# Reddit Posts Scraper (`dt_org/dreemteam-reddit-posts`) Actor Extract public Reddit post search results with titles, URLs, subreddits, authors, scores, comment counts, flair, media, content snippets, and external links. - **URL**: https://apify.com/dt\_org/dreemteam-reddit-posts.md - **Developed by:** [DreamTeam](https://apify.com/dt_org) (community) - **Categories:** Automation, Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.80 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Posts Scraper Reddit Posts Scraper extracts public Reddit posts from keyword searches, topic pages, and community pages into clean dataset rows for social listening, trend research, market monitoring, and community discovery. Use it to find conversations around products, brands, niches, competitors, pain points, launches, controversies, and fast-moving topics across Reddit communities. This Actor is not affiliated with, endorsed by, or sponsored by Reddit. ### What It Collects Each dataset row represents one public Reddit post search result. The Actor can return: - search query, query type, and result rank - post title and Reddit URL - subreddit and public author name - upvotes, comment count, and awards when available - creation date or timestamp when available - post flair and author flair when available - media marker, post content, and external URL when available - promoted flag when available - per-query parser status in the run summary - optional raw page payloads in `RAW_PAGES` ### Common Use Cases - Monitor brand, product, or competitor mentions. - Discover communities discussing a topic. - Build social listening datasets for research teams. - Find Reddit posts for content, PR, or growth analysis. - Track emerging complaints, requests, or market signals. - Collect lead and audience research around a niche. ### Input Provide one or more Reddit search queries, topic URLs, community URLs, or search URLs and choose how many posts to save per query. ```json { "queries": ["SaaS pricing"], "maxResultsPerQuery": 10, "maxPages": 2, "sort": "Relevance", "timeRange": "All time", "deduplicate": true } ```` #### Input Fields - `queries` - Reddit search keywords, phrases, topic URLs, community URLs, or Reddit search URLs. - `maxQueries` - maximum number of queries processed from the list. - `maxResultsPerQuery` - maximum number of post rows saved for each query. - `maxPages` - maximum number of Reddit result pages requested per query. - `sort` - result sorting: relevance, hot, top, new, or comments. - `timeRange` - result time range: all time, hour, day, week, month, or year. - `includeRawData` - writes raw page payloads to `RAW_PAGES` when the source returns them; if not available, the run summary records a warning. - `deduplicate` - removes repeated post rows within the same query. ### Example Queries ```json { "queries": ["SaaS pricing", "AI", "fitness app"], "maxResultsPerQuery": 25, "maxPages": 5, "sort": "New", "timeRange": "Month", "deduplicate": true } ``` Community and topic examples: ```json { "queries": [ "https://www.reddit.com/r/SaaS/", "https://www.reddit.com/t/bitcoin/" ], "maxResultsPerQuery": 20, "maxPages": 3, "sort": "Top", "timeRange": "Month", "deduplicate": true } ``` ### Output Dataset rows are flat and ready for export to JSON, CSV, Excel, databases, or BI tools. ### Result Counting Each saved Reddit post counts as one dataset result. Run summaries, empty results, warnings, errors, and quota-limit messages are written to `OUTPUT`, not as paid dataset rows. Example row: ```json { "query": "SaaS pricing", "queryType": "keyword", "rank": 1, "title": "How do you price your SaaS?", "postUrl": "https://www.reddit.com/r/SaaS/comments/example/post/", "subreddit": "SaaS", "author": "example_user", "upvotes": 1250, "commentsCount": 184, "content": "A discussion about pricing a software product.", "source": "reddit", "collectedAt": "2026-07-05T00:00:00+00:00" } ``` ### Limits And Notes - Results are public Reddit search results and may vary over time. - The Actor collects Reddit post rows in V1. It does not collect full comment threads, subreddit profiles, or user profiles in this version. - Raw page payload availability depends on the source response. Dataset rows remain complete even when raw pages are not returned. - Empty or blocked runs are reported in the `OUTPUT` summary and do not create fake paid dataset rows. - Start with a small query set, review coverage, then scale to scheduled monitoring. # Actor input Schema ## `queries` (type: `array`): Reddit search keywords or phrases to collect public posts for, such as SaaS pricing, AI, fitness app, skincare, or electric cars. ## `maxQueries` (type: `integer`): Maximum number of search queries processed from the list. ## `maxResultsPerQuery` (type: `integer`): Maximum number of Reddit post results saved for each query. ## `maxPages` (type: `integer`): Maximum number of Reddit result pages requested from the source for each query before applying the post row limit. ## `sort` (type: `string`): Reddit result sorting used by the source. ## `timeRange` (type: `string`): Reddit result time range used by the source. ## `includeRawData` (type: `boolean`): Save raw page payloads to the RAW\_PAGES key-value store record for debugging or advanced enrichment. Dataset rows stay flat. ## `deduplicate` (type: `boolean`): Remove repeated post rows within the same query while keeping the same post when it appears for different queries. ## Actor input object example ```json { "queries": [ "SaaS pricing" ], "maxQueries": 10, "maxResultsPerQuery": 10, "maxPages": 2, "sort": "Relevance", "timeRange": "All time", "includeRawData": false, "deduplicate": true } ``` # Actor output Schema ## `results` (type: `string`): Dataset rows produced by this Actor. ## `summary` (type: `string`): Structured run status, counts, quota status, warnings, and errors. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("dt_org/dreemteam-reddit-posts").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 = {} # Run the Actor and wait for it to finish run = client.actor("dt_org/dreemteam-reddit-posts").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 '{}' | apify call dt_org/dreemteam-reddit-posts --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dt_org/dreemteam-reddit-posts", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Posts Scraper", "description": "Extract public Reddit post search results with titles, URLs, subreddits, authors, scores, comment counts, flair, media, content snippets, and external links.", "version": "0.1", "x-build-id": "VhFLpE2HT8LfJzXUk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dt_org~dreemteam-reddit-posts/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dt_org-dreemteam-reddit-posts", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dt_org~dreemteam-reddit-posts/runs": { "post": { "operationId": "runs-sync-dt_org-dreemteam-reddit-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dt_org~dreemteam-reddit-posts/run-sync": { "post": { "operationId": "run-sync-dt_org-dreemteam-reddit-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "queries": { "title": "Search Queries", "type": "array", "description": "Reddit search keywords or phrases to collect public posts for, such as SaaS pricing, AI, fitness app, skincare, or electric cars.", "items": { "type": "string" }, "default": [ "SaaS pricing" ] }, "maxQueries": { "title": "Max Queries", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of search queries processed from the list.", "default": 10 }, "maxResultsPerQuery": { "title": "Max Posts Per Query", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of Reddit post results saved for each query.", "default": 10 }, "maxPages": { "title": "Max Reddit Pages Per Query", "minimum": 1, "maximum": 10, "type": "integer", "description": "Maximum number of Reddit result pages requested from the source for each query before applying the post row limit.", "default": 2 }, "sort": { "title": "Sort", "enum": [ "Relevance", "Hot", "Top", "New", "Comments" ], "type": "string", "description": "Reddit result sorting used by the source.", "default": "Relevance" }, "timeRange": { "title": "Time Range", "enum": [ "All time", "Hour", "Day", "Week", "Month", "Year" ], "type": "string", "description": "Reddit result time range used by the source.", "default": "All time" }, "includeRawData": { "title": "Include Raw Pages", "type": "boolean", "description": "Save raw page payloads to the RAW_PAGES key-value store record for debugging or advanced enrichment. Dataset rows stay flat.", "default": false }, "deduplicate": { "title": "Deduplicate Results", "type": "boolean", "description": "Remove repeated post rows within the same query while keeping the same post when it appears for different queries.", "default": true } } }, "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 } } } } } } } } } } ```