How to Scrape LivePiazza: Philadelphia Real Estate Scraper

Learn how to scrape LivePiazza.com to extract luxury apartment prices, availability, and floor plans. Monitor the Philadelphia real estate market with AI.

Coverage:United StatesPennsylvaniaPhiladelphiaNorthern Liberties
Available Data9 fields
TitlePriceLocationDescriptionImagesContact InfoPosting DateCategoriesAttributes
All Extractable Fields
Building Name (e.g., Alta, Navona)Unit NumberMonthly RentSquare FootageFloor Plan NameNumber of Bedrooms/BathroomsAvailability DateInterior Finish Style (Sleek/Scandinavian)Current Promotional OffersApartment AmenitiesBuilding AmenitiesProperty AddressFloor Plan Image URLsLeasing Office Phone Number
Technical Requirements
JavaScript Required
No Login
Has Pagination
No Official API
Anti-Bot Protection Detected
CloudflareRate LimitingBrowser FingerprintingJavaScript Challenges

Anti-Bot Protection Detected

Cloudflare
Enterprise-grade WAF and bot management. Uses JavaScript challenges, CAPTCHAs, and behavioral analysis. Requires browser automation with stealth settings.
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.
JavaScript Challenge
Requires executing JavaScript to access content. Simple requests fail; need headless browser like Playwright or Puppeteer.

About The Piazza

Learn what The Piazza offers and what valuable data can be extracted from it.

The Piazza, managed by Post Brothers, is a prominent residential and retail development in the Northern Liberties neighborhood of Philadelphia. It features four distinct luxury communities—Alta, Navona, Montesino, and Liberties Walk—offering a 'city-within-a-city' experience with high-end amenities and modern design.

The website functions as a real-time portal for prospective residents, displaying current rental rates, specific unit availability dates, and detailed interior finish options. For data scientists and real estate analysts, LivePiazza represents a critical data source for understanding the luxury multi-family market in one of the fastest-growing urban corridors in the Northeast.

Scraping this data allows for high-frequency monitoring of pricing trends, occupancy levels, and the effectiveness of various rental incentives offered by large-scale property developers.

About The Piazza

Why Scrape The Piazza?

Discover the business value and use cases for extracting data from The Piazza.

Monitor real-time rental pricing fluctuations in the Philadelphia luxury market.

Track occupancy rates and unit turnover across different building communities.

Analyze the impact of rental concessions like '2 months free' on net effective rent.

Gather high-resolution floor plan data for architectural and interior design research.

Automate lead generation for local services like moving companies and furniture retailers.

Perform competitive benchmarking against other luxury developments in the region.

Scraping Challenges

Technical challenges you may encounter when scraping The Piazza.

Cloudflare's 'Waiting Room' and 'Just a moment' verification screens block simple bot requests.

Heavy reliance on client-side JavaScript rendering for unit availability tables.

Internal API endpoints use dynamic tokens that expire quickly.

Frequent DOM structure updates that can break static CSS selectors.

Scrape The Piazza 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 The Piazza. Just type it in plain language — no coding or selectors needed.

2

AI Extracts the Data

Our artificial intelligence navigates The Piazza, 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

Automatically solves Cloudflare challenges without manual proxy configuration.
Renders dynamic JavaScript content exactly as a human browser would.
Allows for visual selection of data points across complex floor plan maps.
Supports scheduled runs to capture daily pricing changes and historical trends.
Exports data directly to Google Sheets or via Webhook for immediate analysis.
No credit card requiredFree tier availableNo setup needed

AI makes it easy to scrape The Piazza 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 The Piazza. Just type it in plain language — no coding or selectors needed.
  2. AI Extracts the Data: Our artificial intelligence navigates The Piazza, 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:
  • Automatically solves Cloudflare challenges without manual proxy configuration.
  • Renders dynamic JavaScript content exactly as a human browser would.
  • Allows for visual selection of data points across complex floor plan maps.
  • Supports scheduled runs to capture daily pricing changes and historical trends.
  • Exports data directly to Google Sheets or via Webhook for immediate analysis.

No-Code Web Scrapers for The Piazza

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape The Piazza. 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 The Piazza

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape The Piazza. 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

# Note: This direct request will likely fail due to Cloudflare
# A proxy or bypass solution like cloudscraper is recommended
url = 'https://www.livepiazza.com/residences'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9'
}

def fetch_piazza():
    try:
        response = requests.get(url, headers=headers, timeout=10)
        if response.status_code == 200:
            soup = BeautifulSoup(response.text, 'html.parser')
            # Example selector for residence cards
            for card in soup.select('.residence-card'):
                name = card.select_one('.residence-name').text.strip()
                price = card.select_one('.price-value').text.strip()
                print(f'Community: {name} | Price: {price}')
        else:
            print(f'Blocked by Anti-Bot: Status {response.status_code}')
    except Exception as e:
        print(f'Error: {e}')

fetch_piazza()

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 The Piazza with Code

Python + Requests
import requests
from bs4 import BeautifulSoup

# Note: This direct request will likely fail due to Cloudflare
# A proxy or bypass solution like cloudscraper is recommended
url = 'https://www.livepiazza.com/residences'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9'
}

def fetch_piazza():
    try:
        response = requests.get(url, headers=headers, timeout=10)
        if response.status_code == 200:
            soup = BeautifulSoup(response.text, 'html.parser')
            # Example selector for residence cards
            for card in soup.select('.residence-card'):
                name = card.select_one('.residence-name').text.strip()
                price = card.select_one('.price-value').text.strip()
                print(f'Community: {name} | Price: {price}')
        else:
            print(f'Blocked by Anti-Bot: Status {response.status_code}')
    except Exception as e:
        print(f'Error: {e}')

fetch_piazza()
Python + Playwright
import asyncio
from playwright.async_api import async_playwright

async def scrape_live_piazza():
    async with async_playwright() as p:
        # Launching with a specific user agent to mimic a real browser
        browser = await p.chromium.launch(headless=True)
        context = await browser.new_context(user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36')
        page = await context.new_page()
        
        await page.goto('https://www.livepiazza.com/alta/')
        
        # Wait for the dynamic unit table to load
        await page.wait_for_selector('.unit-row', timeout=15000)
        
        units = await page.query_selector_all('.unit-row')
        for unit in units:
            unit_id = await (await unit.query_selector('.unit-id')).inner_text()
            rent = await (await unit.query_selector('.unit-rent')).inner_text()
            print(f'Unit: {unit_id.strip()} | Rent: {rent.strip()}')
        
        await browser.close()

asyncio.run(scrape_live_piazza())
Python + Scrapy
import scrapy

class PiazzaSpider(scrapy.Spider):
    name = 'piazza_spider'
    start_urls = ['https://www.livepiazza.com/communities']

    def parse(self, response):
        # Scrapy requires a JS-rendering middleware (like Scrapy-Playwright) for this site
        for building in response.css('.building-section'):
            yield {
                'building_name': building.css('h3.name::text').get(),
                'link': building.css('a.explore-btn::attr(href)').get(),
                'starting_price': building.css('.starting-from::text').get()
            }
        
        # Example of pagination following
        next_page = response.css('a.next-page::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)
Node.js + Puppeteer
const puppeteer = require('puppeteer-extra');
const StealthPlugin = require('puppeteer-extra-plugin-stealth');
puppeteer.use(StealthPlugin());

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  
  await page.goto('https://www.livepiazza.com/montesino', { waitUntil: 'networkidle2' });

  // Wait for the residences container to render
  await page.waitForSelector('.residences-container');

  const apartmentData = await page.evaluate(() => {
    const rows = Array.from(document.querySelectorAll('.apartment-listing'));
    return rows.map(row => ({
      type: row.querySelector('.plan-type').innerText,
      sqft: row.querySelector('.sqft').innerText,
      available: row.querySelector('.availability').innerText
    }));
  });

  console.log(apartmentData);
  await browser.close();
})();

What You Can Do With The Piazza Data

Explore practical applications and insights from The Piazza data.

Real-Time Rent Index

Create a live dashboard tracking the average rent per square foot for luxury apartments in Northern Liberties.

How to implement:

  1. 1Extract daily pricing for all studio, 1BR, and 2BR units.
  2. 2Normalize pricing by square footage to create a PPSF metric.
  3. 3Visualize the trend line over a 90-day period.

Use Automatio to extract data from The Piazza and build these applications without writing code.

What You Can Do With The Piazza Data

  • Real-Time Rent Index

    Create a live dashboard tracking the average rent per square foot for luxury apartments in Northern Liberties.

    1. Extract daily pricing for all studio, 1BR, and 2BR units.
    2. Normalize pricing by square footage to create a PPSF metric.
    3. Visualize the trend line over a 90-day period.
  • Concession Strategy Analysis

    Analyze how property managers use 'Free Rent' incentives to fill vacancies in specific buildings.

    1. Scrape the 'Promotions' field for every listed unit.
    2. Cross-reference promotions with the number of days a unit has been listed.
    3. Determine the 'tipping point' where developers increase incentives.
  • Investment Feasibility Studies

    Use the data to justify or reject new luxury developments in the immediate area based on current supply and demand.

    1. Aggregate the total number of available units across Alta, Navona, and Montesino.
    2. Segment availability by 'move-in date' to forecast supply absorption.
    3. Compare Piazza pricing against city-wide luxury averages.
  • Lead Gen for Movers

    Identify high-volume move-in windows to target marketing for local moving and cleaning services.

    1. Filter scraped listings for 'Available Now' or specific upcoming dates.
    2. Target buildings with the highest upcoming availability.
    3. Align advertising spend with the highest predicted turnover periods.
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Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

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Pro Tips for Scraping The Piazza

Expert advice for successfully extracting data from The Piazza.

Use residential proxies based in Philadelphia to reduce suspicion from Cloudflare security filters.

Focus your scraping on early morning hours (ET) when the property management updates unit availability.

Check the 'Network' tab in your browser to identify XHR/Fetch requests that return JSON data for the unit tables.

Rotate User-Agents frequently to avoid fingerprint-based rate limiting.

Calculate the 'Net Effective Rent' by parsing the text of promotional offers (e.g., '1 month free on 13-month lease').

Implement a 'wait for' logic in your scraper to ensure the interactive floor plans are fully rendered before extraction.

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.

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Frequently Asked Questions About The Piazza

Find answers to common questions about The Piazza