semvec/pypi-packages huggingface dataset:
mailadm 1.0.0
web API and CLI tool for automatic e-mail user creation/deletion

mailadm
=======

mailadm is an administration tool for creating and removing e-mail accounts
(especially temporary accounts) on a `mailcow <https://mailcow.email/>`_ mail
server. This makes creating an email account as easy as scanning a QR code.

The general idea of how it works:

1. Admins generate an "account creation token", which can be displayed as a QR
   code
2. A soon-to-be user uses an email client to scan the QR code, which sends a
   web request to mailadm
3. mailadm creates the account and sends the password to the Delta Chat app,
   the user is automatically logged in to the new account

mail clients with mailadm support
---------------------------------

So far only the `Delta Chat messenger <https://delta.chat/>`_ supports mailadm.

setup & usage
-------------

See the `docs/index.rst` file or https://mailadm.readthedocs.io for more info.
pydataedit 0.0.8
A package to take edit doc/docx/trf files.
Requires Python: >=3.6
Keywords: video,images,video2images,image crop

# pycvtools

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
[![Python 3.10](https://img.shields.io/badge/python-3.10-blue.svg)](https://www.python.org/downloads/)   

## Functionality of the pydlmodels

- EDIT THE DOCUMENT
> - Name 
> - Email
> - Country / Address
> - Mask Mobile and Passport number


```
pip install pydataedit
```
##### To run
```
from pydataedit import *
```
Awa2 1.1.1
Simple Setup
Requires Python: >=3

# Awa2 
![PyPI](https://img.shields.io/pypi/v/awa2)
![Setup](https://img.shields.io/badge/setup-awa2-informational)

快速打包与发布包

## 打包
你可以在`README.md`写入我们的标志
```markdown
![](https://img.shields.io/badge/setup-awa2-informational)
```

## 命令
### 帮助
```bash
python -m awa2 -h
```

### 创建
快速开始创建开发包，需输入一些信息才可以开始
```bash
python -m awa2 quickstart
```

### 发布
快速打包发布包，需输入发布者的账号与密码
```bash
python -m awa2 quickupload
```
tartrl 0.0.3
reinforcement learning framework
Requires Python: >=3.8
Keywords: reinforcement-learning multi-agent reinforcement-learning-algorithms pytorch machine-learning baselines toolbox python data-science gym gymnasium

# TARTRL

---
[![Twitter](https://img.shields.io/twitter/url?style=social&url=https%3A%2F%2Ftwitter.com%2FTARTRL_Lab)](https://twitter.com/TARTRL_Lab)

[![Documentation Status](https://readthedocs.org/projects/tartrl-docs/badge/?version=latest)](https://tartrl-docs.readthedocs.io/zh/latest/?badge=latest)

![GitHub Org's stars](https://img.shields.io/github/stars/TARTRL)
[![GitHub stars](https://img.shields.io/github/stars/TARTRL/TARTRL)](https://github.com/opendilab/TARTRL/stargazers)
[![GitHub forks](https://img.shields.io/github/forks/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/network)
![GitHub commit activity](https://img.shields.io/github/commit-activity/m/TARTRL/TARTRL)
[![GitHub issues](https://img.shields.io/github/issues/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/issues)
[![GitHub pulls](https://img.shields.io/github/issues-pr/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/pulls)
[![Contributors](https://img.shields.io/github/contributors/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/graphs/contributors)
[![GitHub license](https://img.shields.io/github/license/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/blob/master/LICENSE)

## 欢迎来到TARTRL

[中文文档](https://tartrl-docs.readthedocs.io/zh/latest/) | [Documentation](https://tartrl-docs.readthedocs.io/en/latest/)

TARTRL是一个开源的强化学习框架。

## 目录

- [欢迎来到TARTRL](#欢迎来到tartrl)
- [目录](#目录)
- [安装](#安装)
- [快速上手](#快速上手)
- [支持者](#支持者)
  - [&#8627; Stargazers](#-stargazers)
  - [&#8627; Forkers](#-forkers)
- [Citing TARTRL](#citing-tartrl)
- [License](#license)
- [致谢](#致谢)

## 安装

```bash
pip install tartrl
```

## 快速上手

可以通过命令行快速训练`CartPole`环境:
```bash
tartrl --mode train --env CartPole-v1
```

## 支持者

### &#8627; Stargazers

[![Stargazers repo roster for @TARTRL/TARTRL](https://reporoster.com/stars/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/stargazers)

### &#8627; Forkers

[![Forkers repo roster for @TARTRL/TARTRL](https://reporoster.com/forks/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/network/members)

## Citing TARTRL

如果我们的工作对你有帮助，欢迎引用我们的论文:
```latex
@misc{tartrl2023,
    title={TARTRL},
    author={TARTRL Contributors},
    publisher = {GitHub},
    howpublished = {\url{https://github.com/TARTRL/TARTRL}},
    year={2023},
}
```

## License
TARTRL under the Apache 2.0 license.

## 致谢
lex2sent 0.0.2
A Python package to perform unsupervised sentiment analysis using lexicon enhanced Document embeddings
Keywords: python,sentiment analysis,nlp,doc2vec,bagging,text classification

# Lex2Sent - A bagging approach to unsupervised Sentiment Analysis
Lex2Sent is a text classification/clustering model that can be used with minimal a-priori-information to classify texts into two classes. While the [original paper](https://doi.org/10.48550/arXiv.2209.13023) used it for sentiment analysis on english documents, it is not limited to that purpose, but can be used for any arbitrary type of classification and language as long as there are lexica that can be used as an information-basis.

## Getting Started
You may install this package using either pypi
```
pip install lex2sent
```
or GitHub
```
pip install git+https://github.com/K-RLange/Lex2Sent.git
```

The following is an example of using the Opinion Lexicon to classify an iMDb movie review data set. You may have to use ```nltk.download()``` to download the opinion_lexicon first.
First we configure our data set 
```
from datasets import load_dataset
from nltk.corpus import opinion_lexicon
data = load_dataset('imdb')
ratings, reviews = [], []
for stars, text in zip(data["train"]["label"], data["train"]["text"]):
    if text:
        if stars == 0:
            ratings.append("negative")
        else:
            ratings.append("positive")
        reviews.append(text)
```
And now we can start applying Lex2Sent
```
from lex2sent.textClass import *
lexicon = ClusterLexicon([opinion_lexicon.positive(), opinion_lexicon.negative()])
rated_texts = RatedTexts(reviews, lexicon, ratings)

#Basic "counting" method of classification:
count_res = rated_texts.lexicon_classification_eval(label_list=["positive", "negative"])
l2s_res = rated_texts.lbte(label_list=["positive", "negative"], workers=4)
print("Counting accuracy: {}%; Lex2Sent accuracy: {}%".format(count_res * 100, l2s_res*100))
```
yielding the result "Counting accuracy: 73.772%; Lex2Sent accuracy: 78.172%".

## Reference
Please refer to ["Lex2Sent - A bagging approach to unsupervised Sentiment Analysis"](https://doi.org/10.48550/arXiv.2209.13023) when using this package. When you use this package in a publication, please cite it as
```
@misc{lex2sent,
  title = {{Lex2Sent}: {A} bagging approach to unsupervised sentiment analysis},
	shorttitle = {{Lex2Sent}},
	publisher = {arXiv},
	author = {Lange, Kai-Robin and Rieger, Jonas and Jentsch, Carsten},
	month = sep,
	year = {2022},
	note = {arXiv:2209.13023 [cs]},
	keywords = {Computer Science - Computation and Language},
}
```
## Future Features
-Calling from the console

-FastText and SentenceBERT as alternatives to Doc2Vec

-Options to classify into more than two clusters
tartrl-nightly 0.0.4
reinforcement learning framework
Requires Python: >=3.8
Keywords: reinforcement-learning multi-agent reinforcement-learning-algorithms pytorch machine-learning baselines toolbox python data-science gym gymnasium

# TARTRL

---
[![Twitter](https://img.shields.io/twitter/url?style=social&url=https%3A%2F%2Ftwitter.com%2FTARTRL_Lab)](https://twitter.com/TARTRL_Lab)

[![Documentation Status](https://readthedocs.org/projects/tartrl-docs/badge/?version=latest)](https://tartrl-docs.readthedocs.io/zh/latest/?badge=latest)

![GitHub Org's stars](https://img.shields.io/github/stars/TARTRL)
[![GitHub stars](https://img.shields.io/github/stars/TARTRL/TARTRL)](https://github.com/opendilab/TARTRL/stargazers)
[![GitHub forks](https://img.shields.io/github/forks/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/network)
![GitHub commit activity](https://img.shields.io/github/commit-activity/m/TARTRL/TARTRL)
[![GitHub issues](https://img.shields.io/github/issues/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/issues)
[![GitHub pulls](https://img.shields.io/github/issues-pr/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/pulls)
[![Contributors](https://img.shields.io/github/contributors/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/graphs/contributors)
[![GitHub license](https://img.shields.io/github/license/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/blob/master/LICENSE)

## 欢迎来到TARTRL

[中文文档](https://tartrl-docs.readthedocs.io/zh/latest/) | [Documentation](https://tartrl-docs.readthedocs.io/en/latest/)

TARTRL是一个开源的强化学习框架。

## 目录

- [欢迎来到TARTRL](#欢迎来到tartrl)
- [目录](#目录)
- [安装](#安装)
- [快速上手](#快速上手)
- [支持者](#支持者)
  - [&#8627; Stargazers](#-stargazers)
  - [&#8627; Forkers](#-forkers)
- [Citing TARTRL](#citing-tartrl)
- [License](#license)
- [致谢](#致谢)

## 安装

```bash
pip install tartrl
```

## 快速上手

可以通过命令行快速训练`CartPole`环境:
```bash
tartrl --mode train --env CartPole-v1
```

## 支持者

### &#8627; Stargazers

[![Stargazers repo roster for @TARTRL/TARTRL](https://reporoster.com/stars/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/stargazers)

### &#8627; Forkers

[![Forkers repo roster for @TARTRL/TARTRL](https://reporoster.com/forks/TARTRL/TARTRL)](https://github.com/TARTRL/TARTRL/network/members)

## Citing TARTRL

如果我们的工作对你有帮助，欢迎引用我们的论文:
```latex
@misc{tartrl2023,
    title={TARTRL},
    author={TARTRL Contributors},
    publisher = {GitHub},
    howpublished = {\url{https://github.com/TARTRL/TARTRL}},
    year={2023},
}
```

## License
TARTRL under the Apache 2.0 license.

## 致谢
random-prefix-generator 0.4
A package for generating random IPv4 and IPv6 addresses and subnets
Requires Python: >=3.6

# Random IP/Prefix Generator

`randomprefixgenerator` is a simple Python module for generating random IPv4 and IPv6 addresses and subnets.

## Features
* Generate random IPv4 or IPv6 addresses.
* Generate random IPv4 or IPv6 subnets with a specified prefix length.
* Control the range of prefix lengths for generated subnets.


## Installation

You can install myIp using pip:
```
pip install randomprefixgenerator
```


## Usage
```
from randomprefixgenerator import RandomPrefixGenerator

# Create a new myIp object for generating IPv4 addresses
ipv4_gen = RandomPrefixGenerator(4, mode='ip')

# Generate a random IPv4 address
ipv4_addr = next(ipv4_gen)

# Create a new myIp object for generating IPv6 subnets with prefix lengths between 64 and 120
ipv6_gen = RandomPrefixGenerator(6, mode='prefix', min_length=64, max_length=120)

# Generate a random IPv6 subnet
ipv6_subnet = next(ipv6_gen)
```

## Dependancies
* Python 3.x
* `ipaddress` module
spud-mc 1.3.1
A Minecraft Spigot plugin manager that adheres to the Unix philosophy and Python best practices
Requires Python: >=3.8

# Spud
![spudman logo](https://raw.githubusercontent.com/exciteabletom/spud/master/logo/spudman_tiny.png)


[![GPLv3 License](https://www.gnu.org/graphics/gplv3-88x31.png)](https://www.gnu.org/licenses/gpl-3.0.en.html)
[![GitHub Release](https://img.shields.io/github/release/exciteabletom/spud.svg?style=flat)](https://github.com/exciteabletom/spud/releases) 
[![PyPI downloads](https://img.shields.io/pypi/dm/spud-mc.svg)](https://pypistats.org/packages/spud-mc)
[![Code style: Black](https://img.shields.io/badge/code%20style-Black-000000.svg)](https://github.com/psf/black)


The cross-platform, [Spigot](https://www.spigotmc.org/) plugin manager that adheres to the
[Unix philosophy](https://en.wikipedia.org/wiki/Unix_philosophy) and Python best practices.

Some focuses of the project are:

1. Easy and simple commands (updating all your plugins is as simple as `spud update`)

1. Adherence to Unix conventions and no forced interactivity, which unlike other options like [pluGET](https://github.com/Neocky/pluGET), makes Spud easy to use in scripts.

1. Readability, static type hinting, test-driven development, and consistent styling in the codebase.

1. Descriptive and greppable output with actionable error messages


## Installation
Python 3.8 or later is required

Install with `python -m pip install spud-mc`

Run `spud -h` to see all the options.


## Example usages
- Install a plugin: `spud install PluginName`

- Install a plugin without prompting for input: `spud -n install PluginName`

- Update all plugins in the working directory: `spud update`

- Update all plugins in `~/server/plugins`: `spud -d ~/server/plugins update`
 
- Update plugin `myplugin.jar`: `spud update myplugin.jar`

## Known Issues
- Some resources have lots of filler in the title. e.g. `[1.8-1.17] · PluginName |
😃 😃 😃 | Epic Gaming Moments`.
Spud tries its best to extract the plugin name, but it will fail if there is copious amounts of garbage in the title


- Spud can't update plugins it has not installed. Make sure to install the plugin with Spud first, so it can save a metadata file to the jar.


- Spud can't install resources not listed on https://spigotmc.org


- Spud can't install premium resources

## Setting up a dev environment
`git clone git@github.com:exciteabletom/spud`

`cd spud`

`python3 -m venv .venv`

Bash: `. .venv/bin/activate`

Windows PowerShell: `.venv\bin\activate.ps1`

`python3 -m pip install -r requirements.txt -r requirements-dev.txt`

`pre-commit install`

## Acknowledgements
Logo created by [zach_can_draw](https://instagram.com/zach_can_draw/)
socialbox 0.1
SocialBox is a Bruteforce Attack Framework

<!--
https://pypi.org/project/socialbox/
https://pypi.org/project/socialbox/
-->

[![](https://img.shields.io/pypi/pyversions/readme-generator.svg?longCache=True)](https://pypi.org/project/readme-generator/)

#### Installation
```
$ pip install socialbox
```

#### Features
+   **`socialbox`**, **SocialBox is a Bruteforce Attack Framework ;)**


#### How it works
```
$ socialbox
```

#### How to Remove ?
```
$ pip uninstall socialbox
```

#### About Us
```
Created by Parixit Sutariya
Github : github.com/Bhai4You
Blog : bhai4you.blogspot.com
Youtube : youtube.com/BullAnonymous
```