chee86j / ForeclosureAuctionPyScraper

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Foreclosure Auctions Python Scraper

Welcome to the Foreclosure Auctions Python Scraper — a premier tool for seamlessly gathering data from government foreclosure auctions sites. Powered by Python, this robust scraper harnesses the capabilities of the BeautifulSoup and Requests libraries to meticulously parse and extract crucial auction data from websites, starting with our example site at "https://salesweb.civilview.com/Sales/SalesSearch?countyId=9" for Morris County, New Jersey.

My solution is designed for professionals in real estate, data analysis, and investment sectors looking to access up-to-date and comprehensive auction data without the hassle of manual research. Whether you're monitoring auction trends or preparing investment strategies, this tool provides the data backbone you need.

Key Features

  1. Reliable Data Extraction: Automatically scrapes detailed auction data including case numbers, sale dates, property addresses, and status.
  2. Easy to Set Up and Use: Quick setup process and straightforward commands to get the data you need.
  3. Efficient Data Storage: Utilizes SQLite, a lightweight database solution, to store and manage the extracted data efficiently.
  4. Customizable and Expandable: Designed with modularity in mind, allowing for easy updates and customization to cater to specific user needs.

Technologies & Libraries

  1. BeautifulSoup for parsing HTML.
  2. aiohttp for asynchronous web requests.
  3. SQLite for data storage.
  4. Python's logging module for error logging and debugging.

Prerequisites

Before running the scraper, ensure you have the following installed:

  1. Python: Ensure Python 3.x is installed on your system. python.org.
  2. SQLite: Make sure SQLite is installed on your system:
    • SQLite Download page and follow the installation instructions. Look under'Precompiled Binaries for Windows' for the [DLL]
    • Verify installation by running sqlite3 in your terminal. If installed, you should see the SQLite version and a command-line interface.

Installation

  1. Clone the repository
  2. Set up a virtual environment -MacOS/Linux: source venv/bin/activate -Windows: venv\Scripts\activate
  3. Install the required packages -pip install aiohttp beautifulsoup4

Running the Scraper

  1. Run the scraper -python src/main.py

Testing the Scraper

  1. Run the tests -python -m unittest test/test_scraper.py

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