Inspiration
I started investing in a Tax-Free Savings Account (TFSA) at the beginning of 2022 and encountered difficulties in tracking my activity over time and understanding the historical relationships between stocks.
What it does
The Stock Portfolio App is a desktop application built with Python. It allows users to simulate purchase and selling activities and provides high-level insights to maximize profits when deciding to sell a stock on a particular date.
How we built it
The project consists of three major components:
- SQLite database: Used to store user activity, especially when the app is exited or the computer is shut off.
- Data Analytics via Pandas, Numpy, Matplotlib: Enables data analysis and visualization of market trends and portfolio activity.
- Tkinter User Interface: Provides the desktop GUI for interacting with the application (Note: In the future, the UI will be translated into Kivy for mobile use).
Challenges we ran into
During the development process, we encountered several challenges, including:
- Creating data pipelines to synchronize user interactions with the Tkinter UI, object-oriented program changes using pandas, and updates to the database at key checkpoints.
- Translating design ideas from Tkinter, as small tweaks can significantly impact the overall design.
Accomplishments that we're proud of
Throughout the development of the Stock Portfolio App, we achieved the following accomplishments:
- Integration of backend and frontend components into a cohesive data application.
- Gained experience in systems design, considering both the details and the bigger picture.
What's next for Stock Portfolio App
The next step for the Stock Portfolio App is to transition the UI to Kivy, enabling a mobile environment for enhanced user experience.
Demo
Watch the following video for a demonstration of the application and how to create a new portfolio: Demo Video.
Credit
This project was inspired by my personal interest in visualizing and optimizing my Tax-Free Savings Account (TFSA) investments. Please note that the data insights provided by the app are not intended to serve as professional investment advice.
References:
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