How to Scrape Apartments.com | Apartments.com Web Scraper Guide

Learn how to scrape Apartments.com to extract rental listings, pricing, and amenities. Overcome Akamai bot protection to collect valuable US real estate data.

Coverage:United States
Available Data10 fields
TitlePriceLocationDescriptionImagesSeller InfoContact InfoPosting DateCategoriesAttributes
All Extractable Fields
Property NameFull Street AddressCityStateZip CodeMonthly Rent RangeUnit AvailabilityBedroom CountBathroom CountSquare FootagePet Policy DetailsBuilding AmenitiesIn-Unit FeaturesProperty Manager InfoContact Phone NumberDetailed DescriptionImage URLsWalk ScoreTransit Score
Technical Requirements
JavaScript Required
No Login
Has Pagination
No Official API
Anti-Bot Protection Detected
Akamai Bot ManagerCloudflarereCAPTCHARate LimitingTLS Fingerprinting

Anti-Bot Protection Detected

Akamai Bot Manager
Advanced bot detection using device fingerprinting, behavior analysis, and machine learning. One of the most sophisticated anti-bot systems.
Cloudflare
Enterprise-grade WAF and bot management. Uses JavaScript challenges, CAPTCHAs, and behavioral analysis. Requires browser automation with stealth settings.
Google reCAPTCHA
Google's CAPTCHA system. v2 requires user interaction, v3 runs silently with risk scoring. Can be solved with CAPTCHA services.
Rate Limiting
Limits requests per IP/session over time. Can be bypassed with rotating proxies, request delays, and distributed scraping.
Browser Fingerprinting
Identifies bots through browser characteristics: canvas, WebGL, fonts, plugins. Requires spoofing or real browser profiles.

About Apartments.com

Learn what Apartments.com offers and what valuable data can be extracted from it.

Overview of Apartments.com

Apartments.com is a premier online marketplace for residential rental properties in the United States, managed by the CoStar Group. It features an extensive database of millions of active listings, including apartments, condos, townhomes, and single-family houses. The platform is renowned for providing granular details such as high-resolution imagery, floor plans, and verified availability, making it a cornerstone for US rental market analysis.

The Value of the Data

Data extracted from this platform is indispensable for real estate investors, property managers, and economic researchers. It provides a real-time window into rental pricing trends, vacancy rates, and amenity popularity across different metropolitan areas. By aggregating this information, businesses can perform competitive benchmarking and identify emerging investment hotspots with high precision.

Why Scraping is Essential

Manual data collection from Apartments.com is nearly impossible due to the sheer volume of listings and the frequency of updates. Automated scraping allows for the systematic tracking of price fluctuations and new listing alerts, which are critical for staying competitive in the fast-paced residential rental sector.

About Apartments.com

Why Scrape Apartments.com?

Discover the business value and use cases for extracting data from Apartments.com.

Conduct hyper-local rental market price analysis

Monitor competitor vacancy and pricing strategies

Generate high-quality leads for property service providers

Gather historical data for urban development research

Track amenity trends across different demographics

Automate property investment valuation models

Scraping Challenges

Technical challenges you may encounter when scraping Apartments.com.

Aggressive Akamai bot protection and TLS fingerprinting

Heavily dynamic content rendered via JavaScript

Strict rate limiting on search result iterations

Complex multi-layered DOM structures for floor plans

Frequent UI updates that break static CSS selectors

Scrape Apartments.com with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

1

Describe What You Need

Tell the AI what data you want to extract from Apartments.com. Just type it in plain language — no coding or selectors needed.

2

AI Extracts the Data

Our artificial intelligence navigates Apartments.com, handles dynamic content, and extracts exactly what you asked for.

3

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Bypasses Akamai and WAF blocks automatically
No-code visual selection of property attributes
Cloud execution for 24/7 price monitoring
Seamless handling of dynamic pagination and AJAX
No credit card requiredFree tier availableNo setup needed

AI makes it easy to scrape Apartments.com without writing any code. Our AI-powered platform uses artificial intelligence to understand what data you want — just describe it in plain language and the AI extracts it automatically.

How to scrape with AI:
  1. Describe What You Need: Tell the AI what data you want to extract from Apartments.com. Just type it in plain language — no coding or selectors needed.
  2. AI Extracts the Data: Our artificial intelligence navigates Apartments.com, handles dynamic content, and extracts exactly what you asked for.
  3. Get Your Data: Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.
Why use AI for scraping:
  • Bypasses Akamai and WAF blocks automatically
  • No-code visual selection of property attributes
  • Cloud execution for 24/7 price monitoring
  • Seamless handling of dynamic pagination and AJAX

No-Code Web Scrapers for Apartments.com

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Apartments.com. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

1
Install browser extension or sign up for the platform
2
Navigate to the target website and open the tool
3
Point-and-click to select data elements you want to extract
4
Configure CSS selectors for each data field
5
Set up pagination rules to scrape multiple pages
6
Handle CAPTCHAs (often requires manual solving)
7
Configure scheduling for automated runs
8
Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

No-Code Web Scrapers for Apartments.com

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Apartments.com. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools
  1. Install browser extension or sign up for the platform
  2. Navigate to the target website and open the tool
  3. Point-and-click to select data elements you want to extract
  4. Configure CSS selectors for each data field
  5. Set up pagination rules to scrape multiple pages
  6. Handle CAPTCHAs (often requires manual solving)
  7. Configure scheduling for automated runs
  8. Export data to CSV, JSON, or connect via API
Common Challenges
  • Learning curve: Understanding selectors and extraction logic takes time
  • Selectors break: Website changes can break your entire workflow
  • Dynamic content issues: JavaScript-heavy sites often require complex workarounds
  • CAPTCHA limitations: Most tools require manual intervention for CAPTCHAs
  • IP blocking: Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Target URL for a specific city
url = 'https://www.apartments.com/new-york-ny/'

# Realistic headers are mandatory to avoid immediate blocking
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9',
    'Referer': 'https://www.google.com/'
}

try:
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Selectors may change; always inspect the current DOM
        listings = soup.select('.placardContainer .property-title')
        for item in listings:
            print(f'Listing Found: {item.get_text(strip=True)}')
    else:
        print(f'Blocked: Status Code {response.status_code}')
except Exception as e:
    print(f'Error: {str(e)}')

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

  • Fastest execution (no browser overhead)
  • Lowest resource consumption
  • Easy to parallelize with asyncio
  • Great for APIs and static pages

Limitations

  • Cannot execute JavaScript
  • Fails on SPAs and dynamic content
  • May struggle with complex anti-bot systems

How to Scrape Apartments.com with Code

Python + Requests
import requests
from bs4 import BeautifulSoup

# Target URL for a specific city
url = 'https://www.apartments.com/new-york-ny/'

# Realistic headers are mandatory to avoid immediate blocking
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9',
    'Referer': 'https://www.google.com/'
}

try:
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Selectors may change; always inspect the current DOM
        listings = soup.select('.placardContainer .property-title')
        for item in listings:
            print(f'Listing Found: {item.get_text(strip=True)}')
    else:
        print(f'Blocked: Status Code {response.status_code}')
except Exception as e:
    print(f'Error: {str(e)}')
Python + Playwright
from playwright.sync_api import sync_playwright

def scrape_apartments():
    with sync_playwright() as p:
        # Launching with stealth-like parameters
        browser = p.chromium.launch(headless=True)
        context = browser.new_context(user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) Chrome/119.0.0.0')
        page = context.new_page()
        
        # Navigate to a listing page
        page.goto('https://www.apartments.com/los-angeles-ca/', wait_until='networkidle')
        
        # Wait for the main listings container to load
        page.wait_for_selector('.placard')
        
        # Extracting property names and prices
        properties = page.query_selector_all('.placard')
        for prop in properties:
            name = prop.query_selector('.property-title').inner_text()
            price = prop.query_selector('.property-pricing').inner_text() if prop.query_selector('.property-pricing') else 'N/A'
            print(f'Property: {name} | Price: {price}')
            
        browser.close()

scrape_apartments()
Python + Scrapy
import scrapy

class ApartmentsSpider(scrapy.Spider):
    name = 'apartments_spider'
    start_urls = ['https://www.apartments.com/chicago-il/']

    custom_settings = {
        'USER_AGENT': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) Chrome/119.0.0.0',
        'CONCURRENT_REQUESTS': 1,
        'DOWNLOAD_DELAY': 3
    }

    def parse(self, response):
        for listing in response.css('article.placard'):
            yield {
                'name': listing.css('.property-title::text').get(),
                'address': listing.css('.property-address::text').get(),
                'price': listing.css('.property-pricing::text').get(),
            }

        next_page = response.css('a.next::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)
Node.js + Puppeteer
const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  
  // Set a realistic user agent
  await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) Chrome/119.0.0.0');

  try {
    await page.goto('https://www.apartments.com/houston-tx/', { waitUntil: 'networkidle2' });
    
    const data = await page.evaluate(() => {
      const items = Array.from(document.querySelectorAll('.placard'));
      return items.map(item => ({
        title: item.querySelector('.property-title')?.innerText,
        price: item.querySelector('.property-pricing')?.innerText,
        link: item.querySelector('a.property-link')?.href
      }));
    });

    console.log(data);
  } catch (err) {
    console.error('Extraction failed:', err);
  } finally {
    await browser.close();
  }
})();

What You Can Do With Apartments.com Data

Explore practical applications and insights from Apartments.com data.

Real-Time Market Indexing

Create a dashboard that tracks average rent prices across the US to assist economic forecasting.

How to implement:

  1. 1Scrape listings for the top 100 US cities daily.
  2. 2Categorize data by bedroom count and square footage.
  3. 3Calculate and visualize the weighted average price per neighborhood.

Use Automatio to extract data from Apartments.com and build these applications without writing code.

What You Can Do With Apartments.com Data

  • Real-Time Market Indexing

    Create a dashboard that tracks average rent prices across the US to assist economic forecasting.

    1. Scrape listings for the top 100 US cities daily.
    2. Categorize data by bedroom count and square footage.
    3. Calculate and visualize the weighted average price per neighborhood.
  • Undervalued Property Discovery

    Identify rental units priced below the neighborhood average to find high-yield investment opportunities.

    1. Extract all active listings in a specific target zip code.
    2. Calculate the average price-per-square-foot for the area.
    3. Filter for properties listed at 15% or more below that average.
  • Competitor Amenity Analysis

    Help property managers decide which renovations to prioritize by seeing what competitors offer.

    1. Scrape the 'Amenities' list for all buildings within a 2-mile radius.
    2. Identify the most common high-end features (e.g., rooftop pools, EV charging).
    3. Report on the price premium associated with specific amenities.
  • Automated Lead Sourcing

    Provide maintenance or renovation companies with a list of properties likely in need of service.

    1. Filter and scrape properties with older construction or renovation dates.
    2. Extract the property manager's contact name and phone number.
    3. Import the leads directly into a CRM for sales outreach.
  • Dynamic Rent Optimization

    Adjust building rents automatically based on real-time competitor vacancy and pricing.

    1. Set up a scheduled scrape for specific local competing properties.
    2. Detect when a competitor changes their pricing or offering 'specials'.
    3. Trigger an alert or API update to adjust your own listing prices accordingly.
More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents
Web Automation
Smart Workflows

Pro Tips for Scraping Apartments.com

Expert advice for successfully extracting data from Apartments.com.

Use high-quality residential proxies to avoid Akamai's IP reputation blocking.

Implement a 'stealth' plugin for Playwright or Puppeteer to mask browser fingerprints.

Schedule scraping tasks during US off-peak hours (1 AM - 5 AM EST) to minimize detection risk.

Always include a realistic Referer header like 'https://www.google.com/' in your requests.

Monitor the site's DOM structure weekly, as Apartments.com frequently updates its class names.

Extract data from the detailed property pages rather than just search results for more accurate contact info.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Related Web Scraping

Frequently Asked Questions About Apartments.com

Find answers to common questions about Apartments.com