Rent Scraper is a focused data extraction tool that collects detailed apartment and rental property listings from Rent.com. It helps developers, analysts, and property professionals gather structured rental data quickly, reliably, and at scale, without manual browsing.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts structured rental listing data from property pages, turning unstructured listing pages into clean, usable datasets. It solves the problem of manually collecting rental details across listings and is built for anyone who needs reliable rental market data.
- Designed to handle individual property pages and bulk listing URLs
- Captures pricing, location, amenities, and nearby context in one pass
- Outputs clean, structured JSON ready for analysis or storage
- Scales efficiently for market research and aggregation workflows
| Feature | Description |
|---|---|
| Listing data extraction | Collects detailed apartment and property listing information. |
| Pricing normalization | Captures rent ranges in a consistent, readable format. |
| Location parsing | Extracts full address, city, state, and ZIP code cleanly. |
| Media collection | Gathers property image URLs for downstream usage. |
| Amenities mapping | Outputs structured amenity lists for easy comparison. |
| School proximity data | Includes nearby school details and ratings when available. |
| Field Name | Field Description |
|---|---|
| title | Name of the property or apartment complex. |
| property_type | Category such as apartments or condos. |
| price | Monthly rent or rent range. |
| bedrooms | Number of bedrooms available. |
| bathrooms | Number of bathrooms available. |
| square_footage | Size range of the unit in square feet. |
| street_address | Street-level address of the property. |
| city | City where the property is located. |
| state | State where the property is located. |
| zip_code | ZIP or postal code. |
| neighborhood | Neighborhood or area name if provided. |
| image_urls | List of property image links. |
| amenities | List of available apartment amenities. |
| nearby_schools | Schools close to the property with ratings and distance. |
| description | Full property description text. |
| walkscore | Walkability score if available. |
[
{
"title": "Charleston at Fannin Station",
"property_type": "APARTMENTS",
"price": "$1,335 - $1,400/mo",
"bedrooms": 1,
"bathrooms": 1,
"square_footage": "555 - 555",
"street_address": "9779 Fannin Railway",
"city": "Houston",
"state": "Texas",
"zip_code": "77045",
"amenities": [
"Washer & Dryer In Unit",
"Air Conditioning",
"Dishwasher",
"Swimming Pool",
"Fitness Center"
]
}
]
Rent Scraper/
├── src/
│ ├── index.js
│ ├── scraper/
│ │ ├── listingParser.js
│ │ └── pageFetcher.js
│ ├── utils/
│ │ ├── addressUtils.js
│ │ └── normalizePrice.js
│ └── config/
│ └── default.config.json
├── data/
│ ├── input.sample.json
│ └── output.sample.json
├── package.json
└── README.md
- Real estate analysts use it to gather rental pricing data, so they can track market trends accurately.
- Property platforms use it to populate listings automatically, reducing manual data entry.
- Researchers use it to study housing availability, enabling better regional insights.
- Developers use it to integrate rental data into dashboards and applications quickly.
- Investors use it to compare amenities and pricing across neighborhoods.
Does this support scraping multiple listings at once? Yes, the scraper is designed to handle single URLs as well as multiple property listing pages in one run.
What happens if a field is missing on a listing? Missing fields are returned as null, keeping the output schema consistent and predictable.
Is the output format customizable? The core output is JSON-based, making it easy to transform into CSV, databases, or APIs as needed.
How reliable is the extracted data? The scraper prioritizes structured selectors and validation to ensure high data accuracy.
Primary Metric: Processes individual property pages in under 2 seconds on average.
Reliability Metric: Maintains over a 98 percent successful extraction rate across tested listings.
Efficiency Metric: Handles hundreds of listings per hour with stable memory usage.
Quality Metric: Delivers consistently complete datasets with minimal missing fields.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"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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