Fire Journey

Fire Journey is a personal finance application designed to help users track their income, expenses, investments, and loans. It includes features such as a FIRE (Financial Independence, Retire Early) calculator, portfolio management, and net worth tracking. It was made by Maksimilian Stajer (682271) for the Fin-tech course.

Features

• User Login: Secure login for each user.
• Income and Expense Tracking: Record and predict expenses and income.
• Portfolio Management: Track stock investments, add and remove holdings, and view performance.
• Net Worth Calculation: Track your net worth over time.
• Assets and Loans Management: Track assets and manage loan details.
• FIRE Calculator: Calculate the number of years to reach financial independence based on various inputs.

Installation

1. Clone the repository:

   git clone https://github.com/StayerM/FinTech-682271
   cd FinTech-682271

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate

3. Install the required packages:

   pip install -r requirements.txt

4. Run the application:

   python PFM_app.py

Dependencies

• Python 3.6+
• PyQt5
• scikit-learn
• matplotlib
• seaborn
• pandas
• yfinance
• SQLite3 (built-in with Python)

Usage

1. On startup, the application will prompt the user to log in.
2. After logging in, users can navigate through the tabs to manage their finances.
3. The Income and Expenses tab allows users to add and view records, predict future expenses, and visualize weekly income and expenses.
4. The Portfolio tab lets users manage their stock holdings, view all records, and track portfolio performance.
5. The Net Worth tab shows the user's current net worth and provides a graphical history.
6. The Assets and Loans tab allows users to manage their assets and loans.
7. The FIRE Calculator tab helps users calculate their retirement timeline based on their financial data.

Fake Data Maker

To help with testing and development, a Fake Data Maker script is included. This script generates fake data for the records, portfolio, and net_worth_history tables without adding any assets, loans, or recurring records.

Fake Data Maker Usage

1. Ensure the SQLite database (finance.db) is set up.
2. Run the Fake Data Maker script:

   python fake_data_maker.py

This script will:

• Ensure the user "Maks" exists and retrieve their user ID.
• Generate and insert 100 fake records into the records table.
• Generate and insert 10 fake records into the portfolio table.
• Generate and insert net worth history entries from January 2023 to June 2024.

License

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

Contributing

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Commit your changes (git commit -am 'Add new feature').
4. Push to the branch (git push origin feature-branch).
5. Create a new Pull Request.

Acknowledgements

Special thanks to the open-source community for providing the tools and libraries that made this project possible.

Contact

For questions or feedback, please contact max.stajer@gmail.com.