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TOPSIS algorithm as a command-line tool

Project description

Topsis-Py (CLI-Based Python Package)

A Python command-line implementation of TOPSIS
(Technique for Order Preference by Similarity to Ideal Solution) for
Multi-Criteria Decision Making (MCDM) problems.

This package is designed to be academically correct, easy to use, and PyPI-ready.


📌 Project Highlights

Feature Description
Algorithm Standard TOPSIS methodology
Interface Command-Line Interface (CLI)
Input CSV-based decision matrix
Validation Strict input & argument checks
Output Ranked alternatives with scores
Documentation Clear theory + workflow diagrams

❓ What is TOPSIS?

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

🔑 Core Idea

The best alternative is the one that:

  • Is closest to the ideal best solution
  • Is farthest from the ideal worst solution

🌍 Common Applications

Domain Example Use
Engineering Design or component selection
Business Supplier & product evaluation
Finance Investment ranking
Data Science Model or algorithm comparison

🔄 TOPSIS Algorithm Flow

flowchart TD
    A[Decision Matrix] --> B[Normalization]
    B --> C[Apply Weights]
    C --> D[Ideal Best Solution]
    C --> E[Ideal Worst Solution]
    D --> F[Distance from Ideal Best]
    E --> G[Distance from Ideal Worst]
    F --> H[TOPSIS Score]
    G --> H
    H --> I[Final Ranking]

🧠 Program Workflow

flowchart LR
    A[CLI Arguments] --> B[Input Validation]
    B --> C[Load CSV File]
    C --> D[TOPSIS Computation]
    D --> E[Score & Rank Calculation]
    E --> F[Write Output CSV]

📦 Installation

pip install topsis-swastik-102303585

🚀 Usage

python topsis.py <input_file> <weights> <impacts> <output_file>

Example:

python topsis.py data.csv "1,2,1,1" "+,+,-,+" result.csv

⚠️ Limitations

  • Categorical data not supported
  • Missing values not allowed
  • Weights must be positive
  • Impacts must be '+' or '-'

📜 License

MIT License

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