# Reddit Scraper Lite (`caa_software/reddit-scraper-lite`) Actor Unlimited Reddit web scraper to crawl posts and comments without login. Limit web scraping by number of posts or items and extract all data in a dataset in multiple formats. - **URL**: https://apify.com/caa\_software/reddit-scraper-lite.md - **Developed by:** [CAA Software](https://apify.com/caa_software) (community) - **Categories:** Social media, Automation, AI - **Stats:** 6 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.50 / 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 Lite A lightweight, high-performance Reddit scraping tool designed to extract comments and post metadata with ease. Built with Python, this actor is optimized for speed and reliability, making it perfect for sentiment analysis, academic research, or community monitoring. ### 🌟 Key Features - **Fast & Efficient:** Optimized to bypass common bottlenecks and deliver results in seconds. - **Deep Metadata:** Captures not just text, but upvotes, timestamps, author details, and more. - **Custom Sorting:** Supports all native Reddit sorting methods to help you get the most relevant data. - **Scalable:** Seamlessly handles everything from a single discussion to large threads with up to 1,000 comments. ### 🛠️ Input Parameters You can customize your crawl using the following parameters in the input tab: | Parameter | Type | Description | Default | | :--- | :--- | :--- | :--- | | **Reddit Post URL** | `string` | The full link to the Reddit thread you want to scrape. | Required | | **Limit** | `integer` | Maximum number of comments to retrieve (Max: 1000). | `10` | | **Sort** | `select` | The criteria used to order comments (Hot, New, Top, etc.). | `hot` | --- ### 🚀 How to Use 1. **Provide a URL:** Copy and paste the link of any Reddit post. 2. **Set Your Limits:** Choose how many comments you need and how they should be sorted. 3. **Run the Actor:** Click "Start." The data will be populated in the `Dataset` tab in real-time. 4. **Export Data:** Download your results in **JSON, CSV, Excel, or XML** formats for further analysis. [Image of web scraping data flow from website to structured JSON/CSV file] --- ### 📊 Sample Output The scraper delivers clean, structured data ready for your next project: ```json { "id": "o6n....", "author": "reddit_user_123", "body": "This is a sample comment extracted from the thread.", "score": 120, "likes": 190, "dislikes": 0, "permalink": "https://www.reddit.com/r/Turkey/comments/1raz1zp/otopark_çizgileri_süs_mü/o6n8ilv/", "created_utc": 1771700098, "created": 1771700098, "created_at": "2026-02-21 18:54:58", "created_utc_at": "2026-02-21 18:54:58", "depth": 0, "replies": [ { "id": "o6ngq90", "author": "Kerbalgalactic", "body": "This is a sample comment extracted from the thread.", "score": 42, "likes": 42, "dislikes": 0, "permalink": "https://www.reddit.com/r/Turkey/comments/1raz1zp/otopark_çizgileri_süs_mü/o6ngq90/", "created_utc": 1771702579, "created": 1771702579, "created_at": "2026-02-21 19:36:19", "created_utc_at": "2026-02-21 19:36:19", "depth": 1, "replies": [] } ] } # Actor input Schema ## `url` (type: `string`): URL to start with ## `limit` (type: `integer`): Comments limit ## `sort` (type: `string`): Sorting of comments ## Actor input object example ```json { "url": "https://www.reddit.com/r/Turkey/comments/1raz1zp/otopark_%C3%A7izgileri_s%C3%BCs_m%C3%BC/", "limit": 10, "sort": "hot" } ```` # Actor output Schema ## `overview` (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 = { "url": "https://www.reddit.com/r/Turkey/comments/1raz1zp/otopark_%C3%A7izgileri_s%C3%BCs_m%C3%BC/" }; // Run the Actor and wait for it to finish const run = await client.actor("caa_software/reddit-scraper-lite").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 = { "url": "https://www.reddit.com/r/Turkey/comments/1raz1zp/otopark_%C3%A7izgileri_s%C3%BCs_m%C3%BC/" } # Run the Actor and wait for it to finish run = client.actor("caa_software/reddit-scraper-lite").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 '{ "url": "https://www.reddit.com/r/Turkey/comments/1raz1zp/otopark_%C3%A7izgileri_s%C3%BCs_m%C3%BC/" }' | apify call caa_software/reddit-scraper-lite --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=caa_software/reddit-scraper-lite", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper Lite", "description": "Unlimited Reddit web scraper to crawl posts and comments without login. Limit web scraping by number of posts or items and extract all data in a dataset in multiple formats.", "version": "0.0", "x-build-id": "Va4jo5hH0gpZk7OFU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/caa_software~reddit-scraper-lite/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-caa_software-reddit-scraper-lite", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/caa_software~reddit-scraper-lite/runs": { "post": { "operationId": "runs-sync-caa_software-reddit-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/caa_software~reddit-scraper-lite/run-sync": { "post": { "operationId": "run-sync-caa_software-reddit-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "url", "sort" ], "properties": { "url": { "title": "Reddit Post Url", "type": "string", "description": "URL to start with" }, "limit": { "title": "Limit", "maximum": 1000, "type": "integer", "description": "Comments limit", "default": 10 }, "sort": { "title": "Sort", "enum": [ "hot", "new", "top", "confidence", "old" ], "type": "string", "description": "Sorting of comments", "default": "hot" } } }, "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 } } } } } } } } } } ```