# Reddit Thread & Comments Scraper (`datara/reddit-thread-comments-scraper`) Actor Scrape any Reddit post and its complete comment thread — including deeply nested replies — in seconds. Supports bulk URLs, cursor-based pagination for large threads, flat or nested output, score filtering, and depth capping. Perfect for sentiment analysis, AI training data, and community research. - **URL**: https://apify.com/datara/reddit-thread-comments-scraper.md - **Developed by:** [Datara](https://apify.com/datara) (community) - **Categories:** Automation, Lead generation, Social media - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Thread & Comments Scraper Extract any Reddit post and its full comment tree — including nested replies at any depth — in seconds. Supports cursor-based pagination for threads with hundreds or thousands of comments. --- ### What This Actor Does Given one or more Reddit post URLs, this actor: 1. Fetches the **post metadata** (title, author, score, upvote ratio, subscriber count, etc.) 2. Fetches the **full comment tree** including nested replies, paginating through all available comment pages 3. Pushes each post and comment as a clean, structured dataset record Output records are typed (`recordType: "post"` or `"comment"`) and immediately usable in spreadsheets, databases, AI pipelines, or downstream automations. --- ### Use Cases - **Sentiment analysis** — analyse how communities respond to products, brands, or announcements - **AI training data** — collect high-quality human conversation threads for LLM fine-tuning or RLHF - **Community research** — surface recurring themes, pain points, and opinions across subreddits - **Qualitative market research** — understand what real users say about your category - **Content strategy** — identify high-scoring discussions to inform editorial direction --- ### Input Fields | Field | Type | Default | Description | |---|---|---|---| | `postUrl` | string | — | Single Reddit post URL to scrape | | `postUrls` | array | `[]` | List of Reddit post URLs for bulk scraping (overrides `postUrl`) | | `maxPages` | integer | `3` | Max comment pages to fetch per post (cursor pagination, ~25 comments/page) | | `flattenComments` | boolean | `true` | Output comments as individual flat records (true) or with nested replies arrays (false) | | `includePostRecord` | boolean | `true` | Include the post as a separate dataset record | | `minCommentScore` | integer | `0` | Skip comments below this score threshold | | `maxCommentDepth` | integer | `10` | Maximum reply nesting depth to include (0 = top-level only) | | `maxCommentsPerPost` | integer | `200` | Cap on total comment records per post (1–5000) | > **Bulk mode:** If `postUrls` is non-empty, the single `postUrl` field is ignored. Duplicate URLs are automatically deduplicated. --- ### Single URL Example Input ```json { "postUrl": "https://www.reddit.com/r/startups/comments/1abc23/we_just_hit_10k_mrr_heres_what_worked/", "maxPages": 5, "flattenComments": true, "includePostRecord": true, "minCommentScore": 5, "maxCommentDepth": 5, "maxCommentsPerPost": 500 } ```` *** ### Bulk URL Example Input ```json { "postUrls": [ "https://www.reddit.com/r/SaaS/comments/1abc11/thoughts_on_pricing_models/", "https://www.reddit.com/r/entrepreneur/comments/1abc22/bootstrapped_to_1m_ama/", "https://www.reddit.com/r/startups/comments/1abc33/why_we_shut_down/" ], "maxPages": 3, "flattenComments": true, "includePostRecord": true, "minCommentScore": 2, "maxCommentDepth": 10, "maxCommentsPerPost": 300 } ``` *** ### Output Schema #### Post Record (`recordType: "post"`) | Field | Type | Description | |---|---|---| | `recordType` | string | Always `"post"` | | `id` | string | Reddit short ID (e.g. `1lfbo7u`) | | `name` | string | Reddit fullname, prefixed `t3_` (e.g. `t3_1lfbo7u`) | | `title` | string | Post title | | `author` | string | Username of the poster | | `authorFullname` | string | Reddit internal author ID (e.g. `t2_16syu27ar1`) | | `subreddit` | string | Subreddit name (without `r/`) | | `url` | string | Full post URL | | `score` | integer | Net vote score | | `ups` | integer | Upvote count (fuzzy-rounded by Reddit) | | `downs` | integer | Downvote count (almost always 0) | | `upvoteRatio` | number | Ratio of upvotes to total votes (0–1) | | `numComments` | integer | Total comment count as reported by Reddit | | `subredditSubscribers` | integer | Subscriber count of the subreddit | | `isVideo` | boolean | True if the post contains a Reddit-hosted video | | `totalAwardsReceived` | integer | Number of Reddit awards | | `createdUtc` | number | Unix timestamp (UTC seconds) of post creation | | `createdAt` | string | ISO 8601 datetime of post creation | | `scrapedAt` | string | ISO 8601 datetime when the record was scraped | **Example post record:** ```json { "recordType": "post", "id": "1lfbo7u", "name": "t3_1lfbo7u", "title": "What is a thing you love that lots of people hate?", "author": "Vetro_Nodulare2", "authorFullname": "t2_16syu27ar1", "subreddit": "AskReddit", "url": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/", "score": 47, "ups": 47, "downs": 0, "upvoteRatio": 0.91, "numComments": 353, "subredditSubscribers": 56146601, "isVideo": false, "totalAwardsReceived": 0, "createdUtc": 1750341959, "createdAt": "2025-06-19T14:05:59.000Z", "scrapedAt": "2025-06-20T09:45:12.000Z" } ``` *** #### Comment Record (`recordType: "comment"`) | Field | Type | Description | |---|---|---| | `recordType` | string | Always `"comment"` | | `id` | string | Reddit short ID (e.g. `mymupxb`) | | `name` | string | Reddit fullname, prefixed `t1_` (e.g. `t1_mymupxb`) | | `postId` | string | Short ID of the parent post | | `postUrl` | string | Full URL of the parent post | | `author` | string | Username of the commenter | | `authorFullname` | string | Reddit internal author ID | | `body` | string | Plain-text comment body | | `score` | integer | Net vote score | | `ups` | integer | Upvote count | | `downs` | integer | Downvote count | | `depth` | integer | Nesting depth (0 = top-level, 1 = reply to top-level, etc.) | | `parentId` | string | Fullname of the parent (`t3_...` if replying to post, `t1_...` if replying to comment) | | `linkId` | string | Fullname of the parent post (always `t3_...`) | | `subreddit` | string | Subreddit name | | `url` | string | Full URL of this comment | | `permalink` | string | Relative permalink path | | `gilded` | integer | Number of times gilded | | `stickied` | boolean | True if pinned by a moderator | | `locked` | boolean | True if the comment thread is locked | | `archived` | boolean | True if too old to receive votes | | `controversiality` | integer | 0 or 1; 1 = high vote split | | `totalAwardsReceived` | integer | Number of Reddit awards | | `createdUtc` | number | Unix timestamp (UTC seconds) of comment creation | | `createdAt` | string | ISO 8601 datetime of comment creation | | `scrapedAt` | string | ISO 8601 datetime when scraped | | `replies` | array | \[Nested mode only] Child comment records | **Example comment record (flat mode):** ```json { "recordType": "comment", "id": "mymupxb", "name": "t1_mymupxb", "postId": "1lfbo7u", "postUrl": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/", "author": "Background-Emu-2890", "authorFullname": "t2_efdlposp6", "body": "Black cat — I have one and I love her so much!", "score": 75, "ups": 75, "downs": 0, "depth": 0, "parentId": "t3_1lfbo7u", "linkId": "t3_1lfbo7u", "subreddit": "AskReddit", "url": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/mymupxb/", "permalink": "/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/mymupxb/", "gilded": 0, "stickied": false, "locked": false, "archived": false, "controversiality": 0, "totalAwardsReceived": 0, "createdUtc": 1750342221, "createdAt": "2025-06-19T14:10:21.000Z", "scrapedAt": "2025-06-20T09:45:12.000Z" } ``` *** ### Flat vs Nested Comment Output **Flat mode** (`flattenComments: true`, default): - Every comment and reply is pushed as its own dataset record - Use `depth` to understand nesting level (0 = top-level) - Use `parentId` to reconstruct the tree (`t1_XXX` = parent comment, `t3_XXX` = direct reply to post) - Best for: spreadsheet analysis, databases, ML pipelines, CSV export **Nested mode** (`flattenComments: false`): - Top-level comment records contain a `replies` array with child records embedded - Each child also contains its own `replies` array, forming a full tree - Best for: JSON tree processing, displaying thread structure *** ### Pagination The ScrapeCreators API uses cursor-based pagination. Each page returns approximately 25 top-level comments. Set `maxPages` to control how many pages to fetch: - `maxPages: 1` — fast, ~25 top-level comments - `maxPages: 5` — ~125 top-level comments + all their replies - `maxPages: 20` — comprehensive extraction for large threads The actor stops pagination early if `maxCommentsPerPost` is reached or the API signals no more pages available. *** ### Error Handling - Failed URLs push an error record (`error: true`) and processing continues for remaining URLs - Posts with no comments push a warning record - The dataset always contains at least one record per run *** ### Pricing This actor uses **Pay Per Event (PPE)** pricing: - **$0.30 per 100 records** (each post and each comment count as one record) - A thread with 1 post + 199 comments = 200 records ≈ $0.60 - Bulk run: 10 threads × 200 comments = ~2,010 records ≈ $6.03 *** ### Support For questions or feature requests, contact the actor publisher via the Apify Store messaging system. # Actor input Schema ## `postUrl` (type: `string`): Full URL of a Reddit post to scrape. Used when scraping a single thread. Example: https://www.reddit.com/r/AskReddit/comments/abc123/my\_post/ ## `postUrls` (type: `array`): List of Reddit post URLs for bulk scraping. When this array is non-empty, it overrides the single Post URL field above. ## `maxPages` (type: `integer`): Maximum number of comment pages to fetch per post using cursor-based pagination. Each page returns ~25 top-level comments. Set to 1 for a quick grab, or higher for comprehensive extraction. Range: 1–20. ## `flattenComments` (type: `boolean`): When enabled, all comments including nested replies are output as individual flat dataset records, each carrying their depth level and parentId. When disabled, top-level comment records include their replies as nested arrays. ## `includePostRecord` (type: `boolean`): Include the post itself as a separate record (recordType: post) in the output dataset. ## `minCommentScore` (type: `integer`): Exclude comments with a score below this threshold. Set to 0 to include all comments regardless of score. ## `maxCommentDepth` (type: `integer`): Maximum nesting depth of replies to include. 0 = top-level only, 1 = top-level plus direct replies, and so on. The API returns a depth field on each comment. ## `maxCommentsPerPost` (type: `integer`): Cap on the total number of comment records extracted per post across all pages. Range: 1–5000. ## Actor input object example ```json { "postUrl": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/", "postUrls": [], "maxPages": 3, "flattenComments": true, "includePostRecord": true, "minCommentScore": 0, "maxCommentDepth": 10, "maxCommentsPerPost": 200 } ``` # 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 = { "postUrl": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/", "postUrls": [], "maxPages": 3, "flattenComments": true, "includePostRecord": true, "minCommentScore": 0, "maxCommentDepth": 10, "maxCommentsPerPost": 200 }; // Run the Actor and wait for it to finish const run = await client.actor("datara/reddit-thread-comments-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 = { "postUrl": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/", "postUrls": [], "maxPages": 3, "flattenComments": True, "includePostRecord": True, "minCommentScore": 0, "maxCommentDepth": 10, "maxCommentsPerPost": 200, } # Run the Actor and wait for it to finish run = client.actor("datara/reddit-thread-comments-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 '{ "postUrl": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/", "postUrls": [], "maxPages": 3, "flattenComments": true, "includePostRecord": true, "minCommentScore": 0, "maxCommentDepth": 10, "maxCommentsPerPost": 200 }' | apify call datara/reddit-thread-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datara/reddit-thread-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Thread & Comments Scraper", "description": "Scrape any Reddit post and its complete comment thread — including deeply nested replies — in seconds. Supports bulk URLs, cursor-based pagination for large threads, flat or nested output, score filtering, and depth capping. Perfect for sentiment analysis, AI training data, and community research.", "version": "0.0", "x-build-id": "XCSjahUkmQPl3rJXC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datara~reddit-thread-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datara-reddit-thread-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datara~reddit-thread-comments-scraper/runs": { "post": { "operationId": "runs-sync-datara-reddit-thread-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datara~reddit-thread-comments-scraper/run-sync": { "post": { "operationId": "run-sync-datara-reddit-thread-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "postUrl": { "title": "Reddit Post URL", "type": "string", "description": "Full URL of a Reddit post to scrape. Used when scraping a single thread. Example: https://www.reddit.com/r/AskReddit/comments/abc123/my_post/", "default": "https://www.reddit.com/r/AskReddit/comments/1lfbo7u/what_is_a_thing_you_love_that_lots_of_people_hate/" }, "postUrls": { "title": "Reddit Post URLs (Bulk)", "type": "array", "description": "List of Reddit post URLs for bulk scraping. When this array is non-empty, it overrides the single Post URL field above.", "default": [], "items": { "type": "string" } }, "maxPages": { "title": "Max Comment Pages", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of comment pages to fetch per post using cursor-based pagination. Each page returns ~25 top-level comments. Set to 1 for a quick grab, or higher for comprehensive extraction. Range: 1–20.", "default": 3 }, "flattenComments": { "title": "Flatten Comments", "type": "boolean", "description": "When enabled, all comments including nested replies are output as individual flat dataset records, each carrying their depth level and parentId. When disabled, top-level comment records include their replies as nested arrays.", "default": true }, "includePostRecord": { "title": "Include Post Record", "type": "boolean", "description": "Include the post itself as a separate record (recordType: post) in the output dataset.", "default": true }, "minCommentScore": { "title": "Minimum Comment Score", "minimum": -9999, "maximum": 999999, "type": "integer", "description": "Exclude comments with a score below this threshold. Set to 0 to include all comments regardless of score.", "default": 0 }, "maxCommentDepth": { "title": "Max Comment Depth", "minimum": 0, "maximum": 100, "type": "integer", "description": "Maximum nesting depth of replies to include. 0 = top-level only, 1 = top-level plus direct replies, and so on. The API returns a depth field on each comment.", "default": 10 }, "maxCommentsPerPost": { "title": "Max Comments Per Post", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Cap on the total number of comment records extracted per post across all pages. Range: 1–5000.", "default": 200 } } }, "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 } } } } } } } } } } ```