# Reddit User Profile Posts Comments Scraper (`solid-scraper/reddit-user-profile-posts-comments-scraper`) Actor 🚀 Scrape Reddit user profiles, comments, and posts with filters for keywords, subreddits, and engagement signals. Perfect for market research, influencer discovery, and community analytics—get actionable data fast. 📈 - **URL**: https://apify.com/solid-scraper/reddit-user-profile-posts-comments-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Social media, Lead generation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 User Profile Posts & Comments Scraper 🔍 **Reddit User Profile Posts & Comments Scraper** automatically collects Reddit post and comment activity from **user profile pages**, helping you turn public web data into structured datasets. Whether you’re using a **reddit user profile scraper** for research, building a **reddit comments scraper** for community insights, or running a **reddit posts scraper** for content mining—this actor streamlines scraping of a user’s overview activity into a clean output you can analyze. Designed for marketers, data analysts, and researchers, it saves you hours of manual work by organizing collected posts and comments from profile timelines at scale. --- ### Why choose Reddit User Profile Posts & Comments Scraper? | Feature | Benefit | |---|---| | ✅ **Posts + comments in one run** | Extracts both post and comment items from Reddit user profile listings so you don’t need separate tools | | ✅ **Profile URL input** | Works from a list of Reddit user profile URLs (`startUrls`) for fast setup and repeatable runs | | ✅ **Reliability-focused fetching** | Includes retries and fallbacks to improve successful page retrieval during longer batches | | ✅ **Structured dataset output** | Saves consistent fields like `type`, `subreddit`, `author`, `body`, `score`, `num_comments`, `url`, and `created_utc` | | ✅ **Scales across multiple profiles** | Processes each provided profile URL until it reaches `maxItems` or the profile has no further pages | | ✅ **Automation-ready** | Outputs directly into the Apify dataset for easy export (JSON/CSV) and downstream pipelines | --- ### Key features - 🧾 **Posts + comments collection:** Captures both `t3` (posts) and `t1` (comments) items from the user listing data and labels them with `type`. - 🔄 **Recursive replies extraction:** When comment items include nested replies, replies are recursively extracted into the output dataset. - 🧠 **Clean, consistent records:** Each saved item contains the same core fields (like `subreddit`, `author`, `title`, `body`, `score`, `num_comments`, `url`, `created_utc`), which makes analysis straightforward. - 💾 **Real-time dataset saving:** Items are pushed as pages are processed (not only at the end of the run), reducing risk of losing data. - 🌐 **Flexible start URLs:** Accepts a list of Reddit user profile URLs as input, so you can automate “scrape reddit user posts and comments” workflows. - 🛡️ **Resilience with retries:** Uses retry attempts per page fetch and rotates access when failures occur, improving success rate for bulk scraping jobs. - ⏳ **Limits for controlled runs:** Supports `maxPages` and `maxItems` so you can control runtime and output size for each batch. --- ### Input Provide input via an `input.json` file. Example structure: ```json { "startUrls": [ { "url": "https://www.reddit.com/user/redditusername123/" } ] } ```` #### Input Fields | Field | Required | Description | |---|---|---| | `startUrls` | ✅ | A list of Reddit user profile URLs to scrape posts & comments from. Example: `https://www.reddit.com/user/redditusername123/`. | *** ### Output The actor saves scraped Reddit items into the Apify dataset in JSON format. Example of a dataset record (single item): ```json { "type": "post", "subreddit": "exampleSub", "author": "exampleAuthor", "title": "Example post title", "body": "Example content", "score": 123, "num_comments": 45, "url": "https://www.reddit.com/r/exampleSub/comments/example", "created_utc": 1710000000 } ``` #### Output Fields | Field | Type | Description | |---|---|---| | `type` | string | Item type. Posts are labeled as `post`, comments as `comment` (with `unknown` used when kind is not available). | | `subreddit` | string | Subreddit where the post or comment belongs. | | `author` | string | Author username associated with the item. | | `title` | string | Title text for posts (may be empty depending on item type). | | `body` | string | Main content for the item (post or comment text). | | `score` | number | Reddit score for the item. | | `num_comments` | number | Comment count associated with the item (commonly for posts). | | `url` | string | Canonical link for the item. | | `created_utc` | number | Unix timestamp indicating when the item was created. | Note: Each scraped item is pushed into the dataset as pages are processed, making it easy to export as JSON or CSV after the run finishes. *** ### How to use Reddit User Profile Posts & Comments Scraper (via Apify Console) 1. **Open Apify Console** Log in at [console.apify.com](https://console.apify.com) and open the **Actors** tab. 2. **Find the actor** Search for **Reddit User Profile Posts & Comments Scraper** and open its listing. 3. **Add your input** In the **INPUT** section, provide your `startUrls` as a list of Reddit user profile URLs. Use URLs like: - `https://www.reddit.com/user/redditusername123/` 4. **Run the actor** Click **Run** to start scraping posts and comments from each provided profile. 5. **Monitor progress in logs** You’ll see an initial “Starting actor” message, and then processing continues while items are being pushed to the dataset page-by-page (including retry behavior when needed). 6. **Access your dataset** When the run finishes, open the **OUTPUT** tab and view the dataset named **Reddit Data** with the **Scraped Reddit Items** table view. 7. **Export results** Export the dataset as **JSON** or **CSV** for analysis, reporting, or integration into your pipeline. No coding required—get accurate Reddit profile data for posts and comments in minutes. *** ### Advanced features & SEO optimization - 🕒 **Designed for “reddit user profile history scraper” workflows:** The actor iterates through multiple pages per profile until it reaches `maxPages` or `maxItems`, making it ideal for “collect reddit user posts and comments” jobs. - 🔁 **Comment threading support:** Recursively extracts nested replies, which helps when you’re doing deeper **reddit timeline scraper** research rather than just top-level comments. - 📊 **Data completeness for analysis:** Outputs consistent fields across both posts and comments, so you can quickly analyze engagement (like `score`) and activity timing (`created_utc`). - 🧰 **Robust batch control:** Use `maxPages` and `maxItems` (where available in your run inputs) to manage performance when you scale up. - 📝 **Automation-friendly results:** Since everything is pushed into a dataset, it’s easy to plug into downstream “reddit scraper for post and comment data” pipelines. *** ### Best use cases - 📈 **Market researchers profiling community engagement:** Build a timeline of posts and comments to understand how users participate over time. - 🧑‍💼 **B2B marketers analyzing audience behavior:** Use the extracted activity to identify themes and engagement patterns for outreach targeting. - 🎓 **Academic or investigative research:** Gather structured Reddit content for content analysis, coding, and longitudinal studies. - 🧠 **Community managers tracking influential users:** Quickly compile user contributions from a profile’s activity and export for moderation or reporting. - 🧾 **Data analysts building enrichment datasets:** Join profile activity with your own CRM or research tables using stable fields like `author`, `subreddit`, and `created_utc`. - 💻 **Developer teams automating “scrape reddit account activity” pipelines:** Use dataset output to feed dashboards, notebooks, or ETL jobs. - 🔎 **Moderation & safety reviews (public data analysis):** Monitor how users engage across subreddits by collecting post and comment content for review workflows. *** ### Technical specifications - **Supported Input Formats** - ✅ `startUrls` as an array of Reddit user profile URLs (each entry uses the `url` shown in the schema description) - **Proxy Support** - ✅ Includes built-in proxy support aimed at reliable scraping (with an option to continue without proxy if proxy initialization fails) - **Retry Mechanism** - ✅ Uses multiple retry attempts per page fetch and rotates access when requests fail - **Dataset Structure** - ✅ Saves items to the Apify dataset view **Scraped Reddit Items** with fields including: - `type`, `subreddit`, `author`, `title`, `body`, `score`, `num_comments`, `url`, `created_utc` - **Limit Controls** - ✅ Controlled by `maxPages` and `maxItems` (the actor stops when either limit is reached) - **Limitations** - ❌ Requires valid, accessible public profile listing data for the actor to retrieve results - ❌ If a profile has no accessible listing data, fewer or no items may be produced *** ### FAQ #### What does this actor scrape from a Reddit user profile? ✅ It scrapes posts and comments associated with the user’s profile listing activity, and saves each item with a `type` of `post` or `comment`, along with fields like `subreddit`, `author`, `body`, `score`, `num_comments`, `url`, and `created_utc`. #### What input do I need to provide? You need to provide `startUrls`, which is a list of Reddit user profile URLs (for example: `https://www.reddit.com/user/redditusername123/`). The actor uses those profile URLs as the starting points to collect post and comment items. #### Do I need to write any code? ❌ No. You can use the Apify Console to enter your `startUrls`, run the actor, and download/export the resulting dataset. #### Does the scraper collect nested replies under comments? ✅ Yes. When comment items include nested replies, the actor recursively extracts those replies so you get a more complete set of collected discussion content. #### Where does the output go? The actor pushes scraped items into the Apify dataset named **Reddit Data**, shown under the default dataset view **Scraped Reddit Items** in a table format. #### What happens if requests fail for some pages? ✅ The actor includes retries and resilience logic to improve successful retrieval during runs. It also stops based on your `maxPages` and `maxItems` limits. #### Can I export results for analysis? ✅ Yes. After the run completes, you can export the dataset (for example as JSON or CSV) from the Apify dataset output. #### Is this meant for lead generation or contact scraping? This actor is focused on collecting Reddit posts and comments from user profiles, creating a structured dataset for analysis. It is not designed as a dedicated email or contact extractor. *** ### Support & feature requests If you’re using **Reddit User Profile Posts & Comments Scraper** for your next research or automation workflow, we’d love to hear what you need. - 💡 **Feature Requests:** Want enhancements like additional fields in the dataset, expanded control options, or better export workflows for your “reddit user profile scraper tool” use case? Share your ideas. - 📧 **Contact:** Email us at . Your feedback directly helps shape the roadmap for future improvements to this Reddit scraping actor. *** *If you need a reliable **Reddit User Profile Posts & Comments Scraper** to collect structured posts and comments at scale, you’re in the right place—this actor is built to make automation feel effortless.* # Actor input Schema ## `startUrls` (type: `array`): List of Reddit user profile URLs to scrape posts & comments from. Example: https://www.reddit.com/user/redditusername123/ ## Actor input object example ```json { "startUrls": [ { "url": "https://www.reddit.com/user/redditusername123/" } ] } ``` # 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 = { "startUrls": [ { "url": "https://www.reddit.com/user/redditusername123/" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/reddit-user-profile-posts-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 = { "startUrls": [{ "url": "https://www.reddit.com/user/redditusername123/" }] } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/reddit-user-profile-posts-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 '{ "startUrls": [ { "url": "https://www.reddit.com/user/redditusername123/" } ] }' | apify call solid-scraper/reddit-user-profile-posts-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/reddit-user-profile-posts-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit User Profile Posts Comments Scraper", "description": "🚀 Scrape Reddit user profiles, comments, and posts with filters for keywords, subreddits, and engagement signals. Perfect for market research, influencer discovery, and community analytics—get actionable data fast. 📈", "version": "0.1", "x-build-id": "hqmP8b2iZdtMnS4Xg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~reddit-user-profile-posts-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-reddit-user-profile-posts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~reddit-user-profile-posts-comments-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-reddit-user-profile-posts-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~reddit-user-profile-posts-comments-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-reddit-user-profile-posts-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "List of Reddit user profile URLs to scrape posts & comments from. Example: https://www.reddit.com/user/redditusername123/", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```