semvec/pypi-packages huggingface dataset:
Topsis-Harjot-102017126 1.0.2
A Python package implementing TOPSIS for MCDM
License: MIT
Keywords: python,TOPSIS,MCDM,MCDA,statistics,prescriptive analytics,cli

Project 1


Submitted By: Harjot Singh  
Roll Number :102017126


# What is TOPSIS

Technique for Order Preference by Similarity to Ideal

TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal
solution.

### In Command Prompt
```
>> topsis data.csv "1,1,1,1" "-,+,-,+"
```

## Example

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.

Attribute 	price	storage	camera	looks 
m1	         250	    16	     12	     5
m2	         200	    16  	  8	     4
m3	         300	    32	     16	     3
m4	         275	    32	      8	     3
m5	         225	    16	     16	     1


<br>
Using TOPSIS the rankings are displayed in the form of a table , with the 1st rank offering the best decision, and last rank offering the worst decision making.
algefunc 0.1.0
Demo library
License: MIT

# Algefunc
A small demo library for studying libraries in python

### Installation
```
pip install algefunc
```

### Get started
How to work with a function of first degree with this lib:

```Python
from algefunc import func

# Instantiate a variable
functiontest = func('4x-8')

# Print the variable
print(functiontest)

# Output: 2.0
```
techzapi 1.2.1
Python wrapper for the TechZApi
License: MIT
Keywords: API,TechZApi,TechZAPI,TechZBots,GogoAnime,Anime,AnimeAPI,MkvCinemas,MkvCinemasAPI,Scrapper

## TechZApi

Python wrapper for the TechZApi

- Base Url : api.techzbots.live
- Documentation : [Click Here](https://api.techzbots.live/docs)
- Updates Channel : [TechZBots](https://telegram.me/TechZBots)
- Support Group : [TechZBots Support](https://telegram.me/TechZBots_Support)

### Requirements

- API_KEY : Create your own key, from [here](https://telegram.me/TechZApiBot)
- TechZApi Credits : You will get 10000 Free credits, Need More contact us at [TechZBots Support](https://telegram.me/TechZBots_Support)

### Installation

- Install latest version using
```
$ pip install -U techzapi
```

- Use the above command to update also

### Usage

To get latest releases from gogo anime

```
from techzapi.api import TechZApi

GogoApi = TechZApi.Gogo("DVZTAR")

print(GogoApi.latest())
```
xontrib-jupyter-shell 0.1.0
A shell for the Jupyter kernel.
License: MIT
Requires Python: >=3.7
Keywords: xontrib,xonsh

<p align="center">
Xonsh provides a kernel for Jupyter Notebook and Lab so you can execute
xonsh commands in a notebook cell without any additional magic.
</p>

<p align="center">
If you like the idea click ⭐ on the repo and <a href="https://twitter.com/intent/tweet?text=Nice%20xontrib%20for%20the%20xonsh%20shell!&url=https://github.com/xonsh/xontrib-jupyter-shell" target="_blank">tweet</a>.
</p>


## Installation

To install use [xpip](https://xon.sh/aliases.html#xpip):

```xsh
xpip install xontrib-jupyter-shell
# or: xpip install -U git+https://github.com/xonsh/xontrib-jupyter

xontrib load jupyter
xonfig jupyter-kernel --help  # Options for installing.
xonfig jupyter-kernel --user  # Install kernel spec in user config directory.
```

Check the installation:
```xsh
jupyter kernelspec list
# Available kernels:
#  python3    /opt/homebrew/lib/python3.11/site-packages/ipykernel/resources
#  xonsh      /PATH_TO_ENV_PREFIX/share/jupyter/kernels/xonsh

xontrib load jupyter
xonfig jupyter-kernel
# Installing Jupyter kernel spec:
#  root: None
#  prefix: /PATH_TO_ENV_PREFIX/
#  as user: False

xonfig info
#| jupyter          | True
#| jupyter kernel   | /PATH_TO_ENV_PREFIX/share/jupyter/kernels/xonsh

```

## Usage

### Jupyter

Just run [Jupyter Notebook or JupyterLab](https://jupyter.org/) and choose xonsh:

```xsh
jupyter notebook
jupyter lab
```

### Euporie

[Euporie](https://github.com/joouha/euporie) is a terminal based interactive computing environment.

```xsh
euporie-notebook
# Change the kernel to xonsh
```

## Releasing your package 

1. Bump the version of the package.
2. The release notes are automatically generated as a draft release after each PR.
3. Create a GitHub release. 
4. Publish with `poetry publish --build` or `twine`.

## Credits

This package was created with [xontrib cookiecutter template](https://github.com/xonsh/xontrib-cookiecutter).
tensorflow-extra 1.0.2
Tensorflow Extra Utilities. https://github.com/awsaf49/tensorflow_extra
License: MIT
Requires Python: >=3.6
Keywords: tensorflow extra utilities

# Tensorflow Extra
> Extra Utilities for Tensorflow

# Installation
```shell
pip install tensorflow-extra
```

# Activations
## SmeLU: Smooth ReLU
```py
import tensorflow as tf
import tensorflow_extra as tfe

a = tf.constant([-2.5, -1.0, 0.5, 1.0, 2.5])
b = tfe.activations.smelu(a)  # array([0., 0.04166667, 0.6666667 , 1.0416666 , 2.5])
```
<img src="images/smelu.png" width=500>