Topsis-Gazal-102217174 0.2

A Python implementation of the TOPSIS method.

Here's a draft for your GitHub README file explaining parts 1 and 2 of your assignment:

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Topsis Implementation and Python Package

This repository contains the implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as part of an assignment. It includes two components:

1. Command-Line Python Program
2. Python Package Published on PyPI

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1. Command-Line Python Program

This program calculates the TOPSIS scores and ranks for a given dataset.

How It Works:

• Input File:
  The input file is a CSV file with three or more columns:

  • The first column contains the names of the objects/variables (e.g., M1, M2, M3, etc.).
  • The remaining columns contain numeric data.

• Output File:
  The output file includes all columns from the input file with two additional columns:

  • Topsis Score
  • Rank

Features:

• Handles exceptions for:
  • Incorrect input format.
  • Missing files.
  • Non-numeric values.
• Ensures weights and impacts are correctly formatted.
• Validates the consistency of input dimensions (number of weights, impacts, and columns).

Usage:

Run the program through the command line:

python <program.py> <InputDataFile> <Weights> <Impacts> <ResultFileName>

Example:

python Topsis-Gazal-102217174.py data.csv "1,1,1,2" "+,+,-,+" result.csv

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2. Python Package on PyPI

https://pypi.org/project/Topsis-Gazal-102217174/

User Guide:

• Install the package using pip:

  pip install Topsis-Gazal-102217174
  

• Run the TOPSIS calculation from the command line:

  Topsis-Gazal-102217174 <InputDataFile> <Weights> <Impacts> <ResultFileName>
  

  Example:

  Topsis-Gazal-102217174 data.csv "1,1,1,2" "+,+,-,+" result.csv
  

Testing:

The package was thoroughly tested by installing it from PyPI and running multiple test cases.

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Resources and References

• Learn TOPSIS
• How to Publish Python Packages to PyPI

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