semvec/pypi-packages huggingface dataset:
king-99999 0.0.2
suuuuuuuuuuuu
Keywords: python, video, stream, video stream, camera stream, sockets


HI

HI

suuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuu
one-piece-wanted-poster 0.0.13
Python package to generate One Piece Wanted Posters
Requires Python: >=3.10

# one-piece-wanted-poster

[![Python](https://img.shields.io/pypi/pyversions/one-piece-wanted-poster)](https://img.shields.io/pypi/pyversions/one-piece-wanted-poster)
[![Pypi](https://img.shields.io/pypi/v/one-piece-wanted-poster)](https://pypi.org/project/one-piece-wanted-poster/)
[![LOC](https://sloc.xyz/github/nickelza/one-piece-wanted-poster/?category=code)](https://github.com/nickelza/one-piece-wanted-poster/)
[![Downloads](https://static.pepy.tech/personalized-badge/one-piece-wanted-poster?period=month&units=international_system&left_color=grey&right_color=brightgreen&left_text=PyPI%20downloads/month)](https://pepy.tech/project/one-piece-wanted-poster)
[![Downloads](https://static.pepy.tech/personalized-badge/one-piece-wanted-poster?period=total&units=international_system&left_color=grey&right_color=brightgreen&left_text=Downloads)](https://pepy.tech/project/one-piece-wanted-poster)
[![License](https://img.shields.io/badge/license-MIT-green.svg)](https://github.com/nickelza/one-piece-wanted-poster/blob/master/LICENSE)
[![Forks](https://img.shields.io/github/forks/nickelza/one-piece-wanted-poster.svg)](https://github.com/nickelza/one-piece-wanted-poster/network)
[![Issues](https://img.shields.io/github/issues/nickelza/one-piece-wanted-poster.svg)](https://github.com/nickelza/one-piece-wanted-poster/issues)
[![Project Status](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active)

---------

### Install one-piece-wanted-poster from PyPi.
```bash
pip install one-piece-wanted-poster
```

#### Example

```
import os
from wantedposter.wantedposter import WantedPoster
from PIL import Image


def main():
    # Set "Luffy" as first name and "D. Monkey" as last name
    first_name = 'Luffy'
    last_name = 'Monkey D.'

    # Set bounty amount to 3.000.000.000
    bounty_amount = 3_000_000_000

    # Create WantedPoster object
    wanted_poster = WantedPoster(None, first_name, last_name, bounty_amount)

    # Generate poster
    path = wanted_poster.generate()

    # Show image
    Image.open(path).show()


if __name__ == '__main__':
    main()
```

### Credits

[AlleCosti95](https://github.com/allecosti95?tab=repositories)

Thanks to ClayStage for providing the original [template](https://claystage.com/one-piece-wanted-poster-template).
const-utils 0.0.1
Effective constant management tools
Requires Python: >=3.7

# Const-Utils

`const-utils` is a small-yet-effective library that offers some
tools for working with Python constants. Its main feature is
the *Constant Class*, which includes utilities for accessing
constants, stored within a container class.

Defining constant classes is available by using `ConstClassMeta`
(as a metaclass), or the standard `BaseConstClass` (by inheritance).

## Examples
### Creating a constant class
```python
class CountryConsts(BaseConstClass):
    US = 'United States of America'
    UK = 'United Kingdom'
```

### Access options
#### Access from the class itself
```python
>>> CountryConsts.as_dict()  # {'US': 'United States of America', 'UK': 'United Kingdom'}
>>> CountryConsts['US']  # 'United States of America
>>> Country.const_names  # ['US, 'UK']
>>> Country.const_values  # ['United States of America', 'United Kingdom']
```

#### Access global/local constants
```python
>>> # Access current global/local constants (depends on kwarg `local`)
>>> # as a dictionary of names to values
>>> access_namespace_consts(local=False)
```

### Storing class constants to a namespace
```python
>>> # Store constants in a module
>>> CountryConsts.apply_to_module('some_module_name', override=True)
>>> # Store constants as globals
>>> CountryConsts.apply()
>>> # Store constants as locals
>>> CountryConsts.apply(local=True)
```
suuuuuuuuu-suuuuu 0.0.1
suuuuuuuuuuuu
Keywords: python, video, stream, video stream, camera stream, sockets


HI

HI

suuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuusuuuuuuuuuuuuu
Xgua 0.0.2
Logger with saving logs to s3 storage
Requires Python: >=3.6
Keywords: Xgua Logger S3 s3logger

# Xgua - Logger with saving logs to s3 storage

## Save files to the vault to fix bugs and improve your product!

----------

### Quick Startup

```python
import asyncio
from Xgua.config import Config, S3Config
from Xgua.logger import Logger

s3 = S3Config("access_key", "secret_key", "endpoint_url", "bucket_name")
config = Config(s3)
logger = Logger(config)

async def main():
	try:
		"0" + 1
	except Exception as e:
		await logger.log(e)

asyncio.run(main())
```

----------

### Configuration

| Argument | README |
| ------ | ------ |
| access_key | Get after adding a serialized user |
| secret_key | Get after adding a serialized user |
| endpoint_url | If you haven't enabled "Virtual-Hosted Addressing", then https://s3.storage.selcloud.ru or else name-container.s3.storage.selcloud.ru |
| bucket_name | The name of the container at creation. |

#### How do I get all the parameters?

Through the side navigation block go to "Access Control" -> Next tab "Service Users" and add a new user.

[Fast open "Access Control"](https://my.selectel.ru/iam/users_management/users?type=service&create=false)

#### How do you create a container?

Using the navigation box on the right, navigate to "Cloud Storage" and click on the "Create Container" button

![View Photo](https://github.com/SikWeet/Xgua/assets/124031984/5d9a34b1-cf7c-480b-b6a7-b38051a97b92)


[Fast Open "Storage"](https://my.selectel.ru/storage)

#### Config

Now substitute your values by key

```python
s3 = S3Config("access_key", "secret_key", "endpoint_url", "bucket_name")
```
neuro-scribe 0.2.0.post3
NeuroScribe - a lightweight deep learning framework.
Requires Python: >=3.11

<h1 align="center"> NeuroScribe v0.2.0 </h1>

<div align="center">
    <picture>
        <img src="./docs/static/neuroscribe_logo.png">
    </picture>
</div>

## Installation

```
> pip install neuro-scribe
```

> [!Note]
>
> - If you want CUDA support for GPU acceleration, please ensure that you have CUDA Toolkit version 12 or higher installed on your device.<br> You can download CUDA Toolkit from the official NVIDIA website: [CUDA Toolkit Downloads](https://developer.nvidia.com/cuda-downloads)
> - If you're installing NeuroScribe on an Apple Silicon Mac, NeuroScribe will automatically detect the architecture and install additional dependencies for Metal Performance Shaders (MPS) support.

## Quick Start Example

This example demonstrates how to use Neuroscribe in a way that closely resembles PyTorch syntax and conventions. By following PyTorch's familiar patterns, users can easily integrate Neuroscribe into their existing deep learning workflows without significant adjustments.

```python
import neuroscribe as ns
import neuroscribe.nn as nn


class MyModel(nn.Module):
    def __init__(self):
        super().__init__()
        self.l1 = nn.Linear(784, 128)
        self.relu = nn.ReLU()
        self.l2 = nn.Linear(128, 10)

    def forward(self, x):
        x = self.l1(x)
        x = self.relu(x)
        x = self.l2(x)
        return x


def main():
    model = MyModel()
    model.eval()
    model.to('cuda')
    input = ns.randn(32, 784, dtype='float32', requires_grad=False, device='cuda')
    output = model(input)
    print(output)


if __name__ == '__main__':
    main()
```

## Available Accelerators

Neuroscribe currently supports the following accelerators:

- CPU (default)
- CUDA
- MPS (Metal Performance Shaders)

We plan to add support for additional accelerators to further enhance performance capabilities.

## Notes

- Functions suffixed with '\_' in the Tensor class perform in-place modifications to the Tensor object and do not create a new Tensor as output.
function-comment 0.1.0
A library to comment out functions using decorators
Requires Python: >=3.6

# function_comment

A Python library to create full-function comments using decorators.

## Installation

You can install the package using pip:

```bash
pip install function_comment


```python
from function_comment import bbkp, ujmp

@bbkp
@ujmp
def some_function():
    print("This should not be printed")

def normal_function():
    print("This should be printed")

if __name__ == "__main__":
    some_function()       # This will do nothing
    normal_function()     # This will print "This should be printed"