semvec/pypi-packages huggingface dataset:
pyp 3.0.9
Python Power at the Prompt
Requires Python: >=3.0

![pyp logo](https://opensource.imageworks.com/images/large/pyp.jpg)

# pyp
The Pyed Piper: Python Power At the Prompt

This is the original pyp developed at Sony Pictures Imageworks that effectively replaces awk, sed, and other legacy command line tools with intuitive python syntax.

Please check out all of our [Documentation](https://thepyedpiper.github.io/pyp/)
zipcode-sv 1.1.4
A package to get zipcodes from El Salvador departments


# Zip codes El Salvador
This Python package scrapes [this web](https://www.listasal.info/articulos/codigo-postal-el-salvador.shtml) to get zip codes by municipality. It uses Requests with BeautifulSoup to extract that information, which is returned as a dict or JSON.

## Install 🛠️

This package is in **PIP**, so you can install it as a dependency:

```python
pip install zipcode-sv
```
## How to use 🪐

```python
from zipcode.department import Department, Endpoint
```

You have to import `Department`, which is the main class for scraping the zip codes. `Endpoint` is an Enum with El Salvador's departments to select from which one you want to get their municipalities with their zip codes.

```python
# returns endpoint to extract data in web source
my_department = Endpoint.san_salvador.value 
# scrapes web source to get municipalities with its zip codes     
san_salvador_zipcodes = Department(my_department)
# returs a dict with municipalities and its zip codes
san_salvador_zipcodes.zip_codes                  
```

You must expect a dictionary like this.

```python
{ "Aguilares":"01122",
	"Apopa":"01123",
	"Ayutuxtepeque":"01121",
	"Delgado":"01118",
	"Cuscatancingo":"01119",
	"El Paisnal":"01124",
	"Guazapa":"01125",
	"Ilopango":"01117",
	"Mejicanos":"01120",
	"Nejapa":"01126",
	"Panchimalco":"01127",
	"Rosario de Mora":"01128",
	"San Marcos":"01115",
	"San Martín":"01129",
	"San Salvador":"01101",
	"Santiago Texacuangos":"01130",
	"Santo Tomás":"01131",
	"Soyapango":"01116",
	"Tonacatepeque":"01132",
	" ":" ",
	"Summary":"San Salvador es un departamento fundado en 1525 ubicado en la Zona Central de El Salvador. Posee 3 distritos y 19 municipios."
}
```
webhookbin 1.0.1
Python library for webhookbin.net
Requires Python: >=3.7

# webhookbin-library
Python library for https://www.webhookbin.net

Install with pip 
```
pip install webhookbin
```

Examples:
```py
import webhookbin

print(webhookbin.makebin().text)

print(webhookbin.post({"data": "here"}).text)

print(webhookbin.get().text)

print(webhookbin.makebin("both").text)

print(webhookbin.makebin("post").text)

print(webhookbin.makebin("get").text)

print(webhookbin.post({"data": "here"},headers={"Customheader": "Something"}).text)

headers = {"Customheader": "Something"}

print(webhookbin.post({"data": "here"},headers=headers,token="DBwIfrB_9BDycs0a4rm0YVRrgsPPpmS2_Vl11ElKpIM").text)

print(webhookbin.get(delete=False).text)

print(webhookbin.get(orderby="acending").text)

print(webhookbin.get(token="DBwIfrB_9BDycs0a4rm0YVRrgsPPpmS2_Vl11ElKpIM").text)

print(webhookbin.patch().text)
```
aio4 0.2.9
Scrapping/Automating tools, userSwitching, anti-bot detection and more...

# scrapper-boilerplate


Scrapping functions and for making easy for further scrapping

## instalation

### (Optional) install enviroment

make sure that you have python installed

then install:

```python
pip install virtualenv
```

then install the enviroment and activate:

```python
python -m venv venv
.\venv\scripts\activate
```

### Install the dependêncies:

Install chromedriver [click here](https://chromedriver.chromium.org/downloads), and get the path location.

Create .env file with:

- chromedriver location
- token of telegram bot (if you use telegram function)

Example provided in ".env.example"

install the packages:

```python
pip install -r requirements.txt
```
and activate:
 
```python
python index.py
```

### setup enviroment

create ".env" file with following lines:

```env
CHROMEDRIVER_PATH="Insert your chromedriver path"
TELEGRAM_TOKEN="Insert your telegram token..."
```

## Usage 

```python
from time import sleep
from utils.setup import setSelenium
import os

ROOT_DIR = os.path.dirname(os.path.abspath(__file__))

def main():
    # import selenium initialization and browser it
    driver = setSelenium()
    driver.get('https://www.google.com')
    sleep(10)
    driver.quit()

if __name__ == "__main__":
    main()

```
pycollection 1.0.6
Collection iterator over classes
Keywords: python,collection,laravel,iterator,pycollection

# pycollection

pycollection is an amazing library that allows you to iterate through a list, but it returns a transformed item. It has a lot of methods to interact with the collection. It works similar than laravel collections.

## Instalation

`pip install pycollection`

## Basic usage
    
    from pycollection import collection

    class NumberCollection(Collection):

        def item(self, item):
            return Number(item)


    class Number:

        def __init__(self, item):
            self._item = item

        def value(self):
            return self._item
        
        def squared(self):
            return self._item * self._item


    numbers = NumberCollection([1,2,3,4,5])


    for number in numbers:
        print(number.squared())

    # output
    # > 1
    # > 4
    # > 9
    # > 16
    # > 25

As you can see, it allows for an easy-to-read syntax for navigating between lists and their elements, since you can provide new functionality to both.

## Available methods

| methods                        | action                                                    |
|----------------------------| -------------------------------------------------- |
| count()                          | gets the number of total elements in the list  |
| json()                            | jsonifies the list                                     |
| find(callaback: Callable)  | returns the first item that match with the callback |
| where(callback: Callable) | returns a new collection that meets the callback |
| item(element)    | transforms each of the elements of the list when it is iterated over it |
| first()                           | gets the first item of the list                      |
| append(element)             | add a new element to the list                        |
| items()                  | retrieves the collection list |
| random()                      | retrieves a random item from the collection      |
| get(index:int)                | retrieves an element according to the given index |
textdiversity 0.0.29
A family of textual diversity metrics
Requires Python: >=3.8

# TextDiversity
 
## Installation

```
pip install -r requirements.txt
```

Some of the text diversity measures rely on software that must be installed separately. For your particular OS, follow the instructions below:

### Windows

1. Phoneme Diversity
   - Phonemizer
      - Visit: https://github.com/espeak-ng/espeak-ng/releases
      - Install either `espeak-ng-X64.msi` or `espeak-ng-X86.msi` (This project used Release 1.51)
      - Add Phonemizer environement variable ([[reference]](https://github.com/bootphon/phonemizer/issues/44))
         - Navigate: Windows Key > Edit System Environment Variables > Environment Variables
         - Add New Variable:
            - Variable Name: `PHONEMIZER_ESPEAK_LIBRARY`
            - Variable Value: `C:\Program Files\eSpeak NG\libespeak-ng.dll`
2. Syntactical Diversity (non-core functionality)
   - Dependency Parse Tree Visualization
      - `UNKOWN SETUP STEPS`

### Linux

1. Phoneme Diversity
   - Phonemizer
      - `sudo apt-get install espeak-ng`
2. Syntactical Diversity
   - Dependency Parse Tree Visualization (non-core functionality)
      - `sudo apt-get install python3-dev graphviz libgraphviz-dev pkg-config`
wtform-address 0.1.1
Physical address fields (CountrySelectField, StateSelectField) for wtform

# Wtform address fields: CountrySelectField and StateSelectField
Fields that are helpful when dealing with physical addresses such as a
CountrySelectField and a StateSelectField.

## Install
```shell
pip install wtform_address
```

## Usage
```python
from wtforms import Form
from wtform_address import CountrySelectField, StateSelectField

class MyForm(Form):
    country = CountrySelectField(default="US")
    state = StateSelectField(default="US-CA")
```

## Credits
Credits to [@mekza](https://github.com/mekza) for his initial [gist](https://gist.github.com/mekza/516f172278c328468ea0).

## License
[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
yt-stream-recorder 22.2.6
tool for recording youtube streams
Requires Python: >=3.10

# yt_stream_recorder

<img src="https://github.com/gmankab/yt_stream_recorder/raw/main/img/transparent.png">

Script for recording YouTube streams. You only need to run it once, and while it is running it will record all streams on the selected channel

## navigation

- [installation](#installation)
- [installation via terminal](#installation-via-terminal)
- [license](#license)


### installation

[yt_stream_recorder.sh](https://gmankab.github.io/yt_stream_recorder.sh) - for linux  
[yt_stream_recorder.bat](https://gmankab.github.io/yt_stream_recorder.bat) - for windows

just download and run

### installation via terminal

install on linux:  
`curl -sSL gmankab.github.io/yt_stream_recorder.sh | sh`

install on any os:  
`pip install yt_stream_recorder`

launch on any os:  
`python -m yt_stream_recorder`

### license

[gnu gpl 3](https://gnu.org/licenses/gpl-3.0.en.html)
googletable 1.1.3
The module that collects data from the Google table
Requires Python: >=3,<4
Keywords: Google,Table,Google Table,Google Sheets

# ***Получение данных с Google таблиц***
____
### Установка
```cmd
pip install googletable
```
### Импорт и инициализация

```python
from GoogleTable import GoogleTable

tableid = '1iVSut_5LLcXAeecJI73y0EmltL8mwg-9hEHaWP2UOp0'
gid = '0'
encoding = 'utf-8'

GoogleTable(tableid,gid,encoding)
```
### Где найти tableid ?
>tableid - ID таблицы гугл (Под верхними стрелками)
> 
>gid - ID листа таблицы (Над нижними стрелками )

                                           ↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓
    https://docs.google.com/spreadsheets/d/1iVSut_5LLcXAeecJI73y0EmltL8mwg-9hEHaWP2UOp0/edit#gid=0  
                                                                                        ↑↑↑↑↑↑↑↑↑↑


### Примечание
> ## Важно чтобы таблица была открыта для общего доступа!
### Полезные ссылки
>[Страница на GitHub](https://github.com/DaniEruDai/GoogleTable)
> | [Страница на PyPi](https://pypi.org/project/googletable/)
tension 0.2
A Python package for training chaotic Echo State and Spiking RNNs
Requires Python: >=3.7

# tension
The `tension` package is a Python package for building and FORCE training chaotic recurrent neural networks. `tension` is built to integrate seamlessly with TensorFlow/Keras, a widely used software package for training artificial neural networks. 

## Code and documentation
Installation guide, contributing guide, and API reference are available on the [documentation website](https://zhenruiliao.github.io/tension/index.html)

Example notebooks for reproducing the experiments in the associated software report can also be found on the documentation website and in the `examples` folder. These notebooks can be run either in Google Colab or in a local jupyter notebook.

Documentation for TensorFlow/Keras, on which `tension` is based and interoperable with, can be found at the [TensorFlow guide](https://www.tensorflow.org/guide).

## Dependencies
`tension` depends on Python >= 3.7, `tensorflow>=2.5`, `numpy` and `matplotlib`.

## Installation
### Local installation
We recommend installing `tension` into a conda environment
```
conda create -n tension python=3.7
```
followed by
```
conda activate tension
```

#### From GitHub
Clone this repo using
```
git clone https://github.com/zhenruiliao/tension.git
```
Change into the `tension` directory and install using `pip`
```
cd tension/
pip install -e .
```

#### From PyPI
```
pip install tension
```

### Google Colab
To quickly get started with `tension`, the package can also be installed in Google Colab using the following commands
```
!git clone https://github.com/zhenruiliao/tension.git tension
!pip install -e tension
```
The runtime must be restarted for the package to become importable

## Contributing 
Bug reports, feature requests, and pull requests are welcome and encouraged! Use the Issues and Pull requests tabs to open new issues or pull requests. Always be kind and respectful. 

## License
`tension` is provided under the [MIT License](./LICENSE). TensorFlow is provided under the [Apache 2.0 license](https://github.com/tensorflow/tensorflow/blob/master/LICENSE).

## Acknowledgments

Based on work by David Sussillo and Larry Abbott
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2756108/

With thanks to James Priestley for the package name.