semvec/pypi-packages huggingface dataset:
TOPSIS-VK-102003295 1.0.0
A Python package implementing TOPSIS technique used to solve the multi criteria decision making problems.
License: MIT

# TOPSIS-Python

**Assignment 1 : UCS654 Predictive Analysis using Statistics**

**Author - Vardaan Khosla(102003295), TIET Patiala**

## What is TOPSIS

**T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal
**S**olution (TOPSIS) originated in the 1980s as a multi-criteria decision
making method. TOPSIS chooses the alternative of shortest Euclidean distance
from the ideal solution, and greatest distance from the negative-ideal
solution.

<br>

## This is how we can use the developed package:

Topsis-VardaanKhosla-102003295 package can be run as follows:

### In the Command Prompt type:

```
>> topsis input_data.csv "0.25,0.25,0.25,0.25" "+,+,-,+" output_data.csv
```

## Sample dataset

The decision matrix (`a`) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R<sup>2</sup>, Root Mean Squared Error, Correlation, and many more.The number of entries in the impacts and weights column must be equal to the number of columns starting from the 2nd column in the input dataset. For example, in this case there are 4 columns consisting of parameters which affect the decision making procedure. Each column will have an according weight and impact associated to it.

| Model | Correlation | R<sup>2</sup> | RMSE | Accuracy |
| ----- | ----------- | ------------- | ---- | -------- |
| M1    | 0.79        | 0.62          | 1.25 | 60.89    |
| M2    | 0.66        | 0.44          | 2.89 | 63.07    |
| M3    | 0.56        | 0.31          | 1.57 | 62.87    |
| M4    | 0.82        | 0.67          | 2.68 | 70.19    |
| M5    | 0.75        | 0.56          | 1.3  | 80.39    |

Weights (`w`) is not already normalised will be normalised later in the code.

Information of benefit positive(+) or negative(-) impact criteria should be provided in `I`.

<br>

## Output

The output will consist of the original csv file along with two additional columns Topsis Score and Rank.

```
Model  Topsis Score    Rank
-----  ------------    ----
  1    0.77221          2
  2    0.225599         5
  3    0.438897         4
  4    0.523878         3
  5    0.811389         1 
```

<br>
checkedid 0.4.0
CheckedID Python API client
License: MIT
Requires Python: >=3.7,<4.0

# CheckedID Python API client

[![PyPI](https://img.shields.io/pypi/v/checkedid.svg)][pypi_]
[![Status](https://img.shields.io/pypi/status/checkedid.svg)][status]
[![Python Version](https://img.shields.io/pypi/pyversions/checkedid)][python version]
[![License](https://img.shields.io/pypi/l/checkedid)][license]

[![Read the documentation at https://checkedid.readthedocs.io/](https://img.shields.io/readthedocs/checkedid-api-python-client/latest.svg?label=Read%20the%20Docs)][read the docs]
[![Tests](https://github.com/foarsitter/checkedid-api-python-client/workflows/Tests/badge.svg)][tests]
[![Codecov](https://codecov.io/gh/foarsitter/checkedid-api-python-client/branch/main/graph/badge.svg)][codecov]

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)][pre-commit]
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)][black]

[pypi_]: https://pypi.org/project/checkedid/
[status]: https://pypi.org/project/checkedid/
[python version]: https://pypi.org/project/checkedid
[read the docs]: https://checkedid.readthedocs.io/
[tests]: https://github.com/foarsitter/checkedid-api-python-client/actions?workflow=Tests
[codecov]: https://app.codecov.io/gh/foarsitter/checkedid-api-python-client
[pre-commit]: https://github.com/pre-commit/pre-commit
[black]: https://github.com/psf/black

## Features

- Typed API client for api.checkedid.eu

## Requirements

- Build with Pydantic and httpx, does currently not support async.

## Installation

You can install _CheckedID Python API client_ via [pip] from [PyPI]:

```console
$ pip install checkedid
```

## Usage

```py
from checkedid import errors, models, Client

try:
    client = Client('1001')
    dossier: models.ReportResponse = client.dossier('123456789')
except errors.CheckedIDNotFoundError as e:
    print("Dossier does not exists")
```

## Contributing

Contributions are very welcome.
To learn more, see the [Contributor Guide].

## License

Distributed under the terms of the [MIT license][license],
_CheckedID Python API client_ is free and open source software.

## Issues

If you encounter any problems,
please [file an issue] along with a detailed description.

## Credits

This project was generated from [@cjolowicz]'s [Hypermodern Python Cookiecutter] template.

[@cjolowicz]: https://github.com/cjolowicz
[pypi]: https://pypi.org/
[hypermodern python cookiecutter]: https://github.com/cjolowicz/cookiecutter-hypermodern-python
[file an issue]: https://github.com/foarsitter/checkedid-api-python-client/issues
[pip]: https://pip.pypa.io/

<!-- github-only -->

[license]: https://github.com/foarsitter/checkedid-api-python-client/blob/main/LICENSE
[contributor guide]: https://github.com/foarsitter/checkedid-api-python-client/blob/main/CONTRIBUTING.md
hmirls 0.1.0
Library for Schatten-p norm minimization via iteratively reweighted least squares
License: MIT
Requires Python: >=3.8,<3.12

# Harmonic Mean Iteratively Reweighted Least Squares for Low-Rank Matrix Recovery

This repository contains python code to implement a basic variant of the Harmonic Mean Iteratively Reweighted Least Squares (HM-IRLS) algorithm for low-rank matrix recovery, in particular for the low-rank matrix completion problem, described in the paper:

> C. Kümmerle, J. Sigl.
> "Harmonic Mean Iteratively Reweighted Least Squares for Low-Rank Matrix Recovery", Journal of Machine Learning Research (JMLR) volume 19, number 47, pages 1-49, 2018.
> Available online: https://jmlr.org/papers/volume19/17-244/17-244.pdf

## Version history
* Version 0.0.1, 10/25/2020

## Author
Kristof Schröder

## Documentation
> https://hmirls.readthedocs.io/en/latest/
Octra 1.1.4
Full-featured Telegram client library for Python 3
License: MIT
Requires Python: >=3.5
Keywords: telegram api chat client library messaging mtproto

Octra
========
.. epigraph::

  ⭐️ Thanks **everyone** who has starred the project, it means a lot!

|logo| **Octra** is an asyncio_ **Python 3**
MTProto_ library to interact with Telegram_'s API
as a user or through a bot account (bot API alternative).

.. important::

    If you have code using Octra before its 1.0 version, you must
    read `Compatibility and Convenience`_ to learn how to migrate.

What is this?
-------------

Telegram is a popular messaging application. This library is meant
to make it easy for you to write Python programs that can interact
with Telegram. Think of it as a wrapper that has already done the
heavy job for you, so you can focus on developing an application.


Installing
----------

.. code-block:: sh

  pip3 install Octra


Creating a client
-----------------

.. code-block:: python

    from Octra import TelegramClient, events, sync

    # These example values won't work. You must get your own api_id and
    # api_hash from https://my.telegram.org, under API Development.
    api_id = 12345
    api_hash = '0123456789abcdef0123456789abcdef'

    client = TelegramClient('session_name', api_id, api_hash)
    client.start()


Doing stuff
-----------

.. code-block:: python

    print(client.get_me().stringify())

    client.send_message('username', 'Hello! Talking to you from Octra')
    client.send_file('username', '/home/myself/Pictures/holidays.jpg')

    client.download_profile_photo('me')
    messages = client.get_messages('username')
    messages[0].download_media()

    @client.on(events.NewMessage(pattern='(?i)hi|hello'))
    async def handler(event):
        await event.respond('Hey!')


Next steps
----------

Do you like how Octra looks? Check out `Read The Docs`_ for a more
in-depth explanation, with examples, troubleshooting issues, and more
useful information.

.. _asyncio: https://docs.python.org/3/library/asyncio.html
.. _MTProto: https://core.telegram.org/mtproto
.. _Telegram: https://telegram.org
.. _Compatibility and Convenience: https://docs.Octra.dev/en/stable/misc/compatibility-and-convenience.html
.. _Read The Docs: https://docs.Octra.dev

.. |logo| image:: logo.svg
    :width: 24pt
    :height: 24pt
TrakteerDonate 1.0a1
An easy way to listen for Trakteer donation in Python
License: MIT
Requires Python: >=3.6

<p align="center"><b>⚠️ NOTE: THIS PROJECT IS ONLY FOR EDUCATIONAL PURPOSE!! ⚠️<br>I WONT RESPONSIBLE FOR SOMETHING HAPPEN WHEN USING THIS PROGRAM!!</b></p>

<h1 align="center">Trakteer Donate</h1>
<p align="center">An easy way to listen for Trakteer donation in Python</p>

## Installation
To install this package, you can easily use pip!
```bash
pip install trakteerdonate
```

Or,

```bash
pip install git+https://github.com/then77/trakteerdonate
```

## Package Usage
1. First open your **Trakteer** and go to **Stream Overlay** ([here](https://trakteer.id/manage/stream-settings))
2. On the **Widget URL**, copy the key, and the hash
3. Create a code and import the `Client` function.
```python
from trakteerdonate import Client
client = Client("hash", "streamKey")
# Replace "hash" and "streamKey" with the key you copied before
```
4. Add listener for donation
```python
@client.event
async def on_donation(ws, data):
    print("Received donation:")
    print(f"  - Name: {data.name}")
    print(f"  - Amount: {data.amount}")
    print(f"  - Message: {data.message}")
```
5. Last, add this code **To the bottom of the code** and run!
```python
client.start()
```

The reason it should be placed on the bottom because its a blocking function.

## Example Code
```python
from trakteerdonate import Client

client = Client("hash", "streamKey")

@client.event
async def on_connect(ws):
    print("Connected to Trakteer!")

@client.event
async def on_donation(ws, data):
    print("Received donation:")
    print(f"  - Name: {data.name}")
    print(f"  - Amount: {data.amount}")
    print(f"  - Message: {data.message}")

client.start()
```

## Repository License
This repository and its code is under the MIT License. [Read more here](https://github.com/then77/trakteerdonate/blob/main/LICENSE).
umidcalculator 0.0.1
Basic calculator
License: MIT
Keywords: calculator

Bu juda oddiy calculator kutubxona

from umidcalculator.calculator import add_numb,sub_numb,mult_numb,div_numb
print(add_numb(10,10))


Change Log
==========

0.0.1 (23/01/2023)
-------------------
- Second Release