semvec/pypi-packages huggingface dataset:
pyMysterium 0.0.18
UNOFFICIAL Python bindings for Mysterium Tequila API
Keywords: python,myst,mysterium,requests,python myst,tequila api,mysterium api,mysterium python api


# EarnApp API

A Python binding to interact with Mysterium Tequila API.

## Installation
```BASH
pip install pyMysterium
```
## Usage
### Import the package and initiallise
```python
from pyMysterium import Mysterium
myst = Mysterium()
```
correlacao 0.0.1
Pacote para correlacionar Variáveis e Alvo - Análise de Dados
Requires Python: >=3.8

# correlacao

Description. 
The package correlacao is used to:

	- Plot correlations between variable and target.
	- The methods used are: Spearman e Pearson.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install correlacao

```bash
pip install correlacao
```

## Usage:

	- The module spearman_pearson receive with entry a DataFrame with variables and a Serie as target.
	- Ex: ''' from correlacao import spearman_pearson as sp

              sp.start(DataFrame, Target)  '''
## Author
Nicodemos Freitas

## License
[MIT](https://choosealicense.com/licenses/mit/)
filtermat 1.5.3
This Python library is needed in order to search for Russian mat in text.
Requires Python: >=3.6

<h1 align="center" name="name">Library FilterMat</h1>
<p align="center">
    <em>This library allows you to find the mat in the text.</em>
</p>

<p align="center">
    <a href="https://github.com/qxtony/filtermat/issues">
        <img src="https://img.shields.io/github/issues/qxtony/filtermat" alt="Issues">
    </a>
    <a href="https://pypi.org/project/filtermat/">
        <img src="https://img.shields.io/pypi/v/filtermat?colorB=brightgreen" alt="Package version">
    </a>
    <a href="https://github.com/qxtony/filtermat/blob/main/LICENSE">
        <img src="https://img.shields.io/github/license/qxtony/filtermat.svg" alt="License">
    </a>
</p>

## Installation

Stable version:

```bash
pip install -U filtermat
```
## Quickstart
The first program to search for a mate in a sentence.
```python
from filtermat import check

text = input("Введите предложение: ")

if check(text):
    result = "В тексте есть маты"

else:
    result = "Матов не обнаружено"

print(result)
```


As well as a code that shows exactly which mats are found:
```python
from filtermat import check

text = input("Введите предложение: ")
result = ", ".join(check(text, array=True))

print(f"В тексте найдены маты: {result}")
```
You can also remove some text checks. There are only 4 text transformations: Search for an asterisk in the text; Formation of the word in the initial form, singular, nominative; Translation of transliteration into plain text; Checking with regular expressions.

Examples:
```python
from filtermat import check

text = input("Введите предложение: ")
result = ", ".join(check(text, ignore_replace=True)) # Ignore search for an asterisk in the text.

print(f"В тексте найдены маты: {result}")
```
```python
from filtermat import check

text = input("Введите предложение: ")
result = ", ".join(check(text, ignore_form=True)) # Ignore formation of the word in the initial form, singular, nominative.

print(f"В тексте найдены маты: {result}")
```
```python
from filtermat import check

text = input("Введите предложение: ")
result = ", ".join(check(text, ignore_translate=True)) # Ignore translation of transliteration into plain text.

print(f"В тексте найдены маты: {result}")
```
```python
from filtermat import check

text = input("Введите предложение: ")
result = ", ".join(check(text, regex=False)) # Ignore checking with regular expressions.

print(f"В тексте найдены маты: {result}")
```