semvec/pypi-packages huggingface dataset:
ab-testing-kit 0.1.5
Useful functions for A/B testing and data exploration
Requires Python: >=3.10

# A-B_testing_kit

ab-testing-kit is a Python package designed to facilitate A/B testing for data analysis. It provides utilities to perform statistical tests to compare two groups and determine if there are significant differences between them.

## Features
- Normality Test: Check if the data in both test and control groups follow a normal distribution using the Shapiro-Wilk test.
- Variance Equality Test: Assess if the variances between two groups are equal using Leveneâ€™s test.
- A/B Testing: Perform A/B testing using Studentâ€™s T-test, Welchâ€™s T-test, or Mann-Whitney U test based on the data characteristics.

## Installation
You can install ab-testing-kit from PyPI using pip:

`pip install ab-testing-kit`

## Usage
Here's a quick guide on how to use ab-testing-kit for performing A/B testing.

### Importing the Package

`from ab_testing_kit import ab_test`


### Sample data
test_group = pd.DataFrame({
    'metric': [2.5, 3.6, 3.8, 2.9, 3.4]
})

control_group = pd.DataFrame({
    'metric': [3.2, 3.3, 2.8, 3.0, 3.1]
})

### Perform A/B testing
`result = ab_test(test_group, control_group, column='metric', alpha=0.05, center='mean')

print("Statistic:", result['statistic'])
print("P-value:", result['pvalue'])`

#### Functions
_normality_test(test, control, column, alpha)
Tests if the data in both test and control groups are normally distributed.
triangle-calculations-yes 0.0.5
Triangle calculations
Requires Python: >=3.6

# 三角形计算库triangular calculation library
可以用它计算面积，周长，四心，费马点，拿破仑点

It can be used to calculate area, perimeter, four hearts, Fermat points, Napoleon points

其中费马点是用退火算法逼近

where the Fermat point is approximated by the annealing algorithm
WaterProperties 0.0.4
Package for calculating the properties of water and steam
Requires Python: >=3.8

WaterProperties. ML Automation of construction
===============

Introduction
---------------

This library is a collection of functions for calculating various thermodynamic properties of water and steam. The library is based on the international formulation IAPWS (International Association for the Properties of Water and Steam) and allows for the calculation of properties of water and steam over a wide range of temperatures and pressures.

![SchemeWork.png](SchemeWork.png)

The module also is based on the following article:\
[Library of functions for calculating the properties of water and steam](https://habr.com/ru/articles/712656/)\
Which is written in the Visual Basic programming language.

Quick Guide
---------------

Install library, use the `pip install WaterProperties` construct.\
Using the library is as simple and convenient as possible:

First, import everything or needed functions from the library (use the `from WaterProperties import *` construct).\
Second, you can use any function from the library (use the `WaterProperties.Any_Function` construct).

### Example Usage

```python
import WaterProperties

t = 25  # temperature in degrees Celsius
p = 101325  # pressure in Pascals

# calculate the density of water
density = WaterProperties.Density(t, p)
print("Density of water:", density, "kg/m^3")

# calculate the specific entropy of water
entropy = WaterProperties.Specific_Entropy(t, p)
print("Specific entropy of water:", entropy, "J/kg·K")
```

### Functions

The purpose of each of the functions is contained directly in the name.\
The library includes the following functions:

* `Region(t, p)`
* `Density3(t, p)`
* `Helmholtz_Energy(t, ro)`
* `Pressure3(t, ro)`
* `Specific_Energy3(t, ro)`
* `Specific_Entropy3(t, ro)`
* `Specific_Enthalpy3(t, ro)`
* `Heat_Isobary3(t, ro)`
* `Heat_Isochorny3(t, ro)`
* `Sound_Speed3(t, ro)`
* `Gibbs_Energy(t, p)`
* `Specific_Volume(t, p)`
* `Density(t, p)`
* `Specific_Energy(t, p)`
* `Specific_Entropy(t, p)`
* `Specific_Enthalpy(t, p)`
* `Heat_Capacity_Isobaric(t, p)`
* `Heat_Capacity_Isochoric(t, p)`
* `Speed_Sound(t, p)`
* `Saturation_Temperature(p)`
* `Saturation_Pressure(t)`
* `Border_Temperature(p)`
* `Border_Pressure(t)`
* `Viscosity(t, p)`
* `Density_MI(t, p)`
* `Specific_Enthalpy_MI(t, p)`
* `JF(t, p, Trigger, reg)`

References
--------------

* [Library of functions for calculating the properties of water and steam](https://habr.com/ru/articles/712656/)
* [IAPWS](http://www.iapws.org/)
* [IAPWS Documentation](http://www.iapws.org/relguide/IAPWS-95.html)

#### Mikhail and Lev's DevTeam
sc-scraper 0.1.0
Scraper for Soundcloud
Requires Python: >=3.6

# Soundcloud Scraper
This tool is meant to get metadata from tracks.
Currently, it is only possible to get data from a specific Track.

## What Data?
The Default gets you the cover-art as jpg and the description as txt file.
With the --json flag you can also get following as json.

Instead of downloading files, links will be saved!
```
title: Required[str]
cover_art: Required[str]
genre: Required[str]
buy_link: str
description: Required[list[str]]
```
FederatedCryptix 1.0.0
FederatedCryptix is an innovative and modular framework designed for federated learning with a strong focus on cryptographic security.
Requires Python: >=3.6
Keywords: federated learning, machine learning, deep learning, active learning, encryption, homomorphic encryption, FederatedCryptix

# FederatedCryptix

## Overview

This repository contains a federated learning framework that enables collaborative training of machine learning models across multiple devices while preserving data privacy.

## Folder Structure

- **config/**: Configuration files for models and training parameters.
- **encryption/**: Contains encryption and decryption logic using TenSEAL.
- **models/**: Model implementations for TensorFlow and PyTorch.
- **communication/**: Manages WebSocket communication.
- **server/**: Central server implementation.
- **clients/**: Client device implementation.
- **utils/**: Utility functions and decorators.
- **logs/**: Log files for server and clients.
- **main_server.py**: Entry point to start the central server.
- **main_client.py**: Entry point to start a client device.

## Getting Started

### Central Server

1. Install dependencies:
   ```sh
   pip install -r requirements.txt
   ```