Metadata-Version: 2.2
Name: 102203584
Version: 1.0.0
Summary: It performs topsis
Home-page: https://github.com/trish-r/102203584-topsis
Author: Trish Rustagi
Author-email: trishrustagi@gmail.com
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: requires-dist
Dynamic: summary

# TOPSIS Implementation in Python
A Python implementation of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for multi-criteria decision-making problems. This package processes an input dataset, calculates the TOPSIS scores, and ranks alternatives based on their scores.

## Installation
You can install this package directly from PyPI:
```pip install 102203584```

## Usage
### Command-Line Interface
Run the script using the following format:
``` python <program.py> <InputDataFile> <Weights> <Impacts> <ResultFileName> ```

### Arguments:

1. InputDataFile: Path to the input .csv file containing the dataset.
-The first column should contain the names of the alternatives.
-The remaining columns should contain numeric criteria values.

2. Weights: Comma-separated values representing the importance of each criterion.

3. Impacts: Comma-separated values (+ or -) indicating whether the criterion is beneficial (+) or non-beneficial (-).

4. ResultFileName: Name of the output .csv file where the results (TOPSIS scores and ranks) will be saved

## Dependencies
This package requires the following Python libraries:
-pandas
-numpy

## License
This repository is licensed under the MIT license. See LICENSE for details.
