semvec/pypi-packages huggingface dataset:
topsis102203883 0.1
a package to calculate topsis

# topsis python package
a python package to choose the best alternative from a finite set of decision alternatives using TOPSIS.

## overview
the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) library provides an implementation of the TOPSIS decision-making method. this technique is used to rank alternatives based on multiple criteria by comparing their distance from an ideal best and an ideal worst solution.

## features
<ul>
  <li>normalize decision matrices</li>
  <li>apply weights and impacts to criteria</li>
  <li>calculate performance scores and rankings</li>
</ul>

## usage
```python 102203883.py <input_file> <weights> <impacts>```
py-presencedb 2.0.3
API wrapper for the presencedb (undocumented) api
Requires Python: >=3.13

# py-presencedb

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)

Python API wrapper for the <https://presencedb.com> API

## Installation

**Python 3.11 or higher is required**

Install The PyPi Version:

```sh
py -3 -m pip install -U presencedb
```

You may also install the development version:

```sh
pip install git+https://github.com/xFGhoul/py-presencedb.git
```

## Usage

Quick Example:

```py
import asyncio

from presencedb import Client

client = Client()


async def get_user(id):
    user = await client.get_user(id, format=True)
    print(user.current_activity)
    print(user.stats.top_activities)
    print(user.stats.total_duration)


loop = asyncio.new_event_loop()
loop.run_until_complete(get_user(1234))
```

You can find more examples in the [examples](https://github.com/xFGhoul/py-presencedb/blob/dev/examples/) directory.

## Files and Explanations

`├──`[`.github`](https://github.com/xFGhoul/py-presencedb/blob/dev/.github) — GitHub configuration including CI/CD workflows<br>
`├──`[`docs`](https://github.com/xFGhoul/py-presencedb/blob/dev/docs) — Developer Documentation<br>
`├──`[`tests`](https://github.com/xFGhoul/py-presencedb/blob/dev/tests) — Tests<br>
`├──`[`examples`](https://github.com/xFGhoul/py-presencedb/blob/dev/examples) — Examples Showing How To Use The Wrapper<br>
`├──`[`presencedb`](https://github.com/xFGhoul/py-presencedb/blob/dev/pyprotector) — Source Code Of py-presencedb<br>

> Made With ❤️ By `ghoul#1337`
topsis-Akash 0.0.1
A Python package to implement the TOPSIS method for decision making.

# TOPSIS Akash Package

## Overview

The **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method is a multi-criteria decision-making tool. This Python package allows you to implement the TOPSIS method for ranking and selecting alternatives based on multiple criteria.

## How to Use

Run the program through command line as:
Usages: python <program.py> <InputDataFile> <Weights> <Impacts> <ResultFileName>
Example: python 101556.py 101556-data.csv “1,1,1,2” “+,+,-,+” 101556-result.csv


## Features

- Input data validation
- Weighted normalization of the decision matrix
- Calculation of ideal best and worst solutions
- Ranking alternatives based on their similarity to the ideal solution
- Supports command-line execution

---

## Installation

Install the package using `pip`:

```bash
pip install topsis-akash
Topsis-YatinJindal-102203418 0.1.0
A Python package for TOPSIS decision-making method
Requires Python: >=3.6

# **Topsis Package**

This Python package implements the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method for multi-criteria decision-making problems. It helps in ranking and selecting from a set of alternatives based on weights and impacts of the given criteria.

---

## **What is TOPSIS?**
TOPSIS is a multi-criteria decision-making (MCDM) method. It ranks alternatives based on their similarity to the ideal solution (highest value) and their distance from the negative ideal solution (lowest value). The method is widely used for decision analysis across various domains.

---

## **Features**
- Computes TOPSIS scores and rankings for alternatives.
- Accepts custom weights and impacts for criteria.
- Supports command-line execution and integration into Python programs.
- Outputs results as a CSV file with scores and ranks.

---

## **Installation**
To install the package, use the following command:

```bash
pip install topsis_package