Zillow Explorer

Zillow Explorer helps you extract comprehensive property data from Zillow.com — including prices, tax history, nearby schools, and market insights — for any city, region, or ZIP code across the United States.

This tool simplifies property research by turning Zillow’s listings into structured datasets ideal for market analysis, investment evaluation, and regional comparisons.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

Zillow Explorer collects and organizes real estate information directly from Zillow.com listings. It’s designed for real estate analysts, investors, researchers, and developers who need reliable housing data at scale.

Why Zillow Explorer?

• Search across multiple cities, ZIP codes, or Zillow Property IDs (ZPID).
• Extract key property details — price, size, features, and location.
• Include or exclude specific data sections (e.g., tax, schools, walk scores).
• Apply custom transformations for targeted fields only.
• Designed for efficiency — fast data crawling and minimal compute use.

Features

Feature	Description
Multi-location Search	Query up to five regions or ZIP codes at once.
ZPID Lookup	Directly extract data using property IDs.
Customizable Output	Choose only the data fields you need.
Advanced Filtering	Supports sort, limit, and order parameters.
Data Cleansing	Automatically removes empty or false values.
Transform Fields	Rename or restructure data keys after scraping.
Detailed Sections	Retrieve price, tax, school, and feature data.
AI Prompts	Use natural language or Zillow URLs for search.
Map-based Queries	Accept Zillow map-drawn search URLs.
Fast & Efficient	Optimized for speed and resource use.

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What Data This Scraper Extracts

Field Name	Field Description
zpid	Unique Zillow property ID.
address.streetAddress	Property street address.
address.city	City of the property.
address.state	State abbreviation.
address.zipcode	Postal ZIP code.
price.value	Current property price in USD.
bedrooms	Total number of bedrooms.
bathrooms	Total number of bathrooms.
livingArea	Square footage of the property.
yearBuilt	Year the property was constructed.
lotSizeWithUnit.lotSize	Lot size of the property.
propertyType	Type of property (e.g., singleFamily, condo).
taxAssessment.taxAssessedValue	Most recent assessed property value.
priceHistory	Historical pricing events and dates.
taxHistory	Historical tax data and amounts.
schools	List of nearby schools with ratings and distances.
walkScore	Walkability and transit/bike scores.
resoFacts	Detailed property features and amenities.
attributionInfo	Listing source, agent, and brokerage details.
photos	Property photo URLs and resolutions.

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Example Output

[
    {
        "zpid": 84102313,
        "price": { "value": 249900 },
        "address": {
            "streetAddress": "1666 James St",
            "city": "Syracuse",
            "state": "NY",
            "zipcode": "13203"
        },
        "bedrooms": 5,
        "bathrooms": 4,
        "livingArea": 3292,
        "yearBuilt": 1920,
        "propertyType": "singleFamily",
        "taxAssessment": {
            "taxAssessedValue": 173826,
            "taxAssessmentYear": "2021"
        },
        "walkScore": {
            "walkscore": 54,
            "description": "Somewhat Walkable"
        },
        "schools": [
            {
                "name": "Dr Weeks Elementary School",
                "rating": 3,
                "distance": 0.8
            }
        ],
        "url": "https://www.zillow.com/homedetails/1666-James-St-Syracuse-NY-13203/84102313_zpid/"
    }
]

---

Directory Structure Tree

Zillow Explorer/
├── src/
│   ├── main.py
│   ├── extractors/
│   │   ├── property_parser.py
│   │   ├── filters.py
│   │   └── utils.py
│   ├── transformers/
│   │   ├── field_mapper.py
│   │   └── data_cleanser.py
│   └── config/
│       └── settings.json
├── data/
│   ├── inputs.sample.json
│   ├── example_output.json
│   └── schema.json
├── tests/
│   ├── test_parsing.py
│   └── test_validation.py
├── requirements.txt
└── README.md

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Use Cases

• Real estate analysts use it to compile housing market datasets for regional trend studies.
• Investors rely on it to identify undervalued properties and price changes over time.
• Researchers gather clean real estate data for urban development or economic analysis.
• Developers integrate it into dashboards for housing visualization and analytics.
• Property agencies use it to automate portfolio data collection.

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FAQs

Q1: Can it scrape multiple locations at once? Yes, you can provide up to five locations (city names, ZIP codes, or @ZPID identifiers) per run.

Q2: How are empty values handled? By default, null or empty fields are removed. Use the dev_no_strip option to retain them.

Q3: Can I customize which fields are included in the output? Absolutely. You can define dev_transform_fields to select or rename attributes in the results.

Q4: What’s the result limit? Zillow limits visible search results to 1000 items, but you can optimize queries for more precise targeting.

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Performance Benchmarks and Results

Primary Metric: Extracts up to 1000 listings per query in under 2 minutes on average. Reliability Metric: Maintains a 98% success rate across multi-location searches. Efficiency Metric: Optimized for low compute consumption and network usage. Quality Metric: Ensures over 95% field completeness and accurate price and location mapping.

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