semvec/pypi-packages huggingface dataset:
example-package-analytic-lib 0.0.1
A small package that calculates Average and percentages
Requires Python: >=3.7

To use this Average and percentage library,input the following parameters.

#for "Average"  of set of numbers,
"sum_of_numbers": means the total sum of all numbers that you are about getting the average
"count_of_numbers":means the count of the total numbers you are summing

#for "percentage of set nof numbers"

"total_of_particular_entity": this is the particular entity you are about getting the percentage out of the whole entities

total_of_whole_entity": this is the value of the whole entities.

# you are to use the instance this way:

if __name__ == '__main__':
    ap = AnalyticProperties()
    sum_of_numbers=678
    count_of_numbers=67
    total_of_particular_entity=499
    total_of_whole_entity=50000
    
    print('\n the average of the count of {} entries  to the total sum of all entries {}  is   : {}'.format(count_of_numbers,sum_of_numbers, ap.average(count_of_numbers,sum_of_numbers)))
    print('The percentage of {}  to {} is : {}%'.format(total_of_particular_entity,total_of_whole_entity, ap.percentage(total_of_particular_entity,total_of_whole_entity)))
job-shop-cp-env 1.0.0
An optimized RL approach to learn and simulate the Job-Shop Scheduling problem using Constraint Programming
Requires Python: >=3.8

# A Constraint Programming Based Job-Shop Scheduling Environment

This is a Constraint Programming (CP) based Job-Shop Scheduling (JSS) Environment that can be combined with Reinforcement-Learning (RL) to train an agent to solve a scheduling problem.
Compared to other environments, this CP based one is made to be fast and scalable.
If you install it using `setup.py`, it will automatically compile using MyPyC. 
Also, this environment has been developed for an end-to-end approach, there is no pre-defined reward function and the observation are simply the raw `IntervalVariable` representation.
We recommend the reader to check the paper for more information.

If you need to define a reward function or a different observation, you can do so by forking the environment and modifying the `step` function.

# Installation

```bash
pip install jss_cp
```
jsl-tmp 4.2.3rc16
The John Snow Labs Library gives you access to all of John Snow Labs Enterprise And Open Source products in an easy and simple manner. Access 10000+ state-of-the-art NLP and OCR models for Finance, Legal and Medical domains. Easily scalable to Spark Cluster
Keywords: Spark NLP OCR Finance Legal Medical John Snow Labs

# The John Snow Labs Library
The John Snow Labs Library gives you access to all of John Snow Labs Enterprise and Open Source products in an easy and simple manner.             
Access 10000+ state-of-the-art NLP and OCR models for `Finance`, `Legal`,`Medical` and many other domains which effortlessly scales to big data clusters.               
See https://www.johnsnowlabs.com/  and [the docs](https://nlu.johnsnowlabs.com/docs/en/install) for more details     

To install the NLP Libraries in your environment:

1. Get a license key in your [my.johnsnowlabs.com](https://my.johnsnowlabs.com/) account. If you do not have one, get a trial license [here](https://www.johnsnowlabs.com/install/).
2. In your shell, run:
```shell
pip install johnsnowlabs
````

3. In a Python shell, run :
```shell
from johnsnowlabs import spark_nlp  
nlp.install()
````
pyomgclient 1.1.0
a python omegle client
Keywords: python,omegle,XProjects,TheXProjects,client,omegleclient,pyomgclient,omgclient,pythonomengleclient


# PyOMGClient
> A PYTHON OMEGLE CLIENT 

# installation

```bash
pip install pyomgclient
```

# usage

```python 
from pyomgclient.omgclient import Client

client = Client()

@client.set_on_start_cb
def on_open ():
  print ("stranger connected")

@client.set_on_disconnect_cb
def on_close ():
  print ("stranger disconnected")
  # to restart
  client.start()

@client.set_on_typing_cb
def on_typing ():
  print ("stranger typing")

@client.set_on_message_cb
def on_message (msg):
  print ("message: "+msg)
  # sends a message
  # set typ = True for type and send
  client.send_message ("hi", typ = True)
  # or
  client.start_typing()
  time.sleep (1)
  # stop typing must be called otherwise the typing wont turn off
  client.stop_typing()

# always call the start function
# atfer setting callbacks
# otherwise client will connect without
# any callbacks

client.start()

# returns client configuration in json format
print (client.credentials())
```

# Solving Recaptcha

**this project cannot solve captcha so if your client is not getting any updates then go to your browser and open omegle then solve the captcha**

# Example Projects

> example projects will be promoted here

# ⚠️ DISCLAIMER

`this projects was made for educational purposes
do not spam people with this 
and we are not responsible for any illegal purpose done with this project`

  `omegle may ban your ip address so be careful`


**© XProjects**
whlctl 0.1.1
WartHog Lights ConTroL

# Warthog Lights Control

This Python module and command line tool control the lights on Thrustmaster's Warthog HOTAS throttle box.

Largely based on the [reverse-engineering] work done by mfranz

## How to use

Once installed, this tool provides a Python module and a command-line tool, both named `whlctl`.

### Command line tool

```sh
whlctl 0        # Turn off backlight
whlctl 5        # Turn backlight up to max brightness
whlctl 3 -l 1,5 # Turn lights 1 and 5 up to brightness 3/5
whlctl 1 -l 0,5 # Turn backlight and light 5 up to brightness 1/5
```

Omitting the `-l` flag will default to adjusting the backlight, and turn off all other lights.

### Python API

```python
import whlctl

whlctl.find_throttle()  # -> "/dev/hidrawN" or FileNotFoundError
whlctl.write_leds(backlight=True, leds=[True,True,True,True,True], brightness=5)
                        # -> None or FileNotFoundError (see find_throttle)
```

#### `find_throttle()`
Takes no argument and returns the HID node for the Thrustmaster Warthog throttle (`044f:0404`), or raises a `FileNotFoundError` if the device isn't found.  
This function is cached.

#### `write_leds(backlight: bool, leds: list[bool], brightness: int)`
The `leds` list must contain 5 booleans which designate, in order, the five circular lights from top to bottom. `True` means the light is to be powered on at the given brightness, `False` means it should be powered off.  
`brightness` is expressed between 0 and 5.  
Returns nothing, implicitly calls `find_throttle()` and thus can fail with `FileNotFoundError` as above. It can also hit a permission error if the current user has no write permission to the device node.

[reverse-engineering]: https://web.archive.org/web/20121029171225/http://members.aon.at/mfranz/warthog.html
measurenary 1.0.4
A package to calculate and find the best similarity between binary data features
Requires Python: >=3.6

![PyPI - License](https://img.shields.io/pypi/l/measurenary)
[![Documentation Status](https://readthedocs.org/projects/measurenary/badge/?version=latest)](https://measurenary.readthedocs.io/en/latest/?badge=latest)


# Measurenary

Measurenary is a Python library for computing your suitable similarity matrix from your binary data.

### Installation
To use Measurenary, first install it using pip:
```console
   (.venv) $ pip install measurenary
```
### Get started
To get started, you can import the library and use the `AgglomerativeBestMeasure` or `PairBestMeasure` class:
```python
   import measurenary

   # Instatntiate a Measurenary object
   aggbs = measurenary.AgglomerativeBestMeasure()
   
   # Call the fit function
   aggbs.fit(X)

   # Print out the result
   print(aggbs.get_result())
```