semvec/pypi-packages huggingface dataset:
redshadowbox 0.1
simple message box you can use it in CTK > ctkbox(msg)

# Simple Dark Messagebox

## about
just simple dark Messagebox :p

## Usage Example :0
```python
redshadowbox('download complated! :0')
```
## images Example :p
![Dark Messagebox](https://k.top4top.io/p_3154jg9iw1.png)

### Installation -_0
```cmd
pip install redshadowbox
```
vks-bootstraper 1.4.0
The CLI tool to boostrap the instances of VKS clusters.

# vks-bootstraper ![PyPI](https://img.shields.io/pypi/v/vks-bootstraper?label=pypi%20package)
_The simple CLI tool to bootstrap instances of VKS workload clusters_

![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54)


<hr>

# Installation
- Install the `vks-bootstraper:latest` with `pip` tool:
  ```bash
  pip3 install --upgrade vks-bootstraper
  ```

# Build
- Install the Pip dependencies
  ```bash
  pip3 install --upgrade pip
  pip3 install --upgrade -r requirements.txt
  pip3 install --upgrade build twine
  ```

- Build the CLI
  ```bash
  python3 -m build
  twine check dist/*
  ```
  
- Publish the CLI to PyPi _(make sure you have configured the `$HOME/.pypirc` config file, refer this [section](#the-pypirc-config-file) to pre-configure before performing this step)_
  ```bash
  twine upload [--repository pypi] dist/*
  ```

# Others
## The `.pypirc` config file
- The config file should be located at `$HOME/.pypirc`
- The content of the file should be like this:
  ```ini
  [pypi]
    username = __token__
    password = pypi-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
  ```
  
# Usage
- Run the CLI with the following command:
  ```bash
  vks-bootstraper --help
  ```
  > ```bash
  > ➜   vks-bootstraper --help             
  > Usage: vks-bootstraper [OPTIONS] COMMAND [ARGS]...
  > 
  > Options:
  >   --version  Show the version and exit.
  >   --help     Show this message and exit.
  > 
  > Commands:
  >   add-host                 Add a new host to the /etc/hosts file
  >   generate-ssh-key         Generate the SSH key for the current instance
  >   get-instance-id          Get the vServer ID of the current instance
  >   get-local-ipv4           Get the local IPv4 of the current instance
  >   prepare-kubeadm-config   Prepare the kubeadm config file for the...
  >   waiting-instance-booted  Waiting for the instance to be booted up,...
  >   waiting-internet         Waiting for the instance to reach to the...
  > ```
m4811-spt-cli 1.0.0
The model4811 mfg test script.
Requires Python: >=3.7

# Model4811 MFG Test Instruction

This document covers the steps involved in the Model 4811 Remote Power Meter MFG testing using `m4811-spt-cli.py` script.

## Package Installation

- To install the `m4811-spt-cli` package, you can use `pip`. This will automatically install the package along with its dependencies `modbus_tk` and `pyserial`.

## Test Setup

- Make the Test Setup for MFG test by referring the following [Model4811 Connection Block Diagram](https://gitlab-x.mcci.com/mcci/hardware/catena/mfg/test-proc-4811/-/raw/main/assets/Model4811-MFG-Test-Setup.png)
practable 0.0.25
Connect to remote laboratory experiments hosted on a github.com/practable service
Requires Python: >=3.8

# practable-python
a library for connecting to experiments in python


## Example Usage

```python
import matplotlib.pyplot as plt
import numpy as np
from practable.core import Experiment
import time

messages = []
   
#modify with actual group code and experiment name
with Experiment('g-open-x3fca8','Spinner 51 (Open Days)', exact=True) as expt:
    
    # Command a step of 2 radians & collect the data
    expt.command('{"set":"mode","to":"stop"}')
    expt.command('{"set":"mode","to":"position"}')
    expt.command('{"set":"parameters","kp":1,"ki":0,"kd":0}')

    time.sleep(0.5)
        
    expt.command('{"set":"position","to":2}')    
    
    expt.ignore(0.5)
    messages = expt.collect(1.5)
    
    # Process the data
    ts = expt.extract_series(messages, "t")
    ds = expt.extract_series(messages, "d")
    cs = expt.extract_series(messages, "c")
    
    t = np.array(ts)
    t = t - t[0]
    
    # Plot the data
    plt.figure()        
    plt.plot(t/1e3,ds,'-b',label="position")
    plt.plot(t/1e3,cs,':r',label="set point")
    plt.xlabel("time(s)")
    plt.ylabel("position(rad)")
    plt.legend()
```


This script produces the following text output
```
Command: {"set":"mode","to":"stop"}
Command: {"set":"mode","to":"position"}
Command: {"set":"parameters","kp":1,"ki":0,"kd":0}
Command: {"set":"position","to":2}
Ignoring messages for 0.5 seconds |██████████████████████████████████████████████████| 100.0% Complete

Collecting messages for 1.5 seconds |██████████████████████████████████████████████████| 100.0% Complete

```
An a graph:

![Example graphic from a spinner](./img/spinner.jpg)

## Additional information

A user name is obtained and stored locally.

Bookings last only as long as the experiment is needed, because they are cancelled when the `with` environment exits. The default booking duration is 3 min.

You can use an existing booking by specifying `user="cxxxxxxxxxx"` where the username is found on the `user` tab of the booking system that holds the booking.

Other `practable` instances can be accessed by specifying it e.g. `booking-server="https://some.booking.server"`

## Requirements

Recommend python >= 3.8 because we're using websockets 12.0
gofetch 0.1.5
Fetch data from popular resources.
Requires Python: >=3.12.0

<div id="header" align="center">
  <img src="https://media.giphy.com/media/vHvV0vnsQreZFaMamr/giphy.gif" width="100" alt="Lazy Panda"/>

# gofetch

Data fetching package.

</div>


---


<div id="badges" align="center">
  <img src="https://img.shields.io/badge/3.12-yellow?label=python&style=plastic&logo=python&logoColor=yellow" alt="Python version: 3.12">
  <img src="https://img.shields.io/badge/MacOS | Linux-green?label=system&style=plastic&logoColor=blue" alt="System support: MacOS | Linux">
  <img src="https://img.shields.io/badge/beta-red?label=stage&style=plastic&logoColor=blue" alt="Stage: beta">
</div>


---


## Structure

### fetchers

`gofetch/fetchers`
This section is used for interacting with third-party APIs.

### parsers

`gofetch/parsers`
This section is used for parsing data returns from the fetchers module.

### tests

`tests`
This directory is crucial for maintaining the reliability of the package. It contains:
- Unit tests to verify individual parts of the code
- Integration tests to check if different parts work together
- Mock data and fixtures for testing

## Bye 🐧
progkids 0.1.7
Online coding school for kids - ProgKids
Requires Python: >=3.6

## Description

The `progkids` library is a Python package designed for seamless communication with Minecraft: ProgKids edition. This library enables developers to interact with the game programmatically, making it an excellent tool for educational purposes.

## Features

- Easy installation with pip, automatically handling dependencies.
- Suitable for both educational use and creating custom Minecraft projects.

## Installation Instructions

The installation process has been simplified to eliminate the need for manually managing dependencies. The updated installation and setup process is as follows:

### Step 1: Install the Library

To install the `progkids` library, run the following command:

```bash
pip install progkids
```

### Step 2: Obtain Your Access Token

You will need an access token to connect to Minecraft: ProgKids edition. Follow these steps to retrieve your token:

1. Log in to your account on [app.progkids.com](https://app.progkids.com).
2. Navigate to the settings page.
3. Press `F5` to refresh the page, and the token will be generated and displayed in the settings.

### Step 3: Test the Example Code

Try out the following test example to ensure everything is set up correctly. Replace `'nick'` with your nickname and `'your_token'` with your access token:

```python
from progkids import mc

mc.connect(nick='nick', token='your_token')
r1 = mc.player.getDirection()
print(r1)
mc.disconnect()
```
pyknos 0.16.0
don't regress. A package for neural conditional density estimation.
Requires Python: >=3.8
Keywords: conditional density estimation, mixture density networks, normalizing flows, diffusion models, PyTorch

[![PyPI version](https://badge.fury.io/py/pyknos.svg)](https://badge.fury.io/py/pyknos)
[![Contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/sbi-dev/pyknos/blob/master/CONTRIBUTING.md)
[![GitHub license](https://img.shields.io/github/license/mackelab/pyknos)](https://github.com/mackelab/sbi/blob/master/LICENSE.txt)

## Description

Python package for conditional density estimation. It either wraps or
implements diverse conditional density estimators.

### Density estimation with normalizing flows

This package provides pass-through access to all the
functionalities of [nflows](https://github.com/bayesiains/nflows).

## Installation

`pyknos` requires Python 3.8 or higher. A GPU is not required, but can lead to speed-up
in some cases. We recommend using a
[`conda`](https://docs.conda.io/en/latest/miniconda.html) virtual environment
([Miniconda installation instructions](https://docs.conda.io/en/latest/miniconda.html)).
If `conda` is installed on the system, an environment for installing `pyknos` can be
created as follows:

```commandline
$ conda create -n pyknos_env python=3.12 && conda activate pyknos_env
```

Independent of whether you are using `conda` or not, `pyknos` can be installed using `pip`:

```commandline
pip install pyknos
```

## Examples

See the [`sbi` repository](https://github.com/sbi-dev/sbi) for examples of using pyknos.

## Name

pyknós (πυκνός) is the transliterated Greek root for density
(pyknótita) and also means *sagacious*.

## Copyright notice

This program is free software: you can redistribute it and/or modify
it under the terms of the Apache License 2.0., see LICENSE for more details.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Affero General Public License for more details.

## Acknowledgments

Thanks to Artur Bekasov, Conor Durkan and George Papamarkarios for
their work on [nflows](https://github.com/bayesiains/nflows).

The MDN implementation in this package is based on Conor M. Durkan's.
nudantic 0.1.3
Numpy Array type compatible with Pydantic
Requires Python: >=3.10

# Nudantic

> Numpy Array type compatible with Pydantic

```python
from pydanctic import BaseModel
from nudantic import NdArray

class MyModel(BaseModel):
  array: NdArray

MyModel(array=np.array([1, 2, 3])).model_dump_json()
# {'array': [1, 2, 3]}
```
scrapy-settings-log 1.4.0
An extension that allows a user to display all or some of their scrapy spider settings at runtime.
Requires Python: >=3.8

# Scrapy Settings Log
An extension that allows a user to display all or some of their scrapy spider settings at runtime. 
It will add a logline with some or all settings for your spider in JSON compatible format.


## Install

`pip install scrapy-settings-log`

## Quick-Start

Add the following to your settings:

```python
EXTENSIONS = {
    'scrapy_settings_log.SpiderSettingsLogging': 999,
}

SETTINGS_LOGGING_ENABLED = True
```

When you run your spider you will see a log like below when spider is closing:

`[scrapy_settings_log] INFO: {"SETTINGS_LOGGING_ENABLED": true, ...}`

## Additional Options

* `SETTINGS_LOGGING_REGEX` - Add a regular expression to only show some settings - for example `SETTINGS_LOGGING_REGEX = "SPIDERMON"` will show settings with SPIDERMON in their name.
* `SETTINGS_LOGGING_INDENT` - Add indentation to make log more human-readable.
* `MASKED_SENSITIVE_SETTINGS_ENABLED` - Default is `True` - if settings logging is enabled it will mask the value of settings that may be sensitive (password, apikey). For example AWS_SECRET_ACCESS_KEY will have their value shown as **********

## Advanced

Subclass and override the `output_settings` method if you want the settings to be reported in another way.

```python
from scrapy_settings_log import SpiderSettingsLogging

class CustomSettingsLogger(SpiderSettingsLogging):

    def  output_settings(self, settings: dict, spider: scrapy.Spider):
        # custom code here
```