# Reddit Post & Comment Scraper (`fluxcurulin/reddit-scraper`) Actor Scrape posts and comments from any subreddit via old.reddit.com. Extract titles, scores, authors, timestamps, comment threads, and nested replies. Ideal for sentiment analysis, trend tracking, brand monitoring, and academic research. - **URL**: https://apify.com/fluxcurulin/reddit-scraper.md - **Developed by:** [Josh Pinkerton](https://apify.com/fluxcurulin) (community) - **Categories:** AI - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 & Comment Scraper Extract posts and comments from any subreddit with full metadata: titles, scores, authors, timestamps, and nested comment threads. ### Why use this scraper? - Monitor community sentiment and trending topics - Archive subreddit content for research or backup - Build training data for NLP and moderation models - Pull historical thread data Reddit search no longer surfaces easily ### How to use 1. Open the Reddit Post & Comment Scraper in Apify Console 2. Enter one or more subreddits in `subreddits` 3. Choose `sort` order: `hot`, `new`, `top`, or `rising` 4. Set `limit` and optionally enable comments with `maxCommentsPerPost` 5. Click Run and export results to JSON, CSV, or Excel. ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | `subreddits` | array | Subreddits to scrape | `python, programming` | | `sort` | enum | Post sort order | `hot` | | `limit` | integer | Max posts to fetch | `100` | | `includeComments` | boolean | Whether to fetch comments | `true` | | `maxCommentsPerPost` | integer | Max comments per post | `50` | ### Output ```json { "post_id": "t3_abc123", "subreddit": "python", "title": "Why I switched from Flask to FastAPI", "score": 874, "author": "dev_jane", "created_utc": "2026-07-04T20:15:00Z", "url": "https://reddit.com/r/python/comments/abc123", "comments": [ { "comment_id": "t1_def456", "author": "commenter_bob", "body": "Same here, FastAPI is faster to ship with.", "score": 42, "created_utc": "2026-07-04T20:30:00Z" } ] } ```` ### Pricing Pay-per-event: **$0.005 per extracted item** (post or comment). A 100-post / 5,000-comment run costs about $25.00. ### Tips - Use `sort: new` combined with the Apify Scheduler for real-time monitoring - Lower `maxCommentsPerPost` during development to save time and cost - Output works well with downstream sentiment-analysis actors ### FAQ **Does this scrape user profiles?** No. It scrapes public posts and comments from subreddit listings only. **Are private subreddits supported?** No. Only public subreddits are accessible without authentication. # Actor input Schema ## `subreddits` (type: `array`): No description ## `sort` (type: `string`): No description ## `limit` (type: `integer`): No description ## `include_comments` (type: `boolean`): No description ## `max_comments_per_post` (type: `integer`): No description ## Actor input object example ```json { "subreddits": [ { "subreddit": "python" }, { "subreddit": "programming" } ], "sort": "hot", "limit": 100, "include_comments": true, "max_comments_per_post": 50 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "subreddits": [ { "subreddit": "python" }, { "subreddit": "programming" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("fluxcurulin/reddit-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "subreddits": [ { "subreddit": "python" }, { "subreddit": "programming" }, ] } # Run the Actor and wait for it to finish run = client.actor("fluxcurulin/reddit-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 '{ "subreddits": [ { "subreddit": "python" }, { "subreddit": "programming" } ] }' | apify call fluxcurulin/reddit-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fluxcurulin/reddit-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Post & Comment Scraper", "description": "Scrape posts and comments from any subreddit via old.reddit.com. Extract titles, scores, authors, timestamps, comment threads, and nested replies. Ideal for sentiment analysis, trend tracking, brand monitoring, and academic research.", "version": "0.1", "x-build-id": "aipk3M0NVWXgdDK7O" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fluxcurulin~reddit-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fluxcurulin-reddit-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fluxcurulin~reddit-scraper/runs": { "post": { "operationId": "runs-sync-fluxcurulin-reddit-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fluxcurulin~reddit-scraper/run-sync": { "post": { "operationId": "run-sync-fluxcurulin-reddit-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "subreddits" ], "properties": { "subreddits": { "title": "Subreddits", "type": "array", "description": "", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "sort": { "title": "Sort Order", "enum": [ "hot", "new", "top", "rising" ], "type": "string", "description": "", "default": "hot" }, "limit": { "title": "Max Requests", "type": "integer", "description": "", "default": 100 }, "include_comments": { "title": "Include Comments", "type": "boolean", "description": "", "default": true }, "max_comments_per_post": { "title": "Max Comments per Post", "type": "integer", "description": "", "default": 50 } } }, "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 } } } } } } } } } } ```