semvec/pypi-packages huggingface dataset:
pandas-hug 0.14.0
a utility for space efficient dataframes
Requires Python: >=3.7

# pandas hug

sometimes you need to embrace your data and get a little, or a lot, more of it into memory.

your column data types are rarely space efficient. most of the time this is because they were chosen by someone else, but sometimes its just a hassle to find the most space efficient types.

`pandas-hug` is here to help crush your data to fit in memory.

# installation

```shell
pip install pandas-hug
```

# usage

```python
import pandas as pd
import pandas_hug

S = pd.Series([2**8])
A = pd.Series([f'a{i}' for i in range(100)])
M = pd.Series([42])
E = pd.Series(['a', 'b', 'c'] * 15)
df = pd.DataFrame({'S': S, 'A': A, 'M': M, 'E': E})

df.info()

   <class 'pandas.core.frame.DataFrame'>
   RangeIndex: 100 entries, 0 to 99
   Data columns (total 4 columns):
    #   Column  Non-Null Count  Dtype
   ---  ------  --------------  -----
    0   S       1 non-null      float64
    1   A       100 non-null    object
    2   M       1 non-null      float64
    3   E       45 non-null     object
   dtypes: float64(2), object(2)
   memory usage: 3.2+ KB


df.convert_dtypes().hug().info()

   <class 'pandas.core.frame.DataFrame'>
   RangeIndex: 100 entries, 0 to 99
   Data columns (total 4 columns):
    #   Column  Non-Null Count  Dtype
   ---  ------  --------------  -----
    0   S       1 non-null      UInt16
    1   A       100 non-null    string
    2   M       1 non-null      UInt8
    3   E       45 non-null     category
   dtypes: UInt16(1), UInt8(1), category(1), string(1)
   memory usage: 1.6 KB
```

`pandas-hug` monkey-patches `pandas.DataFrame` and `pandas.Series` to add the `hug()` method.

you should call `convert_dtypes()` before hugging your data. this does useful things like converting `float` to `int` (pandas >=1.2.0, dec 2020) and `object` to `string` where appropriate.
mugwort 0.5.5
一套由各种小脚本堆砌而成的工具集，主要用于爬虫和数据治理。
Requires Python: >=3.6.2,<4

# Mugwort Tools

这是一套由各种小脚本堆砌而成的工具集，主要用于数据治理和爬虫。

## 开始使用

因工具集使用了类型提示，故只能在 Python 3.6 以上环境中运行。

- 快速安装

```shell
pip install mugwort
```

- 按需安装

```shell
pip install mugwort[cryptor]
pip install mugwort[database-elasticsearch]
pip install mugwort[proxy-clash]
```

- 完整安装（包含完整依赖）

```shell
pip install mugwort[all]
```

## 工具列表

### Basic

无需安装任何依赖开箱即用的基础工具，包含**日志、多任务处理**等工具。

#### Logger

支持控制台输出和文件输出的日志工具

- 版本：1.1
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/basic/logger.md)

#### MultiTask

基于多线程、多进程实现的多任务处理工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/basic/multitask.md)



### Cryptor

基于各种算法实现的密码学工具，包含**对称加密解密、非对称密钥对生成、非对称加密解密、非对称签名校验、密钥交换、双因数令牌生成校验**等功能。

#### AES

由 AES 算法实现，支持**常用加密模式和常用填充方式**的加解密工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/cryptor/aes_cryptor.md)

#### TripleDES

由 3DES 算法实现，支持**常用加密模式和常用填充方式且兼容 DES 算法**的加解密工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/cryptor/des_cryptor.md)

#### RSA

由 RSA 算法实现，支持**密钥对生成、消息加密、消息解密、消息签名、消息校验功能**的加解密及签名工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/cryptor/rsa_cryptor.md)

#### Ed25519

由 Ed25519 算法实现，支持**密钥对生成、消息签名、消息校验功能**的工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/cryptor/ed25519_cryptor.md)

#### X25519

由 X25519 算法实现，支持**密钥对生成、密钥交换功能**的工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/cryptor/x25519_cryptor.md)

#### TOTP

由双因素身份验证相关算法实现，支持**一次性密码生成和验证**的工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/cryptor/totp_cryptor.md)

#### X509

采用 X509 格式标准实现，支持**证书生成、签名**的工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/cryptor/x509_cryptor.md)



### Database

常见数据库的帮助工具，主要用于快速进行数据的插入和导出。

#### Elasticsearch

用于快速使用 Elasticsearch 的帮助工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/database/elasticsearch_helper.md)



### Proxy

网络代理工具，可以快速启动代理服务器以投入各种需要通过代理出网的工作。

#### Clash

支持**订阅更新、节点切换、节点检测**功能的 Clash 代理工具

- 版本：1.0
- 文档：[点击跳转到说明文档](https://github.com/YongJie-Xie/MugwortTools/blob/main/docs/mugwort/tools/proxy/clash_proxy.md)



## 更新日志

- 2022-12-08
    - 优化密码学工具，添加 X509 证书管理

- 2022-12-30
    - 添加 Elasticsearch 帮助工具

- 2022-11-09
    - 添加多任务处理工具

- 2022-10-22
    - 添加代理工具
- 2022-09-18
    - 添加密码学工具
- 2022-09-14
    - 添加日志工具
AI-Jarvis 0.0.3
AI Jarvis Tools
Keywords: AI Jarvis Tools,Rishabh Tools,Jarvis Tools,AI Jarvis,Jarvis 0.2,AI Robot Tools,Jarvis,Rishabh,Rishabh Sahil,ML Jarvis,Self learning Jarvis

# AI_Jarvis

AI_Jarvis_Tool is a machine-learning based conversational dialog engine build in
Python which makes it possible to generate responses based on collections of
known conversations.

## Installation

This package can be installed from [PyPi](https://pypi.org/project/AI-Jarvis/) by running:

```
pip install AI-Jarvis
```

## Create a Chat Data Txt File
```
>> QNA Chat Txt File:- DataBase\\qna_log.txt
>> ChattterBot Txt File:- DataBase\\chat_log.txt
```

## Create a API
[OpenAI API] (https://beta.openai.com/) and create a api txt file
'''
>> API Txt File:- Data\\Api.txt
'''

## QNA Function
```
from AI_Jarvis import QNA
print(QNA.Questions_Answers("What is python?"))
```
## Output
>> **Question:** What is python? 
> 
>> **Answer:**  Python is a programming language.

## ChatBot Function
```
from AI_Jarvis import Brain
print(Brain.ChatBot_Brain("What is your name?"))
```
## Output
>> **You:** What is your name?   
> 
>> **Jarvis:** My name is Jarvis. 

## Speak Function
```
from AI_Jatvis import Speak
Speak.Speak("Hi I Am Rishabh...!!")
```

## Output
>> **Speak** Hi I Am Rishabh...!!
## Hindi And English Speech-Recognition
```
from AI_Jarvis import Listen
while True:
    print(MicExecution())
```
## Output
>> **Listening...**
>
>> **You Speak:**  Hi I am Rishabh.
> 
>> **Recognizing...**                                     
> 
>> **Speech-To-Text:** Hi I am Rishabh.
> 
>> **Listening...**                                        
> 
>> **You Speak:**  à¤¹à¤¾à¤¯ à¤®à¥‡à¤°à¤¾ à¤¨à¤¾à¤® à¤‹à¤·à¤­ à¤¹à¥ˆ|
> 
>> **Recognizing...**                            
> 
>> **Speech-To-Text:** Hi, My name is Rishabh.

## Clap Detector
```
from AI_Jarvis import Clap
while True:
    value=Clap.Tester()
    if "True-Mic"==value:
        print("Clap is Detected")
```
## Output
>> Clap is Detected

## Developer Details
>> GitHub:- [@RishabhSahil](https://github.com/RishabhSahil).
> 
>> PyPi:- [@RishabhSahil](https://pypi.org/user/RishabhSahil/).
>
>> Link:- [@RishabhSahil](https://www.linkedin.com/in/rishabhsahil/).
> 
>> Twitter:- [@RishabhSahil](https://twitter.com/_rishabh_sahil_).
>
>> Facebook:- [@RishabhSahil](https://www.facebook.com/Rishabh.Sahil.RS).
>
>> Replit:- [@RishabhSahil](https://replit.com/@Sahilkumar124).
> 
>> YouTube:- [@Digital Technical India](https://www.youtube.com/@digitaltechnicalindia587).
shinigami-cli 0.1.4
Basic CLI showing off the Shinigami library.
Requires Python: >=3.6

<h1 align="center">
    <img src="https://raw.githubusercontent.com/shinigamilib/cli/main/assets/shinigamicli_logo.jpg" />
</h1>

Basic CLI showing off the [Shinigami](https://github.com/shinigamilib) library

## Usage

You can install the cli via pip:
```bash
pip install shinigami-cli
```

Available commands:
```
-h,  --help      |  Help menu
-i,  --image     |  Docker image to generate
-v,  --version   |  Version of the Docker image
-b,  --build     |  Build the Dockerfile after generation
-rm, --remove    |  Remove the Dockerfile in your current working directory
```

## Example(s)

This command will generate a Dockerfile for Ubuntu 22.04, but won't build the Docker image
```bash
shinigami-cli -i "ubuntu" -v "22.04"
```

This command will build a Docker image running Python 3.8 and generate the Dockerfile
```bash
shinigami-cli -i "python" -v "3.8" -b
```

Removes the Dockerfile in your current working directory
```bash
shinigami-cli -rm
```
xia-openapi-flask 0.0.3
X-I-A
Requires Python: >=3.9

.. image:: https://img.shields.io/pypi/v/xia-openapi-flask.svg?color=blue
   :alt: PyPI-Server
   :target: https://pypi.org/project/xia-openapi-flask/

====================================
X-I-A
====================================



Quick start
=============================

Install the package::

    pip install xia-openapi-flask
onnx-diff 0.1.1
Work in progress...
Requires Python: >=3.9,<4.0
Keywords: onnx,compare,diff,difference,tool,model,ml,ai

# onnx-diff
A tool to find differences between [ONNX](https://github.com/onnx/onnx) files.

[![Workflow Badge](https://github.com/magnusmaynard/onnx-diff/actions/workflows/tests.yml/badge.svg)](https://github.com/magnusmaynard/onnx-diff/actions/workflows/tests.yml?query=workflow%3ATests)
[![Test Results Badge](https://gist.github.com/magnusmaynard/2c0836a3d3e96d474f7c9190ae0096ba/raw/tests_badge.svg)](https://github.com/magnusmaynard/onnx-diff/actions/workflows/tests.yml?query=workflow%3ATests)
[![Code Coverage Badge](https://gist.github.com/magnusmaynard/2c0836a3d3e96d474f7c9190ae0096ba/raw/coverage_badge.svg)](https://github.com/magnusmaynard/onnx-diff/actions/workflows/tests.yml?query=workflow%3ATests)


## Install
TODO:


## Usage
TODO:


## Develop
Build and install:
```
poetry install
```

Run:
```
poetry run python onnx_diff/diff.py </path/to/a.onnx> </path/to/b.onnx>
```

Test:
```
poetry run pytest -s
```
casestyles 1.2.3
A package for converting case styles to each other
Requires Python: >=3.6

## CaseStyles

### Install
```
pip install casestyles
```

### Import
```python
from casestyles import Name
```

### Create name
```python
name = Name.from_snake_case("snake_case_name")
```

```python
name = Name.from_camel_case("camelCaseName")
```

```python
name = Name.from_pascal_case("PascalCaseName")
```

### Transform name
snake_case_name = name.snake_case
camel_case_name = name.camel_case
pascal_case_name = name.pascal_case
```