Lancaster County Tax Delinquency Scraper

Demo

Watch the scraper in action:

Automated scraping process demonstration

Overview

An automated Python script to extract delinquent tax information from Lancaster County, PA's public parcel viewer system. This scraper extracts delinquent tax data from the Lancaster County Property Tax portal:

https://lancasterpa.devnetwedge.com/parcel/view/{parcel_number}/{tax_year}

Example URL:

https://lancasterpa.devnetwedge.com/parcel/view/5408465600000/2025

Web Interface

Screenshot of the Lancaster County Parcel Viewer interface where data is extracted from

Sample Output

CSV Output Format

The script generates a structured CSV file containing delinquent tax information:

parcel_number,address,owner,scrape_date,tax_year,amount_due,amount_paid,total_due
5408465600000,123 MAIN ST LANCASTER PA,JOHN DOE,2024-03-20,2023,1500.00,0.00,1500.00
1200794700000,456 ELM ST LANCASTER PA,JANE SMITH,2024-03-20,2022,2000.00,500.00,1500.00

Project Structure

lancaster-property-tax-scraper/
├── src/
│   └── property_scraper.py  # Main scraper implementation
├── output/
│   └── delinquent_taxes.csv # Generated output file
├── img/                     # Documentation images
├── requirements.txt         # Python dependencies
└── README.md               # Documentation

How It Works

Overall Workflow

graph LR
    A["Input Parcel List"] --> B["Initialize Scraper"]
    B --> C["Process Each Parcel"]
    C --> D["Check for<br/>Delinquent Taxes"]
    D --> E{"Has Delinquent<br/>Taxes?"}
    E -->|"Yes"| F["Extract Data"]
    E -->|"No"| G["Skip Parcel"]
    F --> H["Add to Results"]
    G --> C
    H --> C
    C --> I["Export to CSV"]

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Data Extraction Process

graph TD
    A["Parcel Page"] --> B["Basic Info"]
    A --> C["Tax Info"]
    B --> D["Parcel Number"]
    B --> E["Property Address"]
    B --> F["Owner Details"]
    C --> G["Tax Year<br/>2022-2024"]
    C --> H["Amount Due"]
    C --> I["Amount Paid"]
    C --> J["Total Due"]
    G & H & I & J --> K["CSV Record"]

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Error Handling & Rate Limiting

sequenceDiagram
    participant S as Scraper
    participant W as Web Server
    participant D as Database
    S->>W: Request Parcel Page
    Note over S,W: 2-5 second delay
    W->>S: Return Page
    S->>S: Extract Data
    alt Success
        S->>D: Store Results
    else Network Timeout
        S->>S: Retry Request
    else No Data Found
        S->>S: Log & Skip
    end

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Features

• Automated scraping of delinquent tax data from Lancaster County's parcel viewer
• Handles multiple parcel numbers in batch
• Extracts data for tax years 2022-2024
• Collects property address and owner information
• Outputs results to CSV format
• Built-in rate limiting to prevent server overload
• Only captures parcels with actual delinquent taxes

Data Extracted

For each parcel with delinquent taxes, the script collects:

• Parcel number
• Property address
• Owner information
• Tax year (2022-2024)
• Amount due
• Amount paid
• Total due
• Scrape date

Prerequisites

• Python 3.7+
• Playwright
• Pandas

Installation

1. Clone this repository:

git clone https://github.com/caesarw0/lancaster-property-tax-scraper.git
cd lancaster-property-tax-scraper

2. Install required packages:

pip install -r requirements.txt

3. Install Playwright browsers:

playwright install

Usage

1. Prepare a list of parcel numbers in the script or import them from a file.

2. Run the script:

python src/property_scraper.py

The script will:

• Process each parcel number
• Extract delinquent tax information if available
• Save results to output/delinquent_taxes.csv

Example Code

from property_scraper import scrape_multiple_parcels

parcel_numbers = [
    "5408465600000",
    "1200794700000",
]

df = scrape_multiple_parcels(parcel_numbers)

Rate Limiting

The script includes built-in delays between requests (2-5 seconds) to avoid overwhelming the server. This helps ensure:

• Ethical scraping practices
• Reduced likelihood of IP blocking
• Server resource conservation

Output Format

The script generates a CSV file with the following columns:

• parcel_number
• address
• owner
• scrape_date
• tax_year
• amount_due
• amount_paid
• total_due

Error Handling

The script includes robust error handling for:

• Network timeouts
• Missing data
• Invalid parcel numbers
• Server errors

Legal Notice

This tool is designed for legitimate data collection from publicly available information. Users should:

• Review and comply with Lancaster County's terms of service
• Use reasonable request rates
• Respect the public resource

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License