# Reddit Comment Scraper (`myagizm/reddit-comment-scraper`) Actor Scrape Reddit comments as structured JSON — full comment trees from any post or subreddit. No login, no API key. - **URL**: https://apify.com/myagizm/reddit-comment-scraper.md - **Developed by:** [MYM](https://apify.com/myagizm) (community) - **Categories:** Social media - **Stats:** 2 total users, 0 monthly users, 80.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $1.40 / 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/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 Comment Scraper 💬 Extract **Reddit comments** at scale as clean, structured JSON. Point it at post URLs or subreddits and get full comment trees — author, text, score, depth, and timestamps. No login, no API key. Perfect for sentiment analysis, community research, customer feedback mining, and training datasets. ### What you get - Full nested comment trees (depth- and count-bounded) - Per comment: `author`, `body`, `score`, `createdUtc`, `depth`, `permalink` - Parent context: `postId`, `postTitle`, `postUrl`, `subreddit` - Date filtering, per-post caps ### Example input ```json { "startUrls": [{ "url": "https://www.reddit.com/r/technology/comments/abc123/title/" }], "maxComments": 100, "maxCommentDepth": 6 } ```` Or scrape the latest posts of a subreddit: ```json { "subreddits": ["AskReddit"], "sort": "hot", "maxComments": 50 } ``` ### Output One record per comment (see the **Comments** view in the Output tab). Export as JSON, CSV, Excel, or via API. ### 💵 Pricing **$1.40 per 1,000 comments** — pay only for what you scrape. No monthly fee. ### ⏱️ Limits A run lasts at most ~10 minutes; only one long-running job runs at a time. ### Notes Reads only public Reddit data. Please scrape responsibly. *** ### 🔎 Keywords reddit comment scraper, scrape reddit comments, reddit comments api, comment tree extractor, reddit thread scraper, reddit sentiment analysis, reddit feedback mining, reddit nlp dataset, reddit discussion scraper, social media comments, reddit data extraction, no login reddit # Actor input Schema ## `startUrls` (type: `array`): Reddit post URLs to scrape comments from. Each post's full comment tree is extracted. ## `subreddits` (type: `array`): Subreddit names — the latest posts in each are opened and their comments scraped. The r/ prefix is optional. ## `sort` (type: `string`): Which posts to pick from a subreddit before scraping their comments. ## `time` (type: `string`): Time window for Top / Controversial. ## `maxComments` (type: `integer`): Upper bound on comments scraped per post. ## `maxCommentDepth` (type: `integer`): Maximum nesting depth of the comment tree to traverse. ## `commentDateLimit` (type: `string`): Keep only comments created on or after this date. Leave empty for no limit. ## `maxItems` (type: `integer`): How many posts to open in total (comments are then extracted from each). A run lasts at most ~10 minutes. ## `maxPostsPerSource` (type: `integer`): Cap on posts opened from each subreddit. ## `maxPages` (type: `integer`): Pagination depth per subreddit listing (25 posts/page). ## `maxRetries` (type: `integer`): Retry attempts per failed request. ## `requestDelayMs` (type: `integer`): Politeness delay between requests. ## `debug` (type: `boolean`): Emit verbose logs. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.reddit.com/r/pics/comments/abc123/title/" } ], "subreddits": [ "news" ], "sort": "hot", "time": "week", "maxComments": 50, "maxCommentDepth": 6, "commentDateLimit": "2026-01-01", "maxItems": 25, "maxPostsPerSource": 25, "maxPages": 1, "maxRetries": 3, "requestDelayMs": 300, "debug": false } ``` # Actor output Schema ## `results` (type: `string`): All scraped items as structured JSON. # 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 = { "startUrls": [ { "url": "https://www.reddit.com/r/AskReddit/" } ], "subreddits": [ "AskReddit" ], "sort": "hot", "time": "week", "maxComments": 50, "maxCommentDepth": 6, "maxItems": 25, "maxPostsPerSource": 25, "maxPages": 1, "maxRetries": 3, "requestDelayMs": 300, "debug": false }; // Run the Actor and wait for it to finish const run = await client.actor("myagizm/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 = { "startUrls": [{ "url": "https://www.reddit.com/r/AskReddit/" }], "subreddits": ["AskReddit"], "sort": "hot", "time": "week", "maxComments": 50, "maxCommentDepth": 6, "maxItems": 25, "maxPostsPerSource": 25, "maxPages": 1, "maxRetries": 3, "requestDelayMs": 300, "debug": False, } # Run the Actor and wait for it to finish run = client.actor("myagizm/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 '{ "startUrls": [ { "url": "https://www.reddit.com/r/AskReddit/" } ], "subreddits": [ "AskReddit" ], "sort": "hot", "time": "week", "maxComments": 50, "maxCommentDepth": 6, "maxItems": 25, "maxPostsPerSource": 25, "maxPages": 1, "maxRetries": 3, "requestDelayMs": 300, "debug": false }' | apify call myagizm/reddit-comment-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=myagizm/reddit-comment-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Comment Scraper", "description": "Scrape Reddit comments as structured JSON — full comment trees from any post or subreddit. No login, no API key.", "version": "0.1", "x-build-id": "kVMxaWo4hZ279tWnh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/myagizm~reddit-comment-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-myagizm-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/myagizm~reddit-comment-scraper/runs": { "post": { "operationId": "runs-sync-myagizm-reddit-comment-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/myagizm~reddit-comment-scraper/run-sync": { "post": { "operationId": "run-sync-myagizm-reddit-comment-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "startUrls": { "title": "Post URLs", "type": "array", "description": "Reddit post URLs to scrape comments from. Each post's full comment tree is extracted.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "subreddits": { "title": "Subreddits", "type": "array", "description": "Subreddit names — the latest posts in each are opened and their comments scraped. The r/ prefix is optional.", "items": { "type": "string" } }, "sort": { "title": "Post sort", "enum": [ "new", "hot", "top", "rising", "controversial" ], "type": "string", "description": "Which posts to pick from a subreddit before scraping their comments.", "default": "hot" }, "time": { "title": "Time range", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Time window for Top / Controversial.", "default": "all" }, "maxComments": { "title": "Max comments per post", "minimum": 1, "maximum": 100, "type": "integer", "description": "Upper bound on comments scraped per post.", "default": 50 }, "maxCommentDepth": { "title": "Max comment depth", "minimum": 0, "maximum": 15, "type": "integer", "description": "Maximum nesting depth of the comment tree to traverse.", "default": 6 }, "commentDateLimit": { "title": "Only comments on/after (YYYY-MM-DD)", "type": "string", "description": "Keep only comments created on or after this date. Leave empty for no limit." }, "maxItems": { "title": "Max posts to open", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many posts to open in total (comments are then extracted from each). A run lasts at most ~10 minutes.", "default": 25 }, "maxPostsPerSource": { "title": "Max posts per subreddit", "minimum": 1, "maximum": 100, "type": "integer", "description": "Cap on posts opened from each subreddit.", "default": 25 }, "maxPages": { "title": "Max listing pages", "minimum": 1, "maximum": 20, "type": "integer", "description": "Pagination depth per subreddit listing (25 posts/page).", "default": 1 }, "maxRetries": { "title": "Max request retries", "minimum": 0, "maximum": 6, "type": "integer", "description": "Retry attempts per failed request.", "default": 3 }, "requestDelayMs": { "title": "Delay between requests (ms)", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Politeness delay between requests.", "default": 300 }, "debug": { "title": "Debug logging", "type": "boolean", "description": "Emit verbose logs.", "default": 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 } } } } } } } } } } ```