Topsis-Yashika-102303439 1.0.0

A Python package for TOPSIS method

TOPSIS Python Package

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

The package is designed as a command-line tool and validates all inputs as per the problem requirements.

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Features

• Command-line execution
• CSV file input
• Supports multiple criteria
• Handles weights and impacts
• Proper input validation and error handling
• Outputs TOPSIS score and rank
• Can be installed using pip

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Installation

After uploading the package to PyPI, install it using:

pip install Topsis-Yashika-102303439

Usage
- The program must be executed from the command line

Syntax
- python topsis.py <InputDataFile> <Weights> <Impact> <OutputResultFileName>
Example
- python topsis.py data.csv "1,1,1,1,1" "+,+,-,+,+" output-result.csv

Input File Format
- The input file must be in CSV format
- The file must contain three or more columns
- The first column should contain names/identifiers of alternatives
- From the second column onward, all values must be numeric

Sample Input
Fund Name,P1,P2,P3,P4,P5
M1,0.82,0.67,7,48.1,14.15
M2,0.83,0.69,3.3,50.7,13.88

Weights and Impacts
- Weights must be numeric
- Impacts must be either:
  - + for benefit criteria
  - - for cost criteria
- Weights and impacts must be comma-separated
- Number of weights = number of impacts = number of criteria


Output File
- Output is generated in CSV format
- Two new columns are added:
   - Topsis Score
   - Rank
- Higher TOPSIS score indicates a better alternative


Error Handling

- The program checks and handles the following errors:
- Incorrect number of command-line arguments
- Input file not found
- Less than three columns in input file
- Non-numeric values in criteria columns
- Mismatch between number of criteria, weights, and impacts
- Invalid impact symbols

Author
- Yashika