semvec/pypi-packages huggingface dataset:
hack4uTerror 0.1.1
Una biblioteca para consultar cursos de hack4u.

# Hack4U Academy Courses Library

Una biblioteca de Python para consultar cursos de la academia Hack4U.

## Cursos disponibles:

- Introducción a Linux [15 horas]
- Personalización de Linux [3 horas]
- Introducción al Hacking [53 horas]

## Instalación

Instala el paquete usando `pip3`:

```python3
pip3 install hack4u
```

## Uso básico

### Listar todos los cursos

```python
from hack4 import list_courses

for course in list_courses():
    print(course)
```

### Obtener un curso por nombre

```python
from hack4u import get_course_by_name

course = get_course_by_name("Introducción a Linux")
print(course)
```

### Calcular la duración total de los cursos

```python3
from hack4.utils import total_duration

print(f"Duración total: {total_duration()} horas")
```
data-pilot-checker 1.6
A package for automating data quality and integrity checks with optional GPU acceleration using cuDF
Requires Python: >=3.11

# DataPilotChecker

Datapilot is a Python package that automates data quality and integrity checks for your dataset. It performs several checks including missing values, duplicate rows, outliers, data type validation, and range validation. The package uses cuDF for GPU acceleration if a compatible GPU is available, and falls back to Dask for parallel processing otherwise.

## Installation

### Basic Installation

You can install the package via pip:

```bash
pip install data_pilot_checker
```

## Installation with GPU Support
To use GPU acceleration with cuDF, you need to set up a compatible environment. Follow these steps:

### Create a conda environment with RAPIDS:

```bash
conda create -n rapids-24.06 -c rapidsai -c conda-forge -c nvidia \
    rapids=24.06 python=3.11 cuda-version=12.2
```
### Activate the conda environment:

```bash
conda activate rapids-24.06
```
### Install DataWhiz in the conda environment:

```bash
pip install data_pilot_checker
```

Check the rapids website for cuDF installation. (https://docs.rapids.ai/install)
analyze-stocks-india 1.0.2
A python package to download historic stock prices from NSE website and process them to find best stock to purchase
Requires Python: >=3.6

Objective
    Library of functions for stock price trend prediction

Python Requirement
    version >= 3.6

Packages requirement
    As mentioned in requirements.txt

Stock Files
    * All the downloaded files are in directory data_files --> raw
    * All the processed data files are in directory data_files --> processed
    * Note: After installation of library 'data_files' folder will not be present, once you start downloading files these will be available at the same location where this library is installed.

Sample Scripts
    Few sample scripts have been created in analyze_stocks_india_sample_scripts folder for ease of understanding.

Library Packages
    * create_plot.py --> to create plots of stock trend and trading volume
    * download_historic_data.py --> to download data files from nse webseite and process them
    * get_stock_moment_from_optionChain.py --> Recomends stocks using option chain data
    * Mean_Reverser_Strategy.py --> Apply Mean Reverser Strategy and recommend stocks
    * news_sentiment_analysis_Indian_Stocks.py --> performs a sentiment analysis on stock based on google news headline from last 7 days

Extra Information for different types of data from NSE website.
	* SYMBOL: Symbol of the listed company.
	* SERIES: Series of the equity. Values are [EQ, BE, BL, BT, GC and IL]
	* OPEN: The opening market price of the equity symbol on the date.
	* HIGH: The highest market price of the equity symbol on the date.
	* LOW: The lowest recorded market price of the equity symbol on the date.
	* CLOSE: The closing recorded price of the equity symbol on the date.
	* LAST: The last traded price of the equity symbol on the date.
	* PREVCLOSE: The previous day closing price of the equity symbol on the date.
	* TOTTRDQTY: Total traded quantity of the equity symbol on the date.
	* TOTTRDVAL: Total traded volume of the equity symbol on the date.
	* TIMESTAMP: Date of record.
	* TOTALTRADES: Total trades executed on the day.
	* ISIN: International Securities Identification Number.
goroutine-py 1.0.9
An Asyncio-based concurrency library for Python.
Requires Python: >=3.7

English | [中文](https://github.com/purplegrapeZz/goroutine-py/blob/master/README-CN.md)

### goroutine-py

🚀 An Asyncio-based concurrency library for Python.

​	Easy concurrency just like goroutine without worry about thread and coroutine in Python.



# Introduction

Withing  ``goroutine.app.go`` you can run a coroutine or a func asynchronously.

Main function ___go___ :

#####  go _(obj: callable, *args, callback: callable = None, lock: bool = False)_

​	___obj:___ Takes both callable coroutinefunction and func as object.

​	___*args:___ Arguments for your obj.

​	___callback:___ Attaches a callable that will be called when the future finishes.



# Getting Started
## Support:

	Python 3.7 / 3.8 / 3.9 / 3.10 / 3.11 / 3.12

## Installation

First you have to install goroutine-py like this:

```
pip install goroutine-py
```

## Quick Tutorial

The primary entity of goroutine-py is ``goroutine.app.go``.
You can simply start using goroutine-py like this:

First, define your tasks:

```
import asyncio
import time
from goroutine.app import go

# A normal func
def task_1(n=2):
    time.sleep(n)
    print('Task_1_done')
    return 'Result_1'
```

```
# A coroutinefunction
async def task_2(n=1):
    await asyncio.sleep(n)
    print('Task_2_done')
    return 'Result_2'
```

```
# Callback func
def callback(result):
    '''
    Parameter "result" is the return from task.
    Use functools.partial() to give arguments if you need more args at the beginning.
    '''
    print('-* callback *-')
    print(result)
```
After you defined all your tasks and callback, you can go like this:

```
go(task_1)
go(task_2)

# The "callback" parameter must be specified separately.
go(task_1, 5, callback = callback)
go(task_2, 3, callback = callback)
print('END')

# Forever runing to show results.
while 1:
    time.sleep(5)
```

Output :

```
>>>
END
Task_2_done
Task_1_done
Task_2_done
-* callback *-
Result_2
Task_1_done
-* callback *-
Result_1
```

# License

This project is licensed under the MIT License - see the `LICENSE` file for details.
netoapi 1.0.1
A Python3 API Client for the Neto (Maropost) Ecommerce platform
Requires Python: >=3.7

# NetoAPI Library
### A Python API client for the <a href="https://www.netohq.com/" target="_blank">Neto</a> (Maropost) Ecommerce platform.
</br>

## Requirements:
* Python 3.7+
* <a href="https://pypi.org/project/requests/">Requests</a>
<br><br>
## To install:
```bash
pip install netoapi
```

## Basic use:
``` python
import netoapi

api = netoapi.NetoAPIClient(
    my_endpoint,
    my_username,
    my_apikey
)
payload = {
    "Filter": {
        "SKU": "LSD",
        "OutputSelector": [
            "Name",
            "RRP"
        ] 
    }
}
response = api.execute_api_call("GetItem", payload)
print(response)
```
``` bash
{
    'Item': [
        {'RRP': '150.00', 'InventoryID': '31673', 'Name': 'Luke Skywalker Doll', 'SKU': 'LSD'}
    ],
    'CurrentTime': '2021-02-06 10:49:40',
    'Ack': 'Success'
}
```

## Method - NetoAPIClient.execute_api_call():
``` python
# Parameters:
action: str """Used in the 'NETOAPI_ACTION' request header"""
payload: dict """Converted to JSON as the request payload"""

# See NETO API documentation for more information on building
# JSON payloads and available 'NETOAPI_ACTION' headers
```

## Custom exceptions:
### Raised if netoapi is imported without the requests library installed:
``` python
netoapi.errors.DependencyNotFoundError
```

### Raised if an error occurs during an API call:
``` python
netoapi.errors.NetoAPIRequestError

# Catch this error to avoid breaking execution
try:
    api.execute_api_call(action, payload)
except NetoAPIRequestError as e:
    # Handle the error
```

## timeout:
### Setting the connection and response timeout property
``` python
# The timeout property will always return a tuple (connection, response)
print(type(api.timeout))
```
``` bash
<class 'tuple'>
```
``` python
# By default the timeout property is set to (5, 5)
# timeout can be set to an integer, a tuple or NoneType

# Set both timeouts to the same value with an integer
api.timeout = 10 # 10 seconds

# Set the timeouts individually with a tuple
api.timeout = (5, 10)

# Set the connection timeout to 5 and wait forever for a response
api.timeout = (5, None)

# Cancel all time limits on connections and requests
api.timeout = None
```

### That's about all there is to it!
</br>

For more info see <a href="https://developers.maropost.com/documentation/engineers/api-documentation" target="_blank">Neto API docs</a>

Written by <a href="https://github.com/dan-hobday" target="_blank">github.com/dan-hobday</a>

### Roadmap:
* -> V1.0.1 - Current release
* -> V1.1.0 - Map API fields to classes. This will make building payloads easier, less error prone and add support for field constraints.
suno-songs 0.6.0
High quality songs generation by suno.ai. Reverse engineered API.

# SunoSongsCreator
About High quality songs generation by https://www.suno.ai/. Reverse engineered API.

## How to
- Login to https://app.suno.ai/ and generate some songs.
- Use `Chrome` or other browsers to inspect the network requests (F12 -> XHR).
- Clone this REPO -> `git clone https://github.com/yihong0618/SunoSongsCreator.git`
- XHR find cookie in this url -> https://clerk.suno.ai/v1/client?_clerk_js_version=4.70.5 
- Copy the cookie.
- You can import the cookie using `export SUNO_COOKIE='<your-suno-cookie>'` or rename `.env.example` to `.env` and fill in `SUNO_COOKIE`.

## Usage

```
python -m suno --prompt 'a big red dream song'
```

or
```
pip install -U suno_songs
```

```python
from suno import SongsGen
i = SongsGen('cookie') # Replace 'cookie'
print(i.get_limit_left())
i.save_songs("a blue cyber dream song", './output')
```

Custom mode

```python
#you can use custom mode
from suno import SongsGen
i = SongsGen('cookie') # Replace 'cookie'
print(i.get_limit_left())
i.save_songs("大江东去，浪淘尽，千古风流人物。故垒西边，人道是、三国周郎赤壁。乱石穿空，惊涛拍岸，卷起千堆雪。江山如画，一时多少豪杰。遥想公瑾当年，小乔初嫁了，雄姿英发。", is_custom=True, title="custom", tags="轻松的R&B, BPM60, 小调, 电吉他、贝斯、键盘和轻鼓, 男性歌手") 
```

Get song library

```python
from suno import SongsGen
i = SongsGen('cookie') # Replace 'cookie'
print(i.get_song_library())
```

## Thanks

- All my 爱发电 sponsors https://afdian.net/a/yihong0618?tab=sponsor
geobizml 0.1.0
A package for geospatial data visualization, plotting, analysis, and machine learning.
Requires Python: >=3.6

# GeoBizML

![PyPI](https://img.shields.io/pypi/v/geobizml)
![License](https://img.shields.io/pypi/l/geobizml)
![Python Versions](https://img.shields.io/pypi/pyversions/geobizml)

GeoBizML is a Python package designed for geospatial business analysis and machine learning. It provides a set of tools and functions to analyze geographical data, perform clustering, visualize results, and more.

## Features

- Geospatial data handling with GeoPandas
- Clustering algorithms including K-Means
- Visualization of clusters and convex hulls using Leaflet maps
- Various visualization plots: points plot, path plots, bubble plots
- Easy integration with Jupyter Notebooks

## Installation

You can install GeoBizML from PyPI using pip:

```bash
pip install geobizml


## Copyright

Â© 2024 Himanshu Bhardwaj

All rights reserved.
vidsrc-search 0.2.7rc1
A pirate movie watcher written in Python
Requires Python: >=3.8
Keywords: movie, video, search

## Overview

![GitHub Release](https://img.shields.io/github/v/release/SomedudeX/vidsrc-search?style=for-the-badge) ![PyPI - Status](https://img.shields.io/pypi/status/vidsrc-search?style=for-the-badge) ![PyPI - Downloads](https://img.shields.io/pypi/dm/vidsrc-search?style=for-the-badge)

A command-line utility program that searches [VidSrc](https://vidsrc.to)'s API to provide movies for free.

<img width="1235" alt="Screenshot 2024-04-14 at 19 38 54" src="https://github.com/SomedudeX/vidsrc-search/assets/101906945/58983e3b-8f13-4474-92fe-cb5ad7f37b5f">

## Installation

```bash
pip install --upgrade vidsrc-search
vidsrc-search help
```

## Usage

```
usage: vidsrc-search <command> [option] [flags]

available commands:
    help        shows this menu
    version     displays version info
    search      search a movie by its name
    library     actions regarding the movie lib

optional flags:
    -d, --debug enables debug logging and disables
                certain features (e.g. progress bars)

use 'vidsrc-search help <command>' for info on a
specific command. arguments are strictly parsed in the
order specified above. when filing a bug report, please
be sure to use the '--debug' flag in log.
```

## Notes

This project has been tested on the following requirements and platforms:

 * CPython 3.8.19, 3.9.1, 3.12.2
 * Windows 11, macOS 14, Debian Linux

## Contributing

Opening issues on GitHub are the preferred way of contributing. Please include the steps to reproduce, what you expected to happen versus what actually happened, as well as the output of `vidsrc-search` with the `--debug` flag in your issue.

When filing issues, please also make sure that you are using `vidsrc-search` by directly cloning the repository as opposed to downloading from pip. This will make sure you have the most up-to-date version of `vidsrc-search`.

## Links

 * [License](https://github.com/SomedudeX/vidsrc-search/blob/main/LICENSE)
 * [Github](https://github.com/SomedudeX/vidsrc-search)
 * [PyPi](https://pypi.org/project/vidsrc-search/)
nugu 0.3
About nugu prgrammer named YangChoi
Requires Python: >=3.6

### What is NUGU?

Nugu(누구) is a Korean word that translates to 'WHO' in English. It carries a slightly negative meaning and can be used to refer to someone who's not very well-known.

I'm an unknown junior web programmer in Korea. 
But someday, I hope to work globally. Perhaps even become famous.
I might not have the skills yet, but I'll get there eventually. So, as a start to getting my name out there, I made this package. This package will lead you to my blog made with Next.js (not my major, just for fun).

Don't say anything about my blog yet, it's still under construction. You know how tough it is to work on side projects while having a full-time job, right? Just hang tight for a bit.

If you want to get to know me better or be a friend, feel free to reach out anytime - email or whatever works.

See ya 😎