semvec/pypi-packages huggingface dataset:
fabric-forked 3.2.2.post2
High level SSH command execution (forked by 'fabric').
License: MIT
Requires Python: >=3.10

<img alt="PyPI - Package Version" src="https://img.shields.io/pypi/v/fabric-forked">
<img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/fabric-forked">
<img alt="PyPI - Fabric Licence" src="https://img.shields.io/pypi/l/fabric">
<img alt="PyPI - FabricForked Licence" src="https://img.shields.io/pypi/l/fabric-forked">

# Welcome to FabricForked!

## Description (FabricForked)

**FabricForked** is a fork of the [Fabric](https://github.com/fabric/fabric) library, which *transplants the existing library functionality to a new typing* and *corrects some elements WITHOUT STRUCTURALLY CHANGING ANYTHING*!

## Description (Fabric)

[Fabric](https://github.com/fabric/fabric) - is a ***high level Python library*** designed to *execute shell commands remotely over SSH*, yielding useful *Python objects* in return. It builds on top of [Invoke](https://pyinvoke.org) (*subprocess command execution and command-line features*) and [Paramiko](https://paramiko.org) (*SSH protocol implementation*), extending their APIs to complement one another and provide additional functionality.

To find out what's new in this version of [Fabric](https://github.com/fabric/fabric), please see [the changelog](https://fabfile.org/changelog.html#%7B%7D).

The project maintainer keeps a [roadmap](https://bitprophet.org/projects#roadmap) on his website.

## Usage

The [Fabric](https://github.com/fabric/fabric) **methods have not changed** in any way, the only thing you will have to do is **redefine the imports** on **FabricForked**:
```python
import os

password = os.environ.get('FABRIC_FORKED_SSH_PASSWORD', None)

import fabric_forked as fabric
from fabric_forked import Connection, Result


with Connection('localhost', port=22, user='fabricforked', connect_kwargs={'password': password}) as connection:
    result = connection.run()
    if result is not None:
        ...
```
pyhafas 0.6.1
Python client for HAFAS public transport APIs
License: MIT

# pyHaFAS
**A python client for HaFAS public transport APIs**.

[![](https://img.shields.io/pypi/v/pyhafas.svg)](https://pypi.python.org/pypi/pyhafas)
[![](https://readthedocs.org/projects/pyhafas/badge/?version=latest)](https://pyhafas.readthedocs.io/)
[![](https://api.travis-ci.com/n0emis/pyhafas.svg?branch=main)](https://travis-ci.com/github/n0emis/pyhafas)
[![#pyhafas on matrix.org](https://img.shields.io/matrix/pyhafas:matrix.org?logo=matrix&server_fqdn=matrix.org)](https://riot.im/app/#/room/#pyhafas:matrix.org)

## Installation
You only need to install the pyhafas package, for example using pip:

```bash
$ pip install pyhafas
```

That’s it!

## Development setup
For development is **recommended** to use a ``venv``.

```bash
$ python3 -m venv .venv
$ source .venv/bin/activate
$ python setup.py develop
```

## Background
There's [a company called HaCon](https://hacon.de) that sells [a public transport management system called HAFAS](https://de.wikipedia.org/wiki/HAFAS). It is [used by companies all over Europe](https://gist.github.com/derhuerst/2b7ed83bfa5f115125a5) to serve routing and departure information for apps. All those endpoints are similar, with the same terms and API routes, but have slightly different options, filters and sets of enabled features.

## Related
- [`hafas-client`](https://github.com/public-transport/hafas-client) – JavaScript client for the HAFAS API.
- [`public-transport-enabler`](https://github.com/schildbach/public-transport-enabler) – Unleash public transport data in your Java project.
- [*Friendly Public Transport Format*](https://github.com/public-transport/friendly-public-transport-format#friendly-public-transport-format-fptf) – A format for APIs, libraries and datasets containing and working with public transport data.
- [`db-hafas`](https://github.com/derhuerst/db-hafas#db-hafas) – JavaScript client for the DB HAFAS API.

## Contributing
If you **have a question**, **found a bug** or want to **propose a feature**, have a look at [the issues page](https://github.com/n0emis/pyhafas/issues).
102217053-topsis 1.0.4
This is a topsis package
License: MIT
Keywords: topsis

# Project Description

## TOPSIS PACKAGE Mitul Agarwal - 102217053

**Roll Number:** 102217053  
**Subgroup:** 3Q23

The program takes a CSV file containing our data to be ranked, weights and impacts in the form of "+" or "-", separated by commas as inputs and then outputs a resultant CSV file with two additional columns of performance score and ranks.

---

## What is TOPSIS

TOPSIS, Technique of Order Preference Similarity to the Ideal Solution, is a multi-criteria decision analysis method (MCDA).  
It chooses the alternative of the shortest Euclidean distance from the ideal solution and the greatest distance from the negative ideal solution.

---

## Installation

### How to install the TOPSIS package

Using pip install:
```bash
pip install 102217053-topsis


The output will then be saved in a newly created CSV file whose name will be provided in the command line by the user.

## Input File [input.csv]:
Topsis mathematical operations to be performed on the input file which contains a dataset having different fields.

## Weights ["1,1,1"]:
The weights assigned to the different parameters in the dataset should be passed in the argument, separated by commas.

## Impacts ["+,+,-"]:
The impacts are passed to consider which parameters have a positive impact on the decision and which ones have a negative impact. Only `+` and `-` values should be passed and should be separated with `,` only.

## Output File [output.csv]:
This argument is used to pass the path of the result file where we want the rank and performance score to be stored.