# 🔴 Reddit Scraper — Posts, Comments & Data (`nexgendata/reddit-scraper`) Actor Extract posts, comments & subreddit data from Reddit. Monitor brand mentions, track discussions & build social listening tools. Get upvotes, awards & comment threads. Pay per post. - **URL**: https://apify.com/nexgendata/reddit-scraper.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Social media, AI - **Stats:** 6 total users, 4 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 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. 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 Scraper — Posts, Comments, Subreddit & User Data Extract structured data from any Reddit subreddit, search query, post URL, or user profile — including posts, full comment trees, scores, awards, flairs, and author metadata. Built as a pay-per-result **alternative to** Reddit's official API (OAuth-gated + 100 req/min), Pushshift (often offline), Brandwatch ($800/mo), Brand24 ($79-499/mo), and BuzzSumo for sentiment analysis, audience research, and competitive intel. ### Why Reddit Scraper Beats Reddit API, Pushshift, Brandwatch & Brand24 | Feature | NexGenData Reddit Scraper | Reddit API | Pushshift | Brandwatch | Brand24 | |---|---|---|---|---|---| | Cost | $0.002 / item, pay-per-result | Free but OAuth + 100/min | Free (often down) | $800+ / month | $79-499 / month | | Posts per subreddit | Unlimited | Capped at 1,000 historical | Historical archive | Plan-gated | Plan-gated | | Full comment trees | Yes | Yes (extra calls) | Yes | Limited | Limited | | Search across all of Reddit | Yes | Yes | Yes | Yes | Yes | | User-profile scrape | Yes | Yes (OAuth required) | Yes | Limited | Limited | | Bulk export | JSON / CSV / Excel | DIY | DIY | Plan-gated | CSV | | Auth required | Apify token | OAuth client + dev account | None (when up) | Account + plan | Account + plan | | Monthly minimum | None | None | None | $800+ | $79+ | Most researchers + marketing teams pick this actor **instead of** Reddit's official API because OAuth setup + the 100-req/min cap make any deep historical dive painful. **Cheaper than** Brandwatch for the Reddit slice and a **drop-in alternative to** Pushshift now that it's permanently rate-limited and frequently offline. ### What You Get **Per post:** - `id`, `subreddit`, `permalink`, `url`, `title`, `selftext` - `author`, `author_id`, `author_premium` - `score`, `upvote_ratio`, `num_comments`, `num_awards` - `created_utc`, `flair`, `is_self`, `is_video`, `is_oc`, `is_nsfw` - `media_url`, `thumbnail` **Per comment (when enabled):** - `id`, `parent_id`, `post_id`, `subreddit` - `author`, `body`, `score`, `controversiality` - `created_utc`, `depth`, `is_submitter`, `gilded` ### Use Cases - **Brand / competitor monitoring** — track mentions across all of Reddit with weekly sweeps - **Sentiment analysis** — bulk-export comment corpora for NLP and classification - **Audience research** — discover what your ICP is actually discussing in niche subreddits - **Content / SEO** — surface frequently-asked questions and pain points by topic - **Product feedback mining** — find unfiltered feedback on your product + competitors - **Crisis / PR monitoring** — detect viral threads before they hit Twitter or news - **Academic research** — pull labeled-discussion datasets for political science, sociology, ML training ### Quick Start (Python) ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("nexgendata/reddit-scraper").call(run_input={ "subreddits": ["startups", "SaaS"], "max_posts": 500, "include_comments": True, "sort": "new" }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["title"], item["score"]) ```` ### Pricing — Pay Per Item - **Actor start:** $0.005 - **Item:** $0.002 A 500-post daily subreddit sweep with comments = $1.005-3.005/day. A 10,000-post research corpus = $20.005. **No monthly minimum.** ### Related NexGenData Social + Discussion Actors | Use case | Actor | |----------|-------| | Reddit brand monitor (Brandwatch alt, sentiment) | [reddit-brand-monitor](https://apify.com/nexgendata/reddit-brand-monitor?fpr=2ayu9b) | | Reddit subreddit trends | [reddit-subreddit-trends](https://apify.com/nexgendata/reddit-subreddit-trends?fpr=2ayu9b) | | Hacker News scraper (stories + comments) | [hacker-news-scraper](https://apify.com/nexgendata/hacker-news-scraper?fpr=2ayu9b) | | HN Show HN tracker (launches) | [hn-show-hn-tracker](https://apify.com/nexgendata/hn-show-hn-tracker?fpr=2ayu9b) | | Indie Hackers product launches | [indie-hackers-products-tracker](https://apify.com/nexgendata/indie-hackers-products-tracker?fpr=2ayu9b) | | Product Hunt daily launches | [product-hunt-launches-scraper](https://apify.com/nexgendata/product-hunt-launches-scraper?fpr=2ayu9b) | | YouTube comments scraper | [youtube-comments-scraper](https://apify.com/nexgendata/youtube-comments-scraper?fpr=2ayu9b) | | Weibo hot-search tracker (China) | [weibo-hot-search-tracker](https://apify.com/nexgendata/weibo-hot-search-tracker?fpr=2ayu9b) | | Zhihu Q\&A tracker (China) | [zhihu-qa-tracker](https://apify.com/nexgendata/zhihu-qa-tracker?fpr=2ayu9b) | ### FAQ **Q: Does it require a Reddit account or OAuth?** A: No. It uses Reddit's public JSON endpoints. Zero setup beyond entering your subreddits / queries. **Q: Comment-tree depth?** A: Full tree by default. You can cap depth with `max_comment_depth` if you only want top-level engagement. **Q: Historical posts beyond 1,000?** A: Reddit's listing API caps at ~1,000 historical posts per subreddit-sort. For deeper history, query by date range and sort variants (top of week / month / year / all). **Q: NSFW + private subreddits?** A: Public NSFW subreddits are accessible. Private (invite-only) subreddits aren't — Reddit's auth wall applies. **Q: How does it differ from reddit-brand-monitor?** A: This is the general scraper — posts, comments, profiles. Reddit Brand Monitor is the keyword-monitoring + sentiment + analytics layer on top, optimized for brand tracking. *** ### How NexGenData Pricing Works Every NexGenData actor uses **pay-per-event** pricing — you only pay for results that actually land in your dataset. No monthly minimum, no seat fees, no surprise overage bills. - **Actor Start:** a single-event charge each time you spin the actor up (scaled to memory size) - **Result / item:** charged per item written to the default dataset - **No charge** for retries, internal proxy rotation, or failed sub-requests — those are absorbed by the platform ### Apify Platform Bonus New to Apify? Sign up with the NexGenData [referral link](https://www.apify.com/?fpr=2ayu9b) — you get free platform credits on signup (enough for several thousand free results) and you help fund the maintenance of this actor fleet. ### Integration Surface Every actor in the NexGenData catalog can be triggered from: - **Apify console** — point-and-click run - **Apify API** — REST + webhooks - **Apify Python / JS SDKs** — programmatic batch - **Zapier, Make.com, n8n** — official integrations - **MCP** — many actors are exposed as MCP tools for Claude / ChatGPT / Cursor agents - **Schedules** — built-in cron for daily / weekly / monthly runs - **Webhooks** — POST results to any HTTPS endpoint on dataset write ### Support NexGenData maintains 260+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get a response within 24 hours. Roadmap requests are welcome — high-demand features ship in the next version. Home: [thenextgennexus.com](https://thenextgennexus.com) Full catalog: [apify.com/nexgendata](https://apify.com/nexgendata?fpr=2ayu9b) # Actor input Schema ## `searchQuery` (type: `string`): Keywords to search for across Reddit posts and comments. ## `subreddit` (type: `string`): Specific subreddit to search within (without r/ prefix). Leave empty to search all of Reddit. ## `sort` (type: `string`): How to sort search results: relevance, hot, top, new, or comments. ## `maxResults` (type: `integer`): Maximum number of posts to return (1-100). ## `includeComments` (type: `boolean`): Fetch top-level comments for each post. Slower but provides discussion data. ## Actor input object example ```json { "searchQuery": "artificial intelligence", "sort": "relevance", "maxResults": 25, "includeComments": 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 = { "searchQuery": "artificial intelligence" }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/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 = { "searchQuery": "artificial intelligence" } # Run the Actor and wait for it to finish run = client.actor("nexgendata/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 '{ "searchQuery": "artificial intelligence" }' | apify call nexgendata/reddit-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/reddit-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🔴 Reddit Scraper — Posts, Comments & Data", "description": "Extract posts, comments & subreddit data from Reddit. Monitor brand mentions, track discussions & build social listening tools. Get upvotes, awards & comment threads. Pay per post.", "version": "0.0", "x-build-id": "zopn4HQ6kIGgM3qBc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~reddit-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~reddit-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-reddit-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~reddit-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-reddit-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchQuery" ], "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Keywords to search for across Reddit posts and comments." }, "subreddit": { "title": "Subreddit", "type": "string", "description": "Specific subreddit to search within (without r/ prefix). Leave empty to search all of Reddit." }, "sort": { "title": "Sort By", "enum": [ "relevance", "hot", "top", "new", "comments" ], "type": "string", "description": "How to sort search results: relevance, hot, top, new, or comments.", "default": "relevance" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of posts to return (1-100).", "default": 25 }, "includeComments": { "title": "Include Comments", "type": "boolean", "description": "Fetch top-level comments for each post. Slower but provides discussion data.", "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 } } } } } } } } } } ```