# Reddit User Comments Scraper — Full History (`toolzerhub/reddit-user-comments-scraper`) Actor Collect comments posted by a Reddit user and sort them by New, Hot, or Top. Paginate automatically and export structured comment records for audience or account research. - **URL**: https://apify.com/toolzerhub/reddit-user-comments-scraper.md - **Developed by:** [ToolzerHub](https://apify.com/toolzerhub) (community) - **Categories:** Social media, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 80.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.05 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 **Collect the comments a Reddit user has posted, sorted by New, Hot, or Top.** Reddit User Comments Scraper is the ToolzerHub discussion-footprint tool for one account. Give it a username and it walks through every reply they've left across subreddits, up to your result cap. ### A discussion footprint takes just a username Provide a username, choose New, Hot, or Top, and set Max Results to bound how deep the reply footprint pull goes. #### Scrape a user's comments Enter a username, choose a sort mode, and set Max Results. Pagination is handled automatically. | Field | Type | Required | Description | | --- | --- | --- | --- | | `username` | string | Yes | Reddit username (without u/), or a profile URL (https://www.reddit.com/user//). | | `sort` | string | No | Sort order for the feed or listing. | | `maxItems` | integer | No | Maximum number of items to save. Set 0 for no limit. | #### Example reply footprint pull ```json { "username": "Turbulent_Nerve3744", "sort": "NEW", "maxItems": 50 } ```` ### Reply records built for tone and sentiment review #### 💬 Comment identity | Field | Type | Description | | --- | --- | --- | | `id` | string | Reddit fullname or ID of the item (post, comment, or search result). | | `username` | string | Reddit username associated with the item. | | `subreddit` | string | Subreddit display name the item belongs to. | #### 📊 Engagement signals | Field | Type | Description | | --- | --- | --- | | `created_at` | string | Creation timestamp reported by the source payload. | | `score` | number | Net score (upvotes minus downvotes) when available. | | `upvotes` | number | Upvote count when reported separately from score. | #### Reply footprint preview ```json { "id": "abcd123", "username": "Turbulent_Nerve3744", "subreddit": "pics", "score": 84 } ``` ### What a footprint pull costs This Actor uses Apify pay-per-result pricing. You are charged for successful dataset results according to the Actor pricing shown on the Apify Pricing tab. Apify's free credits may cover small test runs and up to the free result allowance configured for the Actor. Use Max Results to bound a run before scaling to larger subreddits, users, or query lists. ### Fair use of a reply footprint This Actor extracts publicly available Reddit content. It should not be used to collect private user data. Make sure your use case complies with applicable privacy laws, Reddit's terms, and your own legal obligations. If you are unsure, consult a qualified lawyer. ### Run this Actor from code #### Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_API_TOKEN") run = client.actor("toolzerhub/reddit-user-comments-scraper").call(run_input={ "username": "Turbulent_Nerve3744", "sort": "NEW", "maxItems": 50 }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` #### Node.js ```javascript import { ApifyClient } from "apify-client"; const client = new ApifyClient({ token: "YOUR_APIFY_API_TOKEN" }); const run = await client.actor("toolzerhub/reddit-user-comments-scraper").call({ "username": "Turbulent_Nerve3744", "sort": "NEW", "maxItems": 50 }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Cross-reference the profile card or submitted posts - [Reddit User Profile Scraper — Karma & Trophies](https://apify.com/toolzerhub/reddit-user-profile-scraper) — Fetch a Reddit user's public profile by username, including account and karma data. Enable the optional detail add-on to include the trophy case and active subreddit information. - [Reddit User Posts Scraper — Full History](https://apify.com/toolzerhub/reddit-user-posts-scraper) — Collect posts submitted by a Reddit user and sort them by New, Hot, or Top. Paginate automatically and export structured post and engagement records for analysis. - [Reddit Search Scraper — Posts, Users & More](https://apify.com/toolzerhub/reddit-search-scraper) — Search Reddit by keyword across posts, users, subreddits, or comments. Choose the result type, paginate automatically, and export structured search results for research and monitoring. ### ToolzerHub support Use the Issues tab on the Actor page for bug reports, missing fields, and feature requests. Contact: contact@toolzerhub.com # Actor input Schema ## `username` (type: `string`): Reddit username (without u/), or a profile URL (https://www.reddit.com/user//). ## `sort` (type: `string`): Sort order for the feed or listing. ## `maxItems` (type: `integer`): Maximum number of items to save. Set 0 for no limit. ## Actor input object example ```json { "username": "Turbulent_Nerve3744", "sort": "NEW", "maxItems": 20 } ``` # Actor output Schema ## `dataset` (type: `string`): Dataset containing all scraped data # 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 = { "username": "Turbulent_Nerve3744", "maxItems": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("toolzerhub/reddit-user-comments-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 = { "username": "Turbulent_Nerve3744", "maxItems": 20, } # Run the Actor and wait for it to finish run = client.actor("toolzerhub/reddit-user-comments-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 '{ "username": "Turbulent_Nerve3744", "maxItems": 20 }' | apify call toolzerhub/reddit-user-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=toolzerhub/reddit-user-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit User Comments Scraper — Full History", "description": "Collect comments posted by a Reddit user and sort them by New, Hot, or Top. Paginate automatically and export structured comment records for audience or account research.", "version": "0.1", "x-build-id": "ghqAcBZcw91ws3wFu" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/toolzerhub~reddit-user-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-toolzerhub-reddit-user-comments-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/toolzerhub~reddit-user-comments-scraper/runs": { "post": { "operationId": "runs-sync-toolzerhub-reddit-user-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/toolzerhub~reddit-user-comments-scraper/run-sync": { "post": { "operationId": "run-sync-toolzerhub-reddit-user-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "username" ], "properties": { "username": { "title": "Username", "type": "string", "description": "Reddit username (without u/), or a profile URL (https://www.reddit.com/user//)." }, "sort": { "title": "Sort", "enum": [ "NEW", "HOT", "TOP" ], "type": "string", "description": "Sort order for the feed or listing.", "default": "NEW" }, "maxItems": { "title": "Max Results", "minimum": 0, "type": "integer", "description": "Maximum number of items to save. Set 0 for no limit.", "default": 100 } } }, "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 } } } } } } } } } } ```