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Topsis_Arjun_Angirus_102303596

A simple Python package implementing TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) for multi-criteria decision-making.

Install

pip install .

CLI Usage

# After installation
topsis-aaa-102303596 <InputDataFile> <Weights> <Impacts> <OutputResultFile>

# Example
topsis-aaa-102303596 example.csv "0.5,0.3,0.2" "+,+,-" output.csv
  • InputDataFile: CSV with first column as identifier, remaining columns numeric criteria.
  • Weights: Comma-separated numeric weights (same count as criteria).
  • Impacts: Comma-separated + or - for each criterion.
  • OutputResultFile: Path to save results.

Python API

from Topsis_Arjun_Angirus_102303596.topsis import main
# main() reads args from sys.argv

Project Structure

.
├── LICENSE.txt
├── README.md
├── setup.cfg
├── setup.py
├── Topsis_Arjun_Angirus_102303596/
│   ├── __init__.py
│   └── topsis.py
└── .gitignore

Requirements

  • Python >= 3.8
  • numpy, pandas

License

MIT

About

Python package that implements the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for multi-criteria decision making. The package supports both command-line usage and programmatic execution, allowing users to rank alternatives based on multiple quantitative criteria using user-defined weights and impacts.

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