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Result Analysis Tool

This is a Flask-based web application designed for result analysis. It provides functionalities to register users, perform result analysis, and generate reports. The application uses SQLAlchemy for database management, Flask-WTF for form handling, and Flask-Login for user authentication.

Prerequisites

Before running the application, make sure you have the required Python libraries installed. You can install them using the following command:

pip install requirement.txt

Getting Started

  1. Clone the repository to your local machine:
git clone https://github.com/satishkumarmurugan/Student-Result-Generators-and-Analyzers.git
  1. Run the application:
python app.py

Usage

User Registration

  • Access the application at http://localhost:5000/ in your web browser.
  • Click on the "Register" link in the navigation bar.
  • Fill out the registration form with your name, email, and password.
  • Click on the "Register" button to create an account.

User Login

  • Click on the "Login" link in the navigation bar.
  • Enter your registered email and password.
  • Click on the "Login" button.

Result Analysis

  • Navigate to the "Result Analysis" section.
  • Upload an Excel file containing student result data.
  • Perform various result analysis operations, such as counting failures, calculating pass percentages, etc.
  • View the result analysis report.

Comparison Tool

  • Navigate to the "Comparison Tool" section.
  • Upload Excel files for comparison.
  • The tool will merge the data and extract relevant columns for further analysis.
  • View the formatted output in a new Excel file.

Topper Analysis

  • Navigate to the "Topper Analysis" section.
  • Upload an Excel file containing student result data.
  • The application will identify the top scorers and generate an output Excel file.

Logout

  • Click on the "Logout" link in the navigation bar to log out of your account.

Important Notes

  • Make sure to set a secure secret key (app.secret_key) and database URI (app.config['SQLALCHEMY_DATABASE_URI']) before deploying the application in a production environment.
  • This readme assumes basic knowledge of Flask and web application deployment.

Feel free to customize and extend the application based on your specific requirements!