# Topsis-Vansh-102203021
A Python package to implement the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method for multi-criteria decision-making problems.
---
## Features
- Rank alternatives based on multiple criteria.
- Handle positive and negative impacts of criteria.
- Simple to use with CSV input/output.
- Fully customizable weights and impacts.
---
## Installation
Install the package directly from PyPI:
```bash
pip install Topsis-Vansh-102203021
```
---
## How to Use
The package can be used through the command line or imported into a Python script.
### **Command-Line Usage**
The basic syntax for using the package via the command line:
```bash
python -m topsis <input_file> <weights> <impacts> <output_file>
```
#### **Parameters:**
- `input_file`: CSV file containing the decision matrix.
- `weights`: Comma-separated values representing the importance of each criterion (e.g., `1,1,2,3`).
- `impacts`: Comma-separated values representing the impact of each criterion (`+` for positive, `-` for negative).
- `output_file`: Name of the CSV file where the results will be saved.
#### **Example:**
```bash
python -m topsis data.csv "1,1,2,3" "+,+,-,+" result.csv
```
#### **Input File Format:**
The input file must be a CSV file with the following structure:
| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 |
|--------------|-------------|-------------|-------------|-------------|
| A1 | 250 | 16 | 12 | 5 |
| A2 | 200 | 18 | 8 | 3 |
| A3 | 300 | 14 | 16 | 7 |
| A4 | 275 | 17 | 10 | 4 |
- The first column contains alternative names (e.g., A1, A2, etc.).
- From the second column onwards, numeric values for each criterion are provided.
#### **Output File Format:**
The output file will include the input data along with two additional columns:
| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 | Topsis Score | Rank |
|--------------|-------------|-------------|-------------|-------------|--------------|------|
| A1 | 250 | 16 | 12 | 5 | 0.65 | 2 |
| A2 | 200 | 18 | 8 | 3 | 0.45 | 4 |
| A3 | 300 | 14 | 16 | 7 | 0.78 | 1 |
| A4 | 275 | 17 | 10 | 4 | 0.52 | 3 |
---
### **Python Script Usage**
You can also import and use the package in your Python scripts:
```python
from topsis_vansh_102203021 import topsis
topsis(
input_file="data.csv",
weights="1,1,2,3",
impacts="+,+,-,+",
output_file="result.csv"
)
```
---
## Validation and Error Handling
The package includes robust error handling to ensure correct inputs:
1. **File Not Found:**
- If the input file does not exist, an appropriate error message is shown.
2. **Invalid Parameters:**
- The number of weights, impacts, and criteria must match.
3. **Non-Numeric Values:**
- From the second column onwards, only numeric values are allowed.
4. **Invalid Impacts:**
- Impacts must be either `+` or `-`.
5. **Minimum Column Requirement:**
- The input file must have at least three columns.
---
## Example Files
You can test the package using the following example files:
### Input File (`data.csv`):
| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 |
|--------------|-------------|-------------|-------------|-------------|
| A1 | 250 | 16 | 12 | 5 |
| A2 | 200 | 18 | 8 | 3 |
| A3 | 300 | 14 | 16 | 7 |
| A4 | 275 | 17 | 10 | 4 |
### Output File (`result.csv`):
| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 | Topsis Score | Rank |
|--------------|-------------|-------------|-------------|-------------|--------------|------|
| A1 | 250 | 16 | 12 | 5 | 0.65 | 2 |
| A2 | 200 | 18 | 8 | 3 | 0.45 | 4 |
| A3 | 300 | 14 | 16 | 7 | 0.78 | 1 |
| A4 | 275 | 17 | 10 | 4 | 0.52 | 3 |
---
## Author
Developed by **Vansh Kansal (Roll Number: 102203021)**.
For any questions or feedback, please contact **vanshkansal5@example.com**.
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"description": "# Topsis-Vansh-102203021\r\n\r\nA Python package to implement the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method for multi-criteria decision-making problems.\r\n\r\n---\r\n\r\n## Features\r\n\r\n- Rank alternatives based on multiple criteria.\r\n- Handle positive and negative impacts of criteria.\r\n- Simple to use with CSV input/output.\r\n- Fully customizable weights and impacts.\r\n\r\n---\r\n\r\n## Installation\r\n\r\nInstall the package directly from PyPI:\r\n\r\n```bash\r\npip install Topsis-Vansh-102203021\r\n```\r\n\r\n---\r\n\r\n## How to Use\r\n\r\nThe package can be used through the command line or imported into a Python script.\r\n\r\n### **Command-Line Usage**\r\n\r\nThe basic syntax for using the package via the command line:\r\n\r\n```bash\r\npython -m topsis <input_file> <weights> <impacts> <output_file>\r\n```\r\n\r\n#### **Parameters:**\r\n- `input_file`: CSV file containing the decision matrix.\r\n- `weights`: Comma-separated values representing the importance of each criterion (e.g., `1,1,2,3`).\r\n- `impacts`: Comma-separated values representing the impact of each criterion (`+` for positive, `-` for negative).\r\n- `output_file`: Name of the CSV file where the results will be saved.\r\n\r\n#### **Example:**\r\n\r\n```bash\r\npython -m topsis data.csv \"1,1,2,3\" \"+,+,-,+\" result.csv\r\n```\r\n\r\n#### **Input File Format:**\r\n\r\nThe input file must be a CSV file with the following structure:\r\n\r\n| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 |\r\n|--------------|-------------|-------------|-------------|-------------|\r\n| A1 | 250 | 16 | 12 | 5 |\r\n| A2 | 200 | 18 | 8 | 3 |\r\n| A3 | 300 | 14 | 16 | 7 |\r\n| A4 | 275 | 17 | 10 | 4 |\r\n\r\n- The first column contains alternative names (e.g., A1, A2, etc.).\r\n- From the second column onwards, numeric values for each criterion are provided.\r\n\r\n#### **Output File Format:**\r\n\r\nThe output file will include the input data along with two additional columns:\r\n\r\n| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 | Topsis Score | Rank |\r\n|--------------|-------------|-------------|-------------|-------------|--------------|------|\r\n| A1 | 250 | 16 | 12 | 5 | 0.65 | 2 |\r\n| A2 | 200 | 18 | 8 | 3 | 0.45 | 4 |\r\n| A3 | 300 | 14 | 16 | 7 | 0.78 | 1 |\r\n| A4 | 275 | 17 | 10 | 4 | 0.52 | 3 |\r\n\r\n---\r\n\r\n### **Python Script Usage**\r\n\r\nYou can also import and use the package in your Python scripts:\r\n\r\n```python\r\nfrom topsis_vansh_102203021 import topsis\r\n\r\ntopsis(\r\n input_file=\"data.csv\",\r\n weights=\"1,1,2,3\",\r\n impacts=\"+,+,-,+\",\r\n output_file=\"result.csv\"\r\n)\r\n```\r\n\r\n---\r\n\r\n## Validation and Error Handling\r\n\r\nThe package includes robust error handling to ensure correct inputs:\r\n\r\n1. **File Not Found:**\r\n - If the input file does not exist, an appropriate error message is shown.\r\n\r\n2. **Invalid Parameters:**\r\n - The number of weights, impacts, and criteria must match.\r\n\r\n3. **Non-Numeric Values:**\r\n - From the second column onwards, only numeric values are allowed.\r\n\r\n4. **Invalid Impacts:**\r\n - Impacts must be either `+` or `-`.\r\n\r\n5. **Minimum Column Requirement:**\r\n - The input file must have at least three columns.\r\n\r\n---\r\n\r\n## Example Files\r\n\r\nYou can test the package using the following example files:\r\n\r\n### Input File (`data.csv`):\r\n\r\n| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 |\r\n|--------------|-------------|-------------|-------------|-------------|\r\n| A1 | 250 | 16 | 12 | 5 |\r\n| A2 | 200 | 18 | 8 | 3 |\r\n| A3 | 300 | 14 | 16 | 7 |\r\n| A4 | 275 | 17 | 10 | 4 |\r\n\r\n### Output File (`result.csv`):\r\n\r\n| Alternatives | Criterion 1 | Criterion 2 | Criterion 3 | Criterion 4 | Topsis Score | Rank |\r\n|--------------|-------------|-------------|-------------|-------------|--------------|------|\r\n| A1 | 250 | 16 | 12 | 5 | 0.65 | 2 |\r\n| A2 | 200 | 18 | 8 | 3 | 0.45 | 4 |\r\n| A3 | 300 | 14 | 16 | 7 | 0.78 | 1 |\r\n| A4 | 275 | 17 | 10 | 4 | 0.52 | 3 |\r\n\r\n---\r\n\r\n## Author\r\n\r\nDeveloped by **Vansh Kansal (Roll Number: 102203021)**.\r\n\r\nFor any questions or feedback, please contact **vanshkansal5@example.com**.\r\n",
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