Metadata-Version: 2.4
Name: topsis-shivam-102303881
Version: 0.0.1
Summary: TOPSIS implementation using Python
Author: Shivam Kumar
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Dynamic: author
Dynamic: description
Dynamic: description-content-type
Dynamic: requires-dist
Dynamic: summary

## TOPSIS-Shivam-102303881

TOPSIS-Shivam-102303881 is a Python package that implements the **TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)** method for multi-criteria decision making (MCDM).

TOPSIS is a widely used decision-making technique that ranks alternatives based on their relative distance from an ideal best solution and an ideal worst solution. This package allows users to easily apply the TOPSIS method on tabular data stored in CSV files using a simple command-line interface.

The package performs proper input validation, handles common user errors, and generates a ranked output with TOPSIS scores, making it suitable for academic assignments as well as practical decision-analysis tasks.

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## Features
- Command-line implementation of TOPSIS
- Supports multiple decision criteria
- Handles both beneficial (+) and non-beneficial (-) attributes
- Input validation for files, weights, and impacts
- Outputs TOPSIS score and rank for each alternative

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## Installation

Install the package directly from PyPI:

pip install TOPSIS-Shivam-102303881

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## Usage

Run the TOPSIS analysis from the command line:

topsis input.csv "1,1,1,2,1" "+,+,+,-,+" output.csv

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## Input File Format
- The input file must be a CSV file
- The first column should contain the names of alternatives
- All remaining columns must contain numeric values only
- The number of weights and impacts must match the number of criteria columns

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## Output File
The output CSV file contains:
- All original input columns
- A new column named **Topsis Score**
- A new column named **Rank**, where rank 1 indicates the best alternative

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## Author
Shivam Kumar 
Roll No: 102303881  

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## License
This project is developed for academic and educational purposes.
