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Nestoriaus Parser Spider

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Nestoriaus Parser Spider

Nestoriaus Parser Spider

The Nestoriaus Parser Spider is an Apify Actor that extracts and parses detailed property listings from Nestoria, including prices, locations, and descriptions. It features location-based targeting, high-speed performance, reliable data quality, and flexible JSON/CSV/Excel exports....

Pricing

from $9.00 / 1,000 results

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GetDataForMe

GetDataForMe

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Introduction

The Nestoriaus Parser Spider is a powerful Apify Actor designed to extract and parse property listings from the Nestoria real estate platform. It enables users to gather detailed property data, such as prices, locations, and descriptions, in a structured format for analysis or integration into other systems. This tool is ideal for real estate professionals, researchers, and businesses seeking automated data collection from Nestoria's extensive database.

Features

  • Comprehensive Property Extraction: Scrapes detailed information including property types, prices, locations, and descriptions from Nestoria listings.
  • Location-Based Targeting: Allows precise targeting of specific locations or regions for focused data retrieval.
  • High-Speed Performance: Optimized for fast and efficient scraping, minimizing runtime while handling large volumes of data.
  • Reliable Data Quality: Ensures accurate and consistent output with built-in error handling to avoid incomplete or corrupted data.
  • Flexible Output Formats: Supports JSON, CSV, and Excel exports for easy integration into workflows or analysis tools.
  • Scalable and Customizable: Easily configurable for different use cases, with options to expand for custom requirements.
  • User-Friendly Interface: Simple setup through Apify's platform, with clear logging and monitoring for seamless operation.

Input Parameters

ParameterTypeRequiredDescriptionExample
LocationstringNoThe specific location or region to target for property listings on Nestoria. This can be a city, neighborhood, or custom identifier."washington-arms"

Example Usage

To run the Nestoriaus Parser Spider, provide the input configuration in JSON format. Below is an example:

Example Input:

{
"Location": "washington-arms"
}

Example Output:

// No output available

Note: The output will contain structured property data in JSON format. If no listings are found, the output may be empty or indicate no results.

Use Cases

  • Market Research and Analysis: Gather data on property trends, prices, and availability in specific areas for informed decision-making.
  • Competitive Intelligence: Monitor competitor listings and pricing strategies on Nestoria to stay ahead in the real estate market.
  • Price Monitoring: Track property values over time to identify fluctuations and investment opportunities.
  • Content Aggregation: Collect and aggregate property information for websites, blogs, or databases focused on real estate.
  • Academic Research: Support studies on housing markets, urban development, or economic indicators using real data.
  • Business Automation: Integrate scraped data into CRM systems, dashboards, or automated reporting tools for streamlined operations.

Installation and Usage

  1. Search for "Nestoriaus Parser Spider" in the Apify Store
  2. Click "Try for free" or "Run"
  3. Configure input parameters
  4. Click "Start" to begin extraction
  5. Monitor progress in the log
  6. Export results in your preferred format (JSON, CSV, Excel)

Output Format

The output is provided in JSON format, containing an array of objects where each object represents a property listing. Key fields typically include:

  • title: The property title or headline.
  • price: The listed price.
  • location: The property's location details.
  • description: A summary or full description of the property.
  • url: A link to the original listing on Nestoria.

The structure ensures easy parsing and integration, with each listing as a separate object in the array. If no data is found, the output may be an empty array.

Support

For custom/simplified outputs or bug reports, please contact:

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