Topsis-Naman-102317229 1.2

A Python implementation of the TOPSIS decision-making method.

TOPSIS Decision Support System

A Python implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) used for multi-criteria decision making.
This project provides both a PyPI package and a Flask-based web application that allows users to upload datasets, assign weights and impacts, and receive ranked results via email.

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🚀 Features

• Implements the TOPSIS algorithm from scratch
• Accepts CSV/XLSX datasets
• Supports customizable weights and impacts
• Generates TOPSIS score and rank automatically
• Published as an installable PyPI package
• Integrated with a simple and user-friendly Flask web interface
• Automated result delivery through email
• Input validation for weights, impacts, and email format

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📦 PyPI Package

Install directly using:

pip install Topsis-Naman-102317229

PyPI Link:
https://pypi.org/project/Topsis-Naman-102317229/

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💻 Local Usage

After installing the package:

from topsis.topsis import main

main()

Or via command line:

topsis <inputfile> <weights> <impacts> <outputfile>

Example:

topsis data.csv "1,1,1,1" "+,+,-,+" result.csv

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🌐 Live Web Application

Access the deployed web app here:

👉 https://naman25.pythonanywhere.com

Web App Workflow:

1. Upload the dataset
2. Enter weights (comma separated)
3. Enter impacts (+ or -)
4. Provide your email address
5. Receive the ranked result file via email

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📊 Input File Requirements

• First column: Alternative names (non-numeric)
• Remaining columns: Numeric criteria values
• Minimum 3 columns required
• Number of weights must equal number of impacts
• Impacts must be either + (benefit) or - (cost)

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🛠 Tech Stack

• Python
• Pandas & NumPy
• Flask
• SMTP (Email Automation)
• PyPI Packaging