# ForRentUniversity Scraper - Low-costπŸ’²πŸ”₯πŸŽ“πŸ  (`delectable_incubator/forrentuniversity-scraper-low-cost`) Actor Scrape ForRentUniversity listings πŸ πŸŽ“ with a powerful student housing scraper. Extract property addresses, property types, rental prices, beds, contact details, images & URLs from multiple sources. Ideal for student housing research, rental market analysis, lead generation & real estate datasets πŸ“Š - **URL**: https://apify.com/delectable\_incubator/forrentuniversity-scraper-low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** Lead generation, Real estate, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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

ForRentUniversity Apartment Scraper

--- ## ForRentUniversity Apartment Listings Scraper | Student Housing Data Extractor πŸ πŸŽ“ ### πŸš€ Extract Student Housing Data in Seconds (No Code) The **ForRentUniversity Apartment Listings Scraper (Apify Actor)** is a powerful, scalable and SEO-optimized real estate data extraction tool designed to collect structured student housing listings from ForRentUniversity. It allows you to **scrape university housing listings in bulk**, extract structured rental data, and export it for **real estate analytics, student housing platforms, market research, and AI datasets**. --- ### πŸ”₯ Why This ForRentUniversity Scraper? βœ” Best ForRentUniversity scraper on Apify βœ” Supports bulk URL scraping (multi-university mode) βœ” Fast & scalable student housing data extraction βœ” 100% structured JSON / CSV / Excel output βœ” Ideal for student housing market intelligence βœ” Perfect for real estate analysts & developers βœ” No coding required --- ### 🎯 What This Scraper Does (Apartment Data Extraction) This Apify Actor extracts real-time apartment listings from ForRentUniversity search pages. πŸ“Œ Core Features: - Scrape student housing listings near universities - Extract apartment pricing & property details - Auto pagination handling - Bulk URL processing - Extract contact & listing information - High-speed scraping engine - Clean structured dataset output --- ### ⚑ Input Configuration (Simple & Powerful) πŸ”₯ BULK URL MODE ```` { "urls": \[ "https://www.forrentuniversity.com/Austin-College", "https://www.forrentuniversity.com/New-York-Law-School", "https://www.forrentuniversity.com/Boston-University" ], "maxitems": 50 } ``` --- ### πŸ“Š Extracted Apartment Data (Structured Output) Field description: - propId β†’ Unique property identifier - address β†’ Property address - propertyType β†’ Type of property (Apartment, House, etc.) - price β†’ Rental price range - beds β†’ Number of bedrooms - phone β†’ Contact phone number - postedLabel β†’ Posting time label (e.g. "3 days ago") - postedAt β†’ Exact posting date (ISO format) - imageUrl β†’ Main property image - listingUrl β†’ Direct listing page --- ### πŸ’‘ Use Cases (High Demand SEO Keywords) This ForRentUniversity scraper is used for: 🏠 Student housing market research πŸ“Š Rental price analysis πŸŽ“ University accommodation tracking 🧠 Real estate AI datasets πŸ“ˆ Housing availability monitoring 🏒 Property management intelligence πŸ”Ž Rental comparison platforms πŸ“‘ Multi-city housing analytics --- ### πŸš€ Key Features (Apify SEO Optimized) ⚑ Bulk university URL scraping 🌍 Student housing coverage (US universities) πŸ“Œ Smart pagination system 🧠 Clean structured output πŸ“Š High-speed scraping engine πŸ” Auto retry & stability system πŸ’Ύ Export-ready datasets βš™οΈ Scalable cloud execution (Apify Actor) --- ### πŸ“€ Output Formats Supported βœ” JSON (API-ready) βœ” CSV (Excel analysis) βœ” Excel XLSX (reports) βœ” XML (data pipelines) βœ” HTML (dashboards) --- ### πŸ“¦ Example Output ``` { "propId": "bsgblc8", "listingUrl": "https://www.forrentuniversity.com/nj/jersey-city/the-hendrix/bsgblc8", "imageUrl": "https://images1.forrent.com/i2/8f\_SK4SmS-oIsMi0Ndw6kziWBLQhrfTeTsUDINaywsM/117/image.jpg?p=1", "address": "180 Morgan St, Jersey City, NJ 07302", "propertyType": "Apartment", "price": "$3,300 - $11,100", "beds": "Studio - 3 Beds", "phone": "Call (973) 354-5231", "postedAt": "2025-10-03T06:14:39.583Z", "postedLabel": "2 Wks Ago" } ```` --- ### πŸ”₯ Why This is the BEST ForRentUniversity Scraper on Apify? βœ” Optimized for marketplace SEO ranking βœ” High-performance real estate scraping engine βœ” Bulk university scraping support (rare feature) βœ” Clean structured student housing dataset βœ” Enterprise-ready scalability βœ” Perfect for AI & real estate pipelines --- ### πŸ’Έ Pricing This scraper runs on a **pay-per-result pricing model**. You only pay for successfully extracted records. πŸ’³ **Price:** $1.20 / 1,000 results --- ### ❓ FAQ (SEO BOOST SECTION) #### Can I scrape multiple universities at once? Yes β€” bulk URL mode is fully supported. #### Does it support student housing only? Yes β€” fully optimized for university housing listings. #### Is this scraper fast? Yes β€” built for high-speed extraction. #### Can I export data? Yes β€” JSON, CSV, Excel, XML supported. #### Is coding required? No β€” 100% no-code Apify Actor. --- ### ⚠️ Disclaimer This tool is not affiliated with ForRentUniversity. It is an independent data extraction solution. --- ### 🏠 Student Housing Intelligence Use Cases πŸ’‘ Rental trend tracking πŸ“Š University housing analytics πŸŽ“ Student accommodation databases πŸ€– AI training datasets πŸ“ˆ Real estate monitoring tools 🏒 Property comparison systems --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a 5-star review if you like this scraper πŸ“© Contact for custom scraping solutions or enterprise requests --- # Actor input Schema ## `urls` (type: `array`): List of forrentuniversity.com search URLs to scrape. Pagination is handled automatically. Examples: β€’ https://www.forrentuniversity.com/Austin-College β€’ https://www.forrentuniversity.com/New-York-Law-School ⚠️ Each URL must be from forrentuniversity.com. ## `maxitems` (type: `integer`): Maximum number of apartment listings to collect per URL. The scraper paginates automatically until this number is reached. ## Actor input object example ```json { "urls": [ "https://www.forrentuniversity.com/Austin-College" ], "maxitems": 100 } ```` # 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 = { "urls": [ "https://www.forrentuniversity.com/Austin-College" ], "maxitems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/forrentuniversity-scraper-low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "urls": ["https://www.forrentuniversity.com/Austin-College"], "maxitems": 100, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/forrentuniversity-scraper-low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "urls": [ "https://www.forrentuniversity.com/Austin-College" ], "maxitems": 100 }' | apify call delectable_incubator/forrentuniversity-scraper-low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/forrentuniversity-scraper-low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ForRentUniversity Scraper - Low-costπŸ’²πŸ”₯πŸŽ“πŸ ", "description": "Scrape ForRentUniversity listings πŸ πŸŽ“ with a powerful student housing scraper. Extract property addresses, property types, rental prices, beds, contact details, images & URLs from multiple sources. Ideal for student housing research, rental market analysis, lead generation & real estate datasets πŸ“Š", "version": "0.0", "x-build-id": "xVJl4GUgZn1ERI5CH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~forrentuniversity-scraper-low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-forrentuniversity-scraper-low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~forrentuniversity-scraper-low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-forrentuniversity-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~forrentuniversity-scraper-low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-forrentuniversity-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "urls", "maxitems" ], "properties": { "urls": { "title": "ForRentUniversity Search URLs 🏠", "type": "array", "description": "List of forrentuniversity.com search URLs to scrape. Pagination is handled automatically.\n\nExamples:\nβ€’ https://www.forrentuniversity.com/Austin-College\nβ€’ https://www.forrentuniversity.com/New-York-Law-School\n\n⚠️ Each URL must be from forrentuniversity.com.", "items": { "type": "string" } }, "maxitems": { "title": "Maximum Listings per URL πŸ“„", "type": "integer", "description": "Maximum number of apartment listings to collect per URL. The scraper paginates automatically until this number is reached.", "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 } } } } } } } } } } ```