Metadata-Version: 2.1
Name: topsis-ravish-102303651
Version: 0.0.2
Summary: TOPSIS implementation
Author: ravish
Author-email: sharmaravish77400@gmail.com
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy

TOPSIS Python Package
📌 About TOPSIS

TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making (MCDM) method.
It helps in ranking alternatives based on their distance from the ideal best and ideal worst solutions.

This package provides a command-line implementation of TOPSIS in Python.

📦 Installation

Install the package from PyPI using:

pip install Topsis-Ravish-102303651


🚀 Usage

The package can be used directly from the command line.

🔹 Command Format
topsis <inputFileName> <weights> <impacts> <outputFileName>

🔹 Example
topsis data.csv "1,1,1,2" "+,+,-,+" result.csv

📄 Input File Format

The first column should contain the names of alternatives.

From second column to last column, values must be numeric.

The file must contain at least 3 columns.

✔ Example Input (data.csv)
Fund Name,P1,P2,P3,P4
M1,0.67,0.45,6.5,42.6
M2,0.6,0.36,3.6,53.3
M3,0.82,0.67,3.8,63.1
M4,0.6,0.36,3.5,69.2

📤 Output File Format

The output file will contain two additional columns:

Topsis Score

Rank

✔ Example Output (result.csv)
Fund Name,P1,P2,P3,P4,Topsis Score,Rank
M1,0.67,0.45,6.5,42.6,0.61,2
M2,0.6,0.36,3.6,53.3,0.42,4
M3,0.82,0.67,3.8,63.1,0.78,1
M4,0.6,0.36,3.5,69.2,0.35,5

⚠️ Error Handling

The program checks for the following errors:

Incorrect number of command-line arguments

Input file not found

Less than 3 columns in input file

Non-numeric values in criteria columns

Number of weights, impacts, and criteria mismatch

Impacts other than + or -

Weights and impacts not separated by commas

Appropriate error messages are displayed for invalid inputs.

🛠 Requirements

Python 3.x

pandas

numpy

👨‍💻 Author

Name: Ravish
Roll Number: 102303651
Course: B.Tech (Computer Engineering)

📄 License

This project is licensed under the MIT License.

## License

MIT License

Copyright (c) 2026 Ravish sharma

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
