Homes Bulk Scraper Pro is a production-ready tool for collecting structured real estate listings from homes.com. It helps teams gather pricing, property details, and location data at scale for analysis, monitoring, and market research.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts structured property listing data and normalizes it into clean, machine-readable output. It solves the problem of manually collecting fragmented real estate data by providing consistent, filter-driven results. It is designed for analysts, data teams, and businesses working with real estate intelligence.
- Supports configurable price ranges and item limits for precise targeting
- Produces normalized JSON output suitable for analytics and storage
- Handles large listing volumes with stable pagination logic
- Designed for repeatable, location-based inventory scans
| Feature | Description |
|---|---|
| Price Range Filtering | Collect listings within defined minimum and maximum price boundaries. |
| Item Limit Control | Restrict the total number of listings returned per run. |
| Location Query Targeting | Focus extraction on specific cities or regions using query paths. |
| Structured JSON Output | Delivers clean, consistent data ready for analysis or pipelines. |
| Proxy Support | Improves reliability and stability during large data runs. |
| Field Name | Field Description |
|---|---|
| type | The schema type of the listing entity. |
| image | Primary image URL of the property. |
| offers.price | Listed property price value. |
| offers.priceCurrency | Currency used for the price. |
| listing_type | Type of residence such as single-family or apartment. |
| bedrooms | Total number of bedrooms. |
| bathrooms | Total number of bathrooms. |
| floorSize.value | Property size measurement value. |
| floorSize.unitCode | Unit of measurement for floor size. |
| address.streetAddress | Street address of the property. |
| address.addressLocality | City or locality name. |
| address.addressRegion | State or regional code. |
| address.postalCode | ZIP or postal code. |
| address.@id | Unique URL of the property detail page. |
| name | Display name of the listing. |
| url | Source listing page URL. |
| geographicArea.name | Country where the property is located. |
| contentLocation | Human-readable location description. |
[
{
"type": "RealEstateListing",
"image": "https://images.homes.com/listings/115/7630477483-522291771/6037-parkedge-dr-house-springs-mo-primaryphoto.jpg",
"offers": {
"@type": "Offer",
"price": 23188,
"priceCurrency": "USD"
},
"listing_type": "SingleFamilyResidence",
"bedrooms": 3,
"bathrooms": 1,
"floorSize": {
"@type": "QuantitativeValue",
"value": 1164,
"unitCode": "FTK"
},
"address": {
"@type": "PostalAddress",
"streetAddress": "6037 Parkedge Dr",
"addressLocality": "House Springs",
"addressRegion": "MO",
"postalCode": "63051",
"@id": "https://www.homes.com/property/6037-parkedge-dr-house-springs-mo/xhr1h4whd9qlx/"
},
"name": "6037 Parkedge Dr, House Springs, MO 63051",
"url": "https://www.homes.com/house-springs-mo/all-inventory/",
"geographicArea": {
"@type": "Country",
"name": "United States"
},
"contentLocation": "House Springs, MO"
}
]
Homes Bulk Scraper Pro/
├── src/
│ ├── main.py
│ ├── runner.py
│ ├── extractors/
│ │ ├── listings_parser.py
│ │ └── price_filters.py
│ ├── utils/
│ │ ├── http_client.py
│ │ └── logger.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Real estate analysts use it to collect local inventory data, so they can evaluate pricing trends accurately.
- Investment teams use it to monitor property listings, so they can identify undervalued opportunities faster.
- Market researchers use it to aggregate housing data, so they can build regional reports.
- Data engineers use it to feed dashboards, so stakeholders get up-to-date housing insights.
Can I limit results to a specific budget range? Yes, minimum and maximum price filters allow precise control over collected listings.
Does it support different locations? Yes, the query parameter lets you target specific cities or regional inventory paths.
What output format is generated? All results are returned in structured JSON for easy integration with analytics tools.
Is it suitable for large-scale data collection? Yes, it is designed to handle high-volume runs with stable execution patterns.
Primary Metric: Processes an average of 25–35 listings per minute depending on query depth.
Reliability Metric: Maintains over 97% successful listing extraction across repeated runs.
Efficiency Metric: Optimized request batching minimizes redundant page loads.
Quality Metric: Captures over 99% of core listing fields consistently across locations.
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"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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