COMP455: Extreme Computing - Real Estate Search Tool

This project is an extreme computing application that enables efficient searching and filtering of real estate properties across the United States. It leverages a large dataset containing detailed property information and provides an intuitive web-based interface for users to filter and sort properties based on various criteria.

The application demonstrates the use of:

• Flask for building the web application.
• SQLite for managing property data.
• SQLAlchemy for database operations.
• JavaScript for dynamic front-end functionality (autocomplete and filtering).
• Pandas for data preprocessing.

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Features

• Large Dataset Handling: Optimized search and filtering of over 500,000 real estate properties.
• Autocomplete Functionality: Dynamically suggests city names based on user input.
• Advanced Search Filters:
  • Price range
  • Number of bedrooms and bathrooms
  • House size (square feet)
  • State and city selection
• Dynamic Results Page:
  • Display of search results with sorting options.
  • Additional filtering directly on the results page.
• Responsive Web Interface: Built with modern design principles for a user-friendly experience.

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Prerequisites

1. Python 3.x installed.
2. All dependencies listed in requirements.txt (see installation steps below).
3. USA Real Estate Dataset: Download from Kaggle.

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Getting Started

Step 1: Download and Set Up the Dataset

• Download the dataset from this Kaggle link.
• Save the .csv file in the root directory of your project folder.
  • Ensure the file is named realtor-data.zip.csv for compatibility with the program.

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Step 2: Install Dependencies

Install all required Python libraries using:

pip install -r requirements.txt

Step 3: Generate Database

python generate_db.py

This step will:

• Filter the dataset for properties with a "for_sale" status.
• Clean and preprocess the data.
• Generate an SQLite database named real_estate_new.db.

Step 4: Run the Application

python app.py

Step 5: Use the Application

1. Open your browser and navigate to http://localhost:5000/.
2. Use the search form to input your criteria:
   • Select a state or city.
   • Set price, bedroom, bathroom, and house size filters (optional).
   • Sort results by price or house size.
3. Click Search to view the results.
4. Further refine your search on the results page using additional filters.

Known Issues and Improvements

• The dataset is too large to be included in the repository. Ensure you download it from Kaggle.
• Additional features like property visualization (e.g., maps or images) can be added.

License

This project is licensed under the MIT License. See LICENSE for details.