This project originated on a preconfigured virtual desktop with a fully set up environment, encompassing all necessary dependencies. Initially, the application consisted of a single module.py file designed for CRUD operations. The integration was facilitated through Jupyter Notebook, allowing for easy launching using localhost. The dataset, a singular .csv file, was initially added to MongoDB, seamlessly integrated into the virtual environment. The initial version featured filters, a data table, and a visual component.

In the enhanced version (Current Version), significant improvements were implemented. Utilizing render.com, a host and server were created, and the new GitHub repository was connected to the server. Git was employed for meticulous version control of changes, and command scripting played a crucial role in installing required dependencies. The Jupyter Notebook application underwent conversion into a Python application, aptly renamed as app.py. Unnecessary functionalities were removed, transitioning from MongoDB to a NoSQL solution, specifically SQLite. Algorithms, data structures, and databases were elevated to meet MVP standards. The final step involved deploying the enhanced application to the live server, accessible at https://tammyhartlinescapstone.onrender.com/.