topsis-sachin-102303557 1.0.0

TOPSIS decision method Python package

TOPSIS Implementation - Sachin Goyal

A complete TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) implementation in Python with both CLI and Web Service interfaces.

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🚀 Quick Start

📦 Install from PyPI

pip install topsis-sachingoyal-102303557==1.0.0

🌐 Try the Web Interface

Access the live web service at:
https://topsis-sachin-goyal-102303557.vercel.app/

Upload your CSV, enter weights and impacts, and receive results via email!

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📁 Project Structure

Topsis_SachinGoyal_102303557/
│
├── topsis/                     # Python package
│   ├── __init__.py
│   └── topsis.py               # Core TOPSIS implementation
│
├── templates/                  # Web frontend
│   └── index.html              # Beautiful web UI
│
├── uploads/                    # Temporary file storage (created automatically)
│
├── main.py                     # FastAPI backend server
├── data.csv                    # Sample input data
├── setup.py                    # Package setup configuration
├── requirements.txt            # Python dependencies
├── sample.env                  # Environment variables template
├── README.md                   # This file

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📋 Requirements

• Python 3.6+
• Dependencies: pandas, numpy, fastapi, mailjet-rest, python-dotenv

Install all dependencies:

pip install -r requirements.txt

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🔧 Setup for Local Development

1. Clone the Repository

git clone <https://github.com/SachinGoyal94/Topsis_SachinGoyal_102303557>
cd Topsis_SachinGoyal_102303557

2. Install Dependencies

pip install -r requirements.txt

3. Configure Environment Variables

Create a .env file in the project root with the following:

SENDER_NAME=Your Name
SENDER_EMAIL=[e-mail]
MJ_APIKEY_PUBLIC=your-mailjet-public-key
MJ_APIKEY_PRIVATE=your-mailjet-private-key

Note: A sample.env file is provided as a template. Copy it to .env and fill in your credentials.

Required Variables:

• SENDER_NAME - Your name or service name
• SENDER_EMAIL - Verified sender email in Mailjet
• MJ_APIKEY_PUBLIC - Your Mailjet API public key
• MJ_APIKEY_PRIVATE - Your Mailjet API secret key

4. Run the Backend Server

uvicorn main:app --reload

The API will be available at http://127.0.0.1:8000

5. Open the Frontend

Navigate to http://127.0.0.1:8000 in your browser (if serving static files) or open templates/index.html directly.

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💻 CLI Usage

Command Syntax

python -m topsis.topsis <InputFile> "<Weights>" "<Impacts>" <OutputFile>

Arguments

Argument	Description	Example
InputFile	Path to input CSV file	data.csv
Weights	Comma-separated numeric weights	"1,1,1,1,2"
Impacts	Comma-separated + or -	"+,+,-,+,+"
OutputFile	Path for output CSV	result.csv

Example

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

Output: Creates result.csv with two additional columns:

• Topsis Score (higher is better)
• Rank (1 = best)

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📊 Input CSV Format

Your CSV must have:

• First column: Identifier (e.g., product name, model ID)
• Remaining columns: Numeric criteria values

Example Input

Name,Cost,Performance,Reliability,Efficiency
ProductA,250,8,9,7
ProductB,200,7,8,9
ProductC,300,9,7,8

Example Output

Name,Cost,Performance,Reliability,Efficiency,Topsis Score,Rank
ProductA,250,8,9,7,0.534,2
ProductB,200,7,8,9,0.628,1
ProductC,300,9,7,8,0.421,3

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🌐 Web Service Usage

1. Visit: https://topsis-sachin-goyal-102303557.vercel.app/
2. Upload your CSV file
3. Enter weights (e.g., 1,1,1)
4. Enter impacts (e.g., +,+,-)
5. Enter your email address
6. Submit and receive results via email

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⚠️ Common Errors

Error	Cause	Solution
Input file not found	File path is incorrect	Check file path and try again
Invalid email format	Email is malformed	Use valid email format
Weights and impacts count mismatch	Different number of weights vs impacts	Ensure equal counts
Impacts must be + or -	Invalid impact symbol	Use only + or -
Weights must be numeric	Non-numeric weight	Use only numbers
All columns must be numeric	Non-numeric criteria values	Ensure all criteria are numbers

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📚 How TOPSIS Works

1. Normalize the decision matrix using Euclidean normalization
2. Weight the normalized matrix
3. Identify ideal best and worst solutions
4. Calculate Euclidean distances from ideal solutions
5. Compute similarity score: S = D- / (D+ + D-)
6. Rank alternatives by score (higher is better)

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🛠️ Technology Stack

• Backend: FastAPI (Python)
• Frontend: HTML, CSS, JavaScript
• Email Service: Mailjet REST API
• Package Management: PyPI
• Deployment:
  • Frontend: Vercel
  • Backend: Render

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👤 Author

Sachin Goyal

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🔗 Links

• PyPI Package: topsis-sachingoyal-102303557
• Web App: https://topsis-sachin-goyal-102303557.vercel.app/
• GitHub: https://github.com/SachinGoyal94/Topsis_SachinGoyal_102303557

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