Land.com Scraper

Land.com Scraper helps you collect structured property listing data from Land.com at scale. It solves the problem of manually browsing listings by turning raw pages into clean, usable datasets. Ideal for analysts, investors, and developers who need reliable land and property data fast.

     

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

This project extracts detailed property listings from Land.com based on configurable inputs like zip codes and listing type. It removes the friction of manual data collection and delivers consistent, structured output. Built for developers, real estate professionals, and data teams who need dependable property intelligence.

How it fits into your workflow

• Targets listings by zip code for precise geographic coverage
• Supports multiple listing states such as for sale, for rent, and sold
• Collects both pricing and descriptive property metadata
• Designed to scale without manual pagination handling

Features

Feature	Description
Zip-based scraping	Collect listings by one or multiple zip codes.
Multiple listing types	Supports for sale, for rent, and sold properties.
Rich property details	Extracts titles, prices, acreage, images, and descriptions.
Broker information	Captures broker names, companies, and profile URLs.
Pagination handling	Automatically retrieves all available listings.
Resilient requests	Retries failed requests to ensure stable data collection.

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What Data This Scraper Extracts

Field Name	Field Description
title	Title of the property listing.
price	Listed price of the property.
pricePerAcre	Cost per acre when available.
acres	Total land size in acres.
address	Street address of the property.
city	City where the property is located.
state	State where the property is located.
zip	ZIP code of the listing.
description	Full textual description of the property.
brokerName	Name of the listing broker or agent.
brokerCompany	Broker or agency representing the listing.
canonicalUrl	Direct URL to the property listing.
image	Primary image URL for the property.
latitude	Geographic latitude of the property.
longitude	Geographic longitude of the property.

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Example Output

[
    {
        "title": "Secluded Estate With Two Custom Homes, Pasture, Timber, Wildlife",
        "price": 1499900,
        "pricePerAcre": 17085.09,
        "acres": 87.79,
        "address": "5827 & 5837 Pridmore Rd, Lot#WP001",
        "city": "Jacksonville",
        "state": "Arkansas",
        "zip": "72076",
        "brokerCompany": "Whitetail Properties Real Estate",
        "brokerName": "Jeff Hodge",
        "canonicalUrl": "https://www.land.com/property/...",
        "image": "https://assets.land.com/resizedimages/600/0/h/80/w/1-5494834051"
    }
]

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Directory Structure Tree

Land.com Scraper/
├── src/
│   ├── main.py
│   ├── scraper/
│   │   ├── listings_scraper.py
│   │   └── pagination.py
│   ├── parsers/
│   │   └── property_parser.py
│   ├── utils/
│   │   ├── request_handler.py
│   │   └── retry.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Real estate investors use it to analyze land prices, so they can identify undervalued properties faster.
• Data analysts use it to build regional market datasets, so they can track pricing trends over time.
• Developers use it to feed property data into apps, so they can power search and comparison features.
• Agencies use it to monitor competitor listings, so they can adjust pricing strategies confidently.

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FAQs

What inputs are required to run the scraper? You only need a list of zip codes. Optional parameters allow you to filter by listing type and customize request behavior.

Which listing types are supported? The scraper supports properties that are for sale, for rent, and sold, giving you flexibility across use cases.

Does it handle large result sets? Yes, pagination is handled automatically, allowing full extraction of all available listings for the selected area.

Is proxy support available? The scraper is designed to work with rotating proxies to improve reliability and reduce request failures.

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Performance Benchmarks and Results

Primary Metric: Processes hundreds of listings per zip code with consistent response times.

Reliability Metric: Maintains a high success rate through automatic retries on transient failures.

Efficiency Metric: Optimized request flow minimizes redundant calls and reduces overall runtime.

Quality Metric: Extracted datasets consistently include complete pricing, location, and broker details.

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"Exceptional results, clear communication, and flawless delivery. Bitbash nailed it." Syed Digital Strategist ★★★★★