of-customer mining** — the complaints and praise under reviews and comparison threads are unfiltered product feedback you can't survey for. - **Conversation datasets** — parent-child comment pairs are natural dialogue data for fine-tuning chat models. - **Crisis monitoring** — when a thread about your brand takes off, pull the tree hourly and track which concerns are gaining score. - **Summarized digests** — schedule the Actor + an LLM step to turn daily megathreads into a morning brief. ### Tips for better results - Accept either the full post URL or the bare post ID. - Each comment carries `parentId`, `depth`, and `score`, so you can rebuild the tree, filter to top-level only, or weight by votes. - Find the threads worth expanding with [Reddit Post Search](https://apify.com/ethereal_wool/reddit-post-search) or [Reddit Subreddit Posts](https://apify.com/ethereal_wool/reddit-subreddit-posts). *** ### Why this Actor - **Direct API, no headless browser** — fast, stable runs with nothing to babysit. - **No login, no cookies** — we never touch your accounts, so there's no ban risk. - **Fresh, real-time data** — every run reads the source live, not a stale cache. - **Pay per result** — you're billed only for the rows actually delivered. - **Structured JSON** — export to CSV, Excel, or JSON, or pull straight from the API / MCP. ### Use cases - Mine audience sentiment and feature requests from real comment threads. - Surface the most-liked replies and frequent questions under any post. - Build moderation, UGC, or social-listening datasets at scale. - Spot superfans and detractors by author and engagement. ### FAQ **Do I need an account, cookies, or to log in anywhere?** No. The Actor talks to a fast, direct HTTP API server-side — you just provide inputs and run it. **How am I billed?** Pay-per-result: a fixed price per row returned, with no separate platform/compute charge. Caps like `maxItems` keep spend predictable. **Can I run it on a schedule or call it from my app?** Yes — use Apify Schedules, the REST API, the JavaScript / Python clients, or the MCP server. See the **API** tab. **Is this affiliated with Reddit?** No. It's an independent tool that collects publicly available data. Use it in line with the platform's terms and applicable law. ### More Reddit scrapers by us - [**Reddit Post Search**](https://apify.com/ethereal_wool/reddit-post-search) — Keyword post search across Reddit - [**Reddit Subreddit Posts**](https://apify.com/ethereal_wool/reddit-subreddit-posts) — Posts from any subreddit · sort & time - [**Reddit User Posts**](https://apify.com/ethereal_wool/reddit-user-posts) — A user's posts & comments history Browse the full fleet → **https://apify.com/ethereal\_wool** # Actor input Schema ## `postIds` (type: `array`): Reddit post fullnames to scrape comments from, e.g. "t3\_bawfcs". A bare id ("bawfcs") or a full post URL is also accepted. Each post's comment forest is fetched and paginated independently. ## `sortType` (type: `string`): How to sort the comment forest. ## `maxItems` (type: `integer`): Maximum total number of comments to scrape across all posts. ## `expandReplies` (type: `boolean`): Follow 'load more replies' cursors to fetch deeper nested replies that aren't in the initial comment forest. Slower and uses more API calls. ## `includePostInfo` (type: `boolean`): Fetch each post's metadata (title, subreddit, author, score, comment count) once and attach a 'post' object to every comment item. ## `proxyConfiguration` (type: `object`): Optional. Route the upstream API calls through an Apify Proxy to vary the source IP. Usually not needed. ## Actor input object example ```json { "postIds": [ "t3_bawfcs" ], "sortType": "CONFIDENCE", "maxItems": 50, "expandReplies": false, "includePostInfo": false, "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 = { "postIds": [ "t3_bawfcs" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ethereal_wool/reddit-post-comments").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 = { "postIds": ["t3_bawfcs"] } # Run the Actor and wait for it to finish run = client.actor("ethereal_wool/reddit-post-comments").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 '{ "postIds": [ "t3_bawfcs" ] }' | apify call ethereal_wool/reddit-post-comments --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ethereal_wool/reddit-post-comments", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Post Comments Scraper | $2.5/1K Comments", "description": "Extract Reddit post comments data — title, author, engagement, and more. Scrape by keyword, URL or ID. Export to JSON, CSV & Excel, use the API, schedule runs and integrate. No code required.", "version": "0.1", "x-build-id": "lHZvbkZSN9tiCn6Rm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ethereal_wool~reddit-post-comments/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ethereal_wool-reddit-post-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/ethereal_wool~reddit-post-comments/runs": { "post": { "operationId": "runs-sync-ethereal_wool-reddit-post-comments", "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/ethereal_wool~reddit-post-comments/run-sync": { "post": { "operationId": "run-sync-ethereal_wool-reddit-post-comments", "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": { "postIds": { "title": "Reddit post IDs", "type": "array", "description": "Reddit post fullnames to scrape comments from, e.g. \"t3_bawfcs\". A bare id (\"bawfcs\") or a full post URL is also accepted. Each post's comment forest is fetched and paginated independently.", "default": [ "t3_bawfcs" ], "items": { "type": "string" } }, "sortType": { "title": "Comment sort order", "enum": [ "CONFIDENCE", "TOP", "NEW", "CONTROVERSIAL", "OLD", "QA" ], "type": "string", "description": "How to sort the comment forest.", "default": "CONFIDENCE" }, "maxItems": { "title": "Max comments", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum total number of comments to scrape across all posts.", "default": 50 }, "expandReplies": { "title": "Expand nested replies", "type": "boolean", "description": "Follow 'load more replies' cursors to fetch deeper nested replies that aren't in the initial comment forest. Slower and uses more API calls.", "default": false }, "includePostInfo": { "title": "Include post metadata", "type": "boolean", "description": "Fetch each post's metadata (title, subreddit, author, score, comment count) once and attach a 'post' object to every comment item.", "default": false }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional. Route the upstream API calls through an Apify Proxy to vary the source IP. Usually not needed.", "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 } } } } } } } } } } ```