Topsis-Aryaman-102303622 1.0.2

A Python package to implement TOPSIS for MCDM

TOPSIS-Aryaman-102303622

📌 Overview

TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a Multi-Criteria Decision-Making (MCDM) method.

It ranks alternatives based on:

• Minimum distance from the Ideal Best solution
• Maximum distance from the Ideal Worst solution

The alternative closest to the ideal solution is considered the best choice.

This package provides a simple CLI tool and Python API to apply TOPSIS on CSV or Excel datasets.

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📦 Installation

Install the package using pip:

pip install Topsis-Aryaman-102303622

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🚀 Usage

You can use this package in two ways:

1. Command Line Interface (CLI)
2. As a Python Library

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1️⃣ Command Line Interface (CLI)

Run the following command in your terminal:

topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>

from topsis_aryaman_102303622 import topsis

topsis("data.xlsx", "1,1,1,1", "+,+,-,+", "result.csv")

🔹 Command Line Arguments

Argument	Description	Example
InputDataFile	Path to input CSV or Excel file	data.xlsx
Weights	Comma-separated weights for criteria	"1,1,1,1"
Impacts	Comma-separated impacts (+ or -)	"+,+,-,+"
ResultFileName	Output CSV file name	result.csv

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📊 Input Data Format

The input file must be in CSV or Excel format.

Structure

• First column: Names of alternatives (e.g., M1, M2, M3)
• Remaining columns: Numeric criteria values

Example (data.csv)

Fund Name,P1,P2,P3,P4,P5
M1,0.84,0.71,6.7,42.1,12.59
M2,0.91,0.83,7.0,31.7,10.11
M3,0.79,0.62,4.8,46.7,13.23

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⚠️ Constraints & Assumptions

• Number of weights must equal number of criteria
• Number of impacts must equal number of criteria
• Criteria values must be numeric
• Impacts must be:
  • + for benefit criteria
  • - for cost criteria

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📄 License

This project is licensed under the MIT License.

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👤 Author

Aryaman Shukla
Roll No: 102303622