Address Distance Calculation Scraper

This tool calculates distances between addresses or coordinates based on input addresses or location points. It’s useful for applications requiring geolocation computations, distance-based filtering, or route planning. By automating distance calculations, it helps developers, analysts, and businesses manage location-based workflows more efficiently.

     

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Introduction

The Address Distance Calculation Scraper accepts address pairs (or locations) and returns calculated distances between them. It’s ideal for use cases like logistics planning, customer-to-warehouse matching, real-estate filtering, or any workflow that requires understanding distances between geolocations.

What It Helps You Do

• Compute distances between two or more addresses automatically.
• Handle bulk address lists for batch distance calculations.
• Integrate distance output into data pipelines, reports, or filtering logic.
• Simplify geolocation-based logic for applications like delivery, mapping, or proximity analysis.

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Features

Feature	Description
Bulk Distance Calculation	Process many address pairs in a single run.
Flexible Input	Accepts addresses or coordinates for distance computation.
Built-in Geolocation Logic	Uses appropriate geocoding or coordinate maths to derive distances.
Structured Output	Returns results in JSON (or other exportable formats) ready for further processing.
Easy Integration	Suitable for logistics, mapping tools, real-estate filters, or analytics dashboards.

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What Data This Scraper Returns

Field Name	Field Description
origin	Origin address or coordinates.
destination	Destination address or coordinates.
distanceKm	Distance in kilometers between origin and destination.
distanceMiles	Distance in miles (optional).
travelTimeEstimate	Estimated travel time (if applicable / implemented).
status	Success or error indicator for the calculation.

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Example Output

[
  {
    "origin": "1600 Amphitheatre Parkway, Mountain View, CA",
    "destination": "1 Infinite Loop, Cupertino, CA",
    "distanceKm": 14.2,
    "distanceMiles": 8.8,
    "status": "success"
  }
]

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Directory Structure Tree

Address Distance Calculation Scraper/
├── src/
│   ├── main.js
│   ├── geocoder/
│   │   ├── address_normalizer.js
│   │   └── distance_calculator.js
│   ├── utils/
│   │   ├── logger.js
│   │   └── config_loader.js
│   └── config/
│       └── settings.example.json
├── data/
│   └── sample_output.json
├── package.json
└── README.md

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Use Cases

• Logistics & Delivery Services calculate delivery distances and optimize routing.
• Real-Estate Platforms filter properties based on proximity to a given location.
• E-commerce & Retail match customers to nearest warehouses or stores.
• Analytics Teams compute distance-based metrics for market segmentation.
• Mapping Tools & Apps integrate distance logic into location-based features.

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FAQs

What input formats are supported?
You can input plain addresses or geographic coordinates. The tool handles both.

Can it process many address pairs at once?
Yes — batch processing is supported for scalability.

What output format is provided?
JSON output is standard, suitable for integration into pipelines, dashboards, or further processing.

Does it include travel time estimates?
If supported by geolocation data and calculation logic, travel time estimates are optional.

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Performance Benchmarks and Results

Primary Metric:
Processes hundreds of address pairs per second depending on input size and geocoding latency.

Reliability Metric:
High success rate for valid addresses — ≤95% success under ideal input conditions.

Efficiency Metric:
Low overhead distance calculations using coordinate math or geolocation APIs.

Quality Metric:
Consistent output with accurate distance values and proper status reporting for failures.

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