Attendance-Visualisation

My Dissertation Project on Attendance Monitoring Visualisation, at the University of Sussex (2023).

Marks achieved:

• Interim Report: 68/100
• Project (Final Report and Codebase): 67/100
• Presentation: 66/100
• Overall: 67/100

See Section 8 (Conclusion) of the Final Report (under /documents), for a discussion of where this project did and did not meet its requirements.

Abstract

This project investigates a prototype solution to the growing problem of tracking university attendance. This is motivated by the link between attendance and attainment in higher education, since keeping track of students who may be falling behind and addressing the reasons for this, is likely to yield greater attainment and improve student experience. There is currently no widely available open-source attendance-tracker, nor an option widely in use for the University of Sussex, as most solutions are bespoke tailored options hidden behind paywalls and consulting. This project seeks to produce a three-tier application to store attendance monitoring data for visualisation to key university attendance monitoring staff. The projects objectives were generally achieved, but there is still further work to be done in this area. Functionality produced during this project includes a Flask API with a variety of endpoints for retrieving attendance monitoring data from a PostgreSQL Database, and a ReactJS Front-end that presents several visualisations and options to filter this data.

Installation

Note: Requires Node.js and Python3

In your terminal/OS of choice (though written for Windows CMD)...

1. Run npm install in the project directory to install dependencies from package.json.
2. Navigate to the '/api' subdirectory e.g. by using cd api
3. Create a python virtual environment at '/api/venv' with python3 -m venv venv
4. Activate your virtual environment by running ./venv/Scripts/activate (./venv/bin/activate for Unix systems)
5. Install all python dependencies into your virtual environment by running pip install -r requirements.txt
6. Exit your virtual environment with a simple deactivate

Further steps

Create a configuration file for your Flask API in the following format, where a common 'APP' configuration stores common items, and subversions have differing attributes.

APP:
    secret_key: <value>
    SQLALCHEMY_TRACK_MODIFICATIONS: <value>
    SQLALCHEMY_POOL_RECYCLE: 300
    CACHE_TYPE: SimpleCache
    CACHE_DEFAULT_TIMEOUT: 60

APP_DEV:
    SQLALCHEMY_DATABASE_URI: <value>

APP_DEV_SERVICE:
    SQLALCHEMY_DATABASE_URI: <value>

APP_PROD:
    SQLALCHEMY_DATABASE_URI: <value>

To Start

1. Open a terminal in the project's directory
2. Run npm start to start up the React Frontend Application
3. Run npm run-script start-api to start up the Flask Backend API
4. And that's it!