Metadata-Version: 2.2
Name: topsis-sneha-102303723
Version: 1.0.0
Summary: TOPSIS implementation using Python
Author: Sneha
Author-email: ssneha1_be23@thapar.edu
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: description-content-type
Dynamic: requires-dist
Dynamic: summary

# Topsis-Sneha-102303723

This Python package implements the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, a multi-criteria decision-making technique used to rank alternatives based on their distance from an ideal best and ideal worst solution.

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## Installation

Install the package from PyPI using pip:

pip install Topsis-Sneha-102303723

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## Usage

The package provides a command-line interface (CLI).

### Command format

topsis <input_file> <weights> <impacts> <output_file>

### Example

topsis data.csv "2,1,3,1,2" "+,-,+,+,-" result.csv

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## Input File Format

- The input file must be a CSV file.
- The file must contain at least 3 columns.
- The first column is treated as an identifier (name/label).
- All columns from the second column to the last column must contain numeric values only.

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## Weights and Impacts

- Weights must be numeric and separated by commas.
- Impacts must be either + (benefit) or - (cost) and separated by commas.
- The number of weights and impacts must be equal to the number of criteria columns.

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## Output

- The output is a CSV file.
- Two additional columns are added:
  - Topsis Score
  - Rank
- Higher Topsis score indicates a better rank.

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## Error Handling

The program validates:
- Correct number of command-line arguments
- File existence
- Numeric values in criteria columns
- Correct number of weights and impacts
- Valid impact symbols (+ or -)

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## Author

Sneha
