Trulia Scraper

A dedicated Trulia scraper that crawls real estate listings, normalizes property details, and exports them as clean, structured data ready for your analytics pipelines or dashboards. It helps you track listings across cities, neighborhoods, ZIP codes, and counties without manual copy-paste work. Ideal for investors, analysts, and proptech teams who need reliable Trulia real estate data at scale.

     

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Introduction

The Trulia Scraper automates the process of collecting property information from Trulia’s real estate listings pages. Instead of manually browsing and saving details, it lets you define search locations and search types, then automatically fetches structured data for every home that matches your criteria.

It is designed for:

• Real estate investors comparing listings across multiple markets.
• Data analysts building pricing, inventory, or market trend models.
• Agencies and proptech tools that need a continuous feed of fresh property data.

Real Estate Data Collection at Scale

• Supports multiple search locations such as cities, neighborhoods, ZIP codes, and counties in a single run.
• Handles multiple search intents (Buy, Rent, Sold) so you can analyze active and historical listings together.
• Accepts both direct property URLs and high-level search locations for flexible workflows.
• Lets you sort results (for example by newest listings) to prioritize the most relevant properties.
• Produces machine-readable JSON output that can be loaded into databases, BI tools, or spreadsheets.

Features

Feature	Description
Multiple property URLs	Start from one or more direct listing URLs to enrich or verify specific properties.
Multiple search locations	Query by city, neighborhood, ZIP code, or county in a single configuration.
Multiple search types	Toggle Buy, Rent, and Sold modes to capture the exact stage of the property lifecycle you care about.
Sort homes	Control sorting (e.g., NEW_LISTINGS) to focus on the freshest or most relevant results.
Flexible input	Combine startUrls with searchLocations to cover both targeted and broad-area scans.
Efficient resource usage	Optimized to process thousands of homes per run while keeping memory and CPU usage predictable.
Proxy-friendly design	Built to work with residential or rotating proxies to reduce the risk of blocking and captchas.
Structured JSON output	Delivers normalized property records ready for storage, analysis, or integration with external systems.

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What Data This Scraper Extracts

Field Name	Field Description
url	Canonical URL of the property listing.
searchLocation	Human-readable description of the location used in the search (e.g., Fremont, CA).
query	Raw query string or location text used to retrieve this result.
title	Full page title including address, property summary, and key listing attributes.
metaDescription	Meta description snippet summarizing the property, beds, baths, size, and a short narrative.
isOffMarket	Boolean flag indicating whether the listing is currently off the market.
isRecentlySold	Boolean flag that marks recently sold properties.
isForeclosure	Boolean flag showing if the property is in foreclosure.
isActiveForRent	Boolean flag showing if the property is currently available for rent.
isActiveForSale	Boolean flag showing if the property is currently listed for sale.
isRecentlyRented	Boolean flag that marks recently rented properties.
location.stateCode	Two-letter state code for the property location.
location.jsonLdSchemaFullLocation	Full location string as used in structured schema data.
location.homeFormattedAddress	Full formatted street address of the home.
location.cityStateZipAddress	Combined city, state, and ZIP code in a single string.
location.summaryFormattedLocation	Shortened display address (usually street or community).
location.city	City name of the property.
location.zipCode	ZIP code where the property is located.
location.neighborhoodName	Neighborhood name or community label.
location.streetAddress	Street address without city, state, or ZIP code.
location.formattedLocation	Display-ready location string, often matching the street or neighborhood label.
location.latitude	Latitude coordinate of the property.
location.longitude	Longitude coordinate of the property.
price	Listing price or last known price of the property, in numeric form.
bedrooms	Number of bedrooms in the property.
bathrooms	Number of bathrooms in the property.
floorSpace	Interior floor area of the home in square feet.
propertyType	Type of property (e.g., Single Family Home, Condo, Townhouse).
lotSize	Lot size as a human-readable string (e.g., 0.58 acres).

---

Example Output

[
    {
        "url": "https://www.trulia.com/p/ca/fremont/48871-crown-ridge-cmn-fremont-ca-94539--2083417606",
        "searchLocation": "Fremont, CA",
        "query": "Fremont, CA",
        "title": "48871 Crown Ridge Cmn, Fremont, CA 94539 - 5 Bed, 4 Bath Single-Family Home - MLS# ML81834752 - 39 Photos | Trulia",
        "metaDescription": "48871 Crown Ridge Cmn, Fremont, CA 94539 is a 3,811 sqft, 5 bed, 4 bath Single-Family Home listed for $2,980,000. Welcome to 48871 Crown Ridge Common, an exquisite home located on a tree lined street in the prestigious...",
        "isOffMarket": false,
        "isRecentlySold": false,
        "isForeclosure": false,
        "isActiveForRent": false,
        "isActiveForSale": true,
        "isRecentlyRented": false,
        "location": {
            "stateCode": "CA",
            "jsonLdSchemaFullLocation": "48871 Crown Ridge Cmn, Fremont, CA 94539",
            "homeFormattedAddress": "48871 Crown Ridge Cmn, Fremont, CA 94539",
            "cityStateZipAddress": "Fremont, CA 94539",
            "summaryFormattedLocation": "48871 Crown Ridge Cmn",
            "city": "Fremont",
            "zipCode": "94539",
            "neighborhoodName": "Vineyards-Avalon",
            "streetAddress": "48871 Crown Ridge Cmn",
            "formattedLocation": "48871 Crown Ridge Cmn",
            "latitude": 37.47203826904297,
            "longitude": -121.8926010131836
        },
        "price": 2980000,
        "bedrooms": 5,
        "bathrooms": 4,
        "floorSpace": 3811,
        "propertyType": "Single Family Home",
        "lotSize": "0.58 acres"
    }
]

---

Directory Structure Tree

trulia-scraper (IMPORTANT: always keep this name as the name of the Trulia Scraper)/
├── src/
│   ├── main.js
│   ├── truliaClient.js
│   ├── crawler/
│   │   ├── requestQueue.js
│   │   ├── listingCrawler.js
│   │   └── paginationHandler.js
│   ├── parsers/
│   │   ├── listingParser.js
│   │   └── locationNormalizer.js
│   ├── outputs/
│   │   ├── datasetWriter.js
│   │   └── exportToCsv.js
│   └── config/
│       ├── inputSchema.json
│       └── settings.example.json
├── data/
│   ├── inputs.sample.json
│   └── sample-output.json
├── tests/
│   ├── listingParser.test.js
│   └── locationNormalizer.test.js
├── scripts/
│   ├── run-local.sh
│   └── validate-input.js
├── package.json
├── scraper.config.json
├── .env.example
└── README.md

---

Use Cases

• Real estate investors use it to collect comparable properties across multiple cities, so they can quickly evaluate deals and estimate fair market value.
• Data analysts use it to build time-series datasets of list prices and inventory, so they can track market trends and price movements over months or years.
• Proptech startups use it to feed their internal APIs and recommendation engines with fresh listing data, so they can deliver more accurate search and discovery experiences to end users.
• Market researchers use it to monitor neighborhood-level supply, prices, and property types, so they can produce data-backed reports and insights for clients or stakeholders.
• Lead generation teams use it to identify high-value properties in specific ZIP codes, so they can target outreach and marketing campaigns more effectively.

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FAQs

Q1: What is the minimal configuration I need to start scraping? You only need to provide either a list of startUrls (direct listing links) or a list of searchLocations (such as "San Francisco" or "Fremont, CA"). If you use searchLocations, make sure at least one of searchTypeBuy, searchTypeRent, or searchTypeSold is set to true so the scraper knows which type of listings to retrieve.

Q2: Can I run both Buy and Rent searches in a single run? Yes. You can set multiple search-type flags to true (for example, searchTypeBuy: true and searchTypeRent: true). For each search location, the scraper will fetch separate result sets for each selected search type, giving you a richer dataset covering different segments of the market.

Q3: How do I avoid being blocked while scraping Trulia? Use a reputable proxy pool with residential or rotating IPs and keep your maximum concurrency at a modest level. For most setups, a low concurrency (for example 2–5 parallel requests) is enough to maintain good throughput while minimizing the chances of triggering rate limits or captchas.

Q4: In what formats can I export the data? By default, the scraper works with structured JSON. You can then transform this output into CSV, Excel, or load it directly into a database. The outputs helpers in the project structure show how to pipe results into CSV exports or other downstream tools.

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Performance Benchmarks and Results

Primary Metric: On a typical 1 GB memory configuration, the Trulia Scraper is able to process roughly 4,000 home listings per hour under stable network conditions, including parsing and normalization.

Reliability Metric: With conservative concurrency settings and a healthy proxy pool, users can expect a successful retrieval rate above 95% for reachable listings, with automatic retries for transient network or parsing errors.

Efficiency Metric: CPU and memory usage are tuned so that a single node can handle thousands of listings per run without spikes, keeping average CPU utilization in a moderate range even during peak crawling phases.

Quality Metric: Field coverage for core attributes (price, beds, baths, address, coordinates, and property status flags) is generally above 98% completeness, ensuring that the resulting dataset is ready for analytics, dashboards, and automated decision-making with minimal post-processing.

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