# Reddit Subreddit Comments Export (`automationagents/reddit-subreddit-comments-export`) Actor Export Reddit subreddit comments as structured dataset output. - **URL**: https://apify.com/automationagents/reddit-subreddit-comments-export.md - **Developed by:** [Alex Jordan](https://apify.com/automationagents) (community) - **Categories:** Automation - **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 ### What does Reddit Subreddit Comments Export do? **Reddit Subreddit Comments Export** returns comments from a target subreddit as structured dataset output. It is useful for community analysis, moderation research, and audience insight workflows. Built on the **Apify platform**, this Actor supports scheduling, webhooks, and dataset exports. ### Why use Reddit Subreddit Comments Export? - **Community analysis** - Export comments from subreddit discussions - **Audience insights** - Understand recurring topics and sentiment - **Structured output** - Store comment data in sheets, dashboards, or internal tools ### How to use Reddit Subreddit Comments Export 1. Open the Actor on Apify 2. Enter the subreddit URL or identifier and result limit inputs 3. Start the run 4. Download the dataset output ### Input This Actor accepts the fields required to collect comments from a target subreddit. **Example input:** ```json { "subreddit": "marketing", "limit": 25 } ```` ### Output The Actor writes the collected subreddit comments to the default dataset. **Example output:** ```json { "success": true, "response": [ { "subreddit": "marketing", "author": "sample_user", "commentBody": "This channel worked well for us last quarter.", "commentUrl": "https://www.reddit.com/r/marketing/comments/example/", "score": 24 } ] } ``` ### Pricing / Cost estimation **$0.00054 per started block of up to 25 results** on Apify. - `1-25` results: `$0.00054` - `26-50` results: `$0.00108` - `51-75` results: `$0.00162` No result means no result-charge event. ### Support If you need adjustments for your workflow, use the Actor Issues tab or your internal support channel. # Actor input Schema ## `subRedditUrl` (type: `string`): Subreddit URL ## `maxCount` (type: `integer`): Max Count ## `sort` (type: `string`): Sort ## `cookieHeader` (type: `string`): Cookie Header ## `csrfToken` (type: `string`): CSRF Token ## `userAgent` (type: `string`): User-Agent ## `acceptLanguage` (type: `string`): Accept-Language ## `redditHost` (type: `string`): Reddit Host ## `referer` (type: `string`): Referer ## `origin` (type: `string`): Origin ## `proxy` (type: `object`): Proxy ## Actor input object example ```json { "maxCount": 10, "sort": "new", "acceptLanguage": "en-US,en;q=0.9", "redditHost": "www.reddit.com", "referer": "https://www.reddit.com/", "origin": "https://www.reddit.com", "proxy": { "ip": "http://portal.anyip.io", "port": "1080", "username": "", "password": "" } } ``` # 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 = { "maxCount": 10, "sort": "new", "acceptLanguage": "en-US,en;q=0.9", "redditHost": "www.reddit.com", "referer": "https://www.reddit.com/", "origin": "https://www.reddit.com", "proxy": { "ip": "http://portal.anyip.io", "port": "1080", "username": "", "password": "" } }; // Run the Actor and wait for it to finish const run = await client.actor("automationagents/reddit-subreddit-comments-export").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 = { "maxCount": 10, "sort": "new", "acceptLanguage": "en-US,en;q=0.9", "redditHost": "www.reddit.com", "referer": "https://www.reddit.com/", "origin": "https://www.reddit.com", "proxy": { "ip": "http://portal.anyip.io", "port": "1080", "username": "", "password": "", }, } # Run the Actor and wait for it to finish run = client.actor("automationagents/reddit-subreddit-comments-export").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 '{ "maxCount": 10, "sort": "new", "acceptLanguage": "en-US,en;q=0.9", "redditHost": "www.reddit.com", "referer": "https://www.reddit.com/", "origin": "https://www.reddit.com", "proxy": { "ip": "http://portal.anyip.io", "port": "1080", "username": "", "password": "" } }' | apify call automationagents/reddit-subreddit-comments-export --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automationagents/reddit-subreddit-comments-export", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Subreddit Comments Export", "description": "Export Reddit subreddit comments as structured dataset output.", "version": "0.3", "x-build-id": "Gk9Y41I683yvIEKLl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automationagents~reddit-subreddit-comments-export/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automationagents-reddit-subreddit-comments-export", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automationagents~reddit-subreddit-comments-export/runs": { "post": { "operationId": "runs-sync-automationagents-reddit-subreddit-comments-export", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automationagents~reddit-subreddit-comments-export/run-sync": { "post": { "operationId": "run-sync-automationagents-reddit-subreddit-comments-export", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "subRedditUrl", "maxCount", "sort" ], "properties": { "subRedditUrl": { "title": "Subreddit URL", "type": "string", "description": "Subreddit URL" }, "maxCount": { "title": "Max Count", "type": "integer", "description": "Max Count" }, "sort": { "title": "Sort", "enum": [ "new", "hot", "top", "relevance" ], "type": "string", "description": "Sort" }, "cookieHeader": { "title": "Cookie Header", "type": "string", "description": "Cookie Header" }, "csrfToken": { "title": "CSRF Token", "type": "string", "description": "CSRF Token" }, "userAgent": { "title": "User-Agent", "type": "string", "description": "User-Agent" }, "acceptLanguage": { "title": "Accept-Language", "type": "string", "description": "Accept-Language" }, "redditHost": { "title": "Reddit Host", "type": "string", "description": "Reddit Host" }, "referer": { "title": "Referer", "type": "string", "description": "Referer" }, "origin": { "title": "Origin", "type": "string", "description": "Origin" }, "proxy": { "title": "Proxy", "type": "object", "description": "Proxy" } } }, "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 } } } } } } } } } } ```