Property Portfolio Forecaster & ROI Calculator

Overview

The Property Portfolio Forecaster & ROI Calculator is a Python-based application designed to help users estimate property valuations and calculate return on investment (ROI) for renovations. The application leverages a MySQL database to store property details, renovation features, and associated costs, enabling users to make informed decisions about property investments and renovations.

This tool allows users to:

• Add new or existing properties and forecast their valuation after renovations.
• Track renovation costs and their impact on ROI.
• Amend existing renovation cost records for accurate forecasting and ROI calculations.

Features

• Property Evaluation and ROI Forecasting:

  • Submit details of new or existing properties.
  • Add renovation features and receive a forecast of the updated property valuation.
  • Calculate ROI statistics based on added features and associated costs.

• Renovations Tracker:

  • Log renovation quotes and forecasts for properties.
  • Amend feature costs to reflect updated quotes or budgets, with recalculated ROI statistics.

• User-Friendly API:

  • Access the application programmatically through endpoints for various functionalities.

Project Files

Core Files

• Property_Portfolio_Forecaster_app.py: Flask application to serve the API.
• Property_Portfolio_Forecaster_main.py: Client-side script to interact with the API.
• Property_Portfolio_&_Forecaster.sql: SQL script to set up the database, tables, and triggers.
• Db_utils.py: Utility script for database connection.
• Config.py: Configuration file containing MySQL connection details.

Additional Folders & Content

• API Call Snippets: Screenshots of API results.
• Error Handling Screenshots: Demonstrates error-handling procedures and messages.
• Output Extracts: Text file extracts of terminal output for sample program usage.
• SQL Snippets: Screenshots of MySQL tables and data at the time of submission.
• Testing Folder: Includes basic test files for function and API testing.
• Testing Snippet: Screenshot of successful test runs.

System Requirements

• MySQL Workbench: Version 8.0 or higher.
• Python: Version 3.12.5 (64-bit).
• VSCode: Version 1.94.2 or higher.
• Required Python Libraries:
  • mysql.connector==9.0.0
  • flask==3.0.3
  • requests==2.32.3

API Requirements

• Configure Config.py with MySQL user details.
• Ensure the Property_Portfolio_Forecaster_app.py script is running to access the API.

Available API Endpoints

• Home Page: http://127.0.0.1:5001/
• Retrieve All Properties: http://127.0.0.1:5001/all_properties
• Retrieve Properties with Renovations: http://127.0.0.1:5001/all_properties_after_renovations
• Retrieve Properties by Bedroom Count: http://127.0.0.1:5001/properties_by_bedroom_nr/<bedroom_count> (e.g., <bedroom_count>=2).
• Retrieve Renovation Features: http://127.0.0.1:5001/renovation_features
• Retrieve Renovation Tracker by Property ID: http://127.0.0.1:5001/renovations_tracker/<property_id> (e.g., <property_id>=2).
• Refer to the API Call Snippets folder for examples of API responses.

Getting Started

Setup Instructions

• Download Project Files: Store all files in the same directory to maintain module accessibility.

Database Setup:

• Start MySQL.
• Open Property_Portfolio_&_Forecaster.sql in MySQL Workbench.
• Run the script to create the database and tables.

Configure MySQL Connection:

• Open Config.py.
• Enter your MySQL login details (username, password, etc.).

Start Flask App:

• Open a terminal and run:

python Property_Portfolio_Forecaster_app.py

• Ensure the server is active. You should see a confirmation message in the terminal.

Running the Client Program

• Open Property_Portfolio_Forecaster_main.py in VSCode.
• Run the script to access the interactive interface.
• Follow the prompts to input property details, add renovation features, and view forecasts.

User Journey & Results

Forecasting a Property

• Choose to forecast a new or existing property.
• Input property details (e.g., postcode, purchase amount, bedrooms).
• Add renovation features and their associated costs.
• View property valuation and ROI statistics, including:
  • Added value due to inflation.
  • Added value from renovations.
  • Net added value accounting for renovation costs.
• Optionally save the details in the database.

Amending Renovation Costs

• Select a property and renovation record to amend.
• Input the updated cost.
• View updated ROI statistics and a refreshed list of renovation records.
• Continue amending other properties or records as needed.

Output Examples

• Forecast Results: Displays property valuation and ROI statistics.
• Amend Results: Shows updated renovation costs and recalculated ROI.

Testing

Two test scripts are included in the Testing Folder. Screenshots of successful test runs are available in the Testing Snippet folder.

Future Enhancements

• Advanced Inflation Impact: Currently the code assumes a flat inflation percentage from the first year onwards. To enhance this, a more comprehensive calculation can be coded into SQL, possibly utilising real figures scraped from the web.
• Web Interface: Build a user-friendly web application for broader accessibility.
• Advanced ROI Calculations: Incorporate more complex algorithms for ROI forecasting.
• Data Visualization: Add graphical representations of ROI statistics and property trends.
• Enhanced Error Handling: Improve error messages and handling for edge cases.

Contact

For questions, feedback, or collaboration opportunities, please contact:

GitHub: CodeHerUniverse