# Reddit Scraper Enhanced (`dash_authority/reddit-scraper-enhanced`) Actor Scrape Reddit posts, comments, and subreddit analytics with built-in sentiment scoring. Uses Reddit public JSON API for reliable data extraction. - **URL**: https://apify.com/dash\_authority/reddit-scraper-enhanced.md - **Developed by:** [Dash Authority](https://apify.com/dash_authority) (community) - **Categories:** Developer tools, Other, AI - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $2.00 / 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 Enhanced Scrape Reddit posts, comments, and subreddit analytics with built-in sentiment scoring. Uses Reddit's public JSON API — no browser automation needed, no datacenter IP blocks. ### Use Cases - **Market Research** — Monitor subreddit trends, track product mentions, analyze competitor discussions - **Sentiment Analysis** — Automatically classify post/comment sentiment as positive, negative, or neutral - **Pain Point Discovery** — Find complaints, feature requests, and frustrations in niche communities - **Content Ideation** — Discover what topics resonate in your target communities - **Community Monitoring** — Track brand mentions, competitor activity, and industry discussions - **Lead Generation** — Identify potential customers expressing needs your product solves ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `subreddit` | string | — | Subreddit name without `r/` (e.g., `python`, `startups`) | | `searchQuery` | string | — | Search within subreddit or all of Reddit | | `sort` | select | `hot` | Sort method: `hot`, `new`, `top`, `rising` | | `timeFilter` | select | `all` | Time range for top sort: `hour`, `day`, `week`, `month`, `year`, `all` | | `maxResults` | integer | `50` | Max posts to scrape (1–500) | | `includeComments` | boolean | `false` | Include top-level comments for each post | | `commentDepth` | integer | `3` | Depth of comment thread recursion (1–10) | | `proxyConfiguration` | proxy | — | Apify proxy settings | ### Example Output ```json { "id": "abc123", "title": "I built a tool that solved my biggest frustration with Reddit research", "author": "example_user", "subreddit": "startups", "score": 247, "upvoteRatio": 0.92, "numComments": 58, "created": 1713542400, "url": "https://www.reddit.com/r/startups/comments/abc123/...", "permalink": "https://www.reddit.com/r/startups/comments/abc123/i_built_a_tool_that_solved/", "selftext": "After months of manually scrolling through subreddits...", "flair": "Tool", "isStickied": false, "isLocked": false, "awards": 3, "sentiment": "positive", "sentimentScore": 0.6, "positiveCount": 4, "negativeCount": 1, "top_comments": [ { "author": "commenter1", "body": "This is amazing! Exactly what I needed.", "score": 45, "created": 1713546000, "depth": 0, "sentiment": "positive", "sentimentScore": 1.0, "replies": [] } ], "commentCount": 1 } ```` ### How It Works 1. **No browser needed** — Uses Reddit's public `.json` API endpoints 2. **Built-in rate limiting** — Respects 60 req/min with proper User-Agent 3. **Simple sentiment scoring** — Keyword-based analysis with no ML dependencies 4. **Recursive comments** — Fetches nested reply threads up to configurable depth 5. **Proxy support** — Use Apify Proxy to avoid rate limits ### Quick Start ```bash ## Via Apify CLI apify run --input='{"subreddit": "python", "sort": "hot", "maxResults": 100}' ## Or use the Apify Console / API ``` ### Limitations - Reddit's JSON API returns max 100 items per request (the actor paginates automatically) - Some subreddits may restrict API access - Sentiment analysis is keyword-based and may not capture sarcasm or nuanced language - Rate limits apply (~60 requests/minute with proper User-Agent) ### Pricing $0.002 per scraped post (PAY\_PER\_EVENT model). # Actor input Schema ## `subreddit` (type: `string`): Subreddit name without the r/ prefix (e.g., 'python', 'startups', 'technology') ## `searchQuery` (type: `string`): Search term to find posts. If a subreddit is specified, searches within that subreddit. Otherwise searches all of Reddit. ## `sort` (type: `string`): How to sort the results ## `timeFilter` (type: `string`): Time range for 'top' sort. Only applies when sort is 'top'. ## `maxResults` (type: `integer`): Maximum number of posts to scrape (1-500) ## `includeComments` (type: `boolean`): Fetch top-level comments for each post. This will increase scraping time and API usage. ## `commentDepth` (type: `integer`): How deep to fetch nested comment replies (1-10 levels). Only applies when Include Comments is enabled. ## `proxyConfiguration` (type: `object`): Select proxies to use for scraping. Recommended for avoiding rate limits. ## Actor input object example ```json { "subreddit": "python", "sort": "hot", "timeFilter": "all", "maxResults": 50, "includeComments": false, "commentDepth": 3 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "subreddit": "python", "searchQuery": "" }; // Run the Actor and wait for it to finish const run = await client.actor("dash_authority/reddit-scraper-enhanced").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "subreddit": "python", "searchQuery": "", } # Run the Actor and wait for it to finish run = client.actor("dash_authority/reddit-scraper-enhanced").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 '{ "subreddit": "python", "searchQuery": "" }' | apify call dash_authority/reddit-scraper-enhanced --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dash_authority/reddit-scraper-enhanced", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper Enhanced", "description": "Scrape Reddit posts, comments, and subreddit analytics with built-in sentiment scoring. Uses Reddit public JSON API for reliable data extraction.", "version": "1.0", "x-build-id": "8WNme9k9KJJwXaaHX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dash_authority~reddit-scraper-enhanced/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dash_authority-reddit-scraper-enhanced", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dash_authority~reddit-scraper-enhanced/runs": { "post": { "operationId": "runs-sync-dash_authority-reddit-scraper-enhanced", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dash_authority~reddit-scraper-enhanced/run-sync": { "post": { "operationId": "run-sync-dash_authority-reddit-scraper-enhanced", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "subreddit": { "title": "Subreddit", "type": "string", "description": "Subreddit name without the r/ prefix (e.g., 'python', 'startups', 'technology')" }, "searchQuery": { "title": "Search Query", "type": "string", "description": "Search term to find posts. If a subreddit is specified, searches within that subreddit. Otherwise searches all of Reddit." }, "sort": { "title": "Sort Method", "enum": [ "hot", "new", "top", "rising" ], "type": "string", "description": "How to sort the results", "default": "hot" }, "timeFilter": { "title": "Time Filter", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Time range for 'top' sort. Only applies when sort is 'top'.", "default": "all" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of posts to scrape (1-500)", "default": 50 }, "includeComments": { "title": "Include Comments", "type": "boolean", "description": "Fetch top-level comments for each post. This will increase scraping time and API usage.", "default": false }, "commentDepth": { "title": "Comment Thread Depth", "minimum": 1, "maximum": 10, "type": "integer", "description": "How deep to fetch nested comment replies (1-10 levels). Only applies when Include Comments is enabled.", "default": 3 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Select proxies to use for scraping. Recommended for avoiding rate limits." } } }, "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 } } } } } } } } } } ```