The main goal for the project is to convert the legacy data wrangling and visualization application written in JavaScript to Python, containerize it, and use FastAPI as the server. This will involve several different steps for the learners, including:

- Analyzing the existing JavaScript codebase and understanding the data wrangling and visualization logic.

- Converting the existing JavaScript code to Python and ensuring compatibility with the single dataset/datafile.

- Containerizing the Python application for easy deployment and management.

- Integrating FastAPI as the server for the containerized application.

What tasks will learners need to complete to achieve the project goal?

- Completed analysis of the existing JavaScript codebase and documentation of the data wrangling and visualization logic.

- Converted Python codebase with documentation and compatibility with the single dataset/datafile.

- Containerized Python application with documentation for deployment and management.

- Integrated FastAPI as the server with documentation for future maintenance.

We have a team of 5 data specialists who maintain a visualization and wrangling suite that can mentor the learners who are working on data aspects. We have pipelines & development guidelines for creating containerized applications as well as a team of 5 local software developers who can assist in converting the JavaScript to FastAPI.