semvec/pypi-packages huggingface dataset:
kivy-garden.ebs.progressspinner 1.2
Fork of kivy-garden progress spinner
Keywords: Kivy kivy-garden

# ProgressSpinner

ProgressSpinner is a Kivy widget to display an Android Lollipop style progress spinner.

About this Fork
---------------

This package builds on a lot of good work of other people, including :
  - The original [kivy.garden.progressspinner](https://github.com/kivy-garden/garden.progressspinner), 
  written by @kived and contributed to over the years by others.  
  - Fork by [@stimpe](https://github.com/stimpe/garden.progressspinner), making the package pip installable.
  - At the time of the fork, upstream has remained unchanged 
  for 8 years. 
  - The fork has remained unchanged for 2 years. 

This is forked from `stimpe/garden.progressspinner` for the sole purpose of 
making it pip installable from PyPI. and will be made available as the 
`kivy_garden.ebs.progressspinner` package on PyPI. 

This package has no dependencies in the ebs namespace - it is simply used as 
a convenient way to differentiate from the upstream package and restrict 
namespace pollution to within the existing ebs namespace.

If you are considering using this: 

  - The original package works just fine, and has been working unmodified for 
  almost a decade at the time of this fork. No development is required or 
  planned. If you're fine with 'garden install progressspinner', don't use this
  fork.
  - If upstream makes itself pip installable, this fork and the associated PyPI 
  package will likely become unmaintained.
  - Some minor work may be needed to done to bring this in line with the new 
  `kivy_garden` format. I'm not actively working on this, but if the need for 
  it arises in form or another, I might look into it. Create an issue if you 
  have a use case which calls for it.
  
If you do end up using this package - especially if you do so in a 
production setting - please reach out to me and let me know by email at 
shashank at chintal dot in. The number of users, if any, is likely to 
determine how much effort I will put into maintaining this.


## Demo

![Example animation](progspin.gif)
zacktools 0.3.8
Zack's ommon tools

# zacktools

### Useful tools created by zackdai

# install
`pip install zacktools`

or from git

`pip3 install git+https://github.com/ZackAnalysis/zacktools.git`

## pageparser

A tool for parse address,phone, email, facebook, twitter, linkedin, contact link, about us link from a webpage

### usage

```
from zacktools import pageparser
import requests
res = requests.get('http://rel8ed.to')
result = pageparser.parse(res.content)
print(result)
```

```
{
  "facebook": "https://www.facebook.com/rel8edto/",
  "twitter": "https://twitter.com/rel8edto",
  "instagram": "",
  "linkedin": "https://www.linkedin.com/company/rel8ed-to",
  "contactlink": "http://www.rel8ed.to/contact-us/",
  "aboutlink": "http://www.rel8ed.to/about-us/",
  "title": "Big Data Analysis Data Mining Predictive Analytics",
  "email": "info@rel8ed.to",
  "phone": "905.321.0466",
  "Mainaddress": "1 St. Paul St., Unit A303, St. Catharines, ON L2R 7L2",
  "addresses": [
    "1 St. Paul St., Unit A303, St. Catharines, ON L2R 7L2"
  ]
}
```
### Test it [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1aE8PeQhJym8G6I_yHVfqIuydod5tlQuQ?usp=sharing)


## multithread

```
from zacktools.multiThread import scrapeurls
import asyncio
urls = ['ibm.com','idc.com']
asyncio.run(scrapeurls(urls))
```
sz-img-cls 0.0.1
Image classification model trained by the deep learning group of Guangdong University of Technology's Digital Intelligence Studio

#SZ_DeepLearning
This is an open source deep learning model. You can use the weights already provided by this model for free.
The model is allowed to be modified at will and any non-commercial use, this account does not assume any joint and several responsibility


```! pip install SZ_DeepLearning``` to install the package

```
import numpy as np
import tensorflow as tf
from SZ_DeepLearning import PI_resnet34

model = get_resnet34_model(image_size=224, class_num=5, load_weights="Porn-identification")

def Input_One_pics(image_path):
    """
    Convert single image to one array.
    :param image_path:
    :return:
    """
    image = tf.keras.preprocessing.image.load_img(image_path, target_size=(224, 224))
    input_arr = tf.keras.preprocessing.image.img_to_array(image)
    input_arr = np.array([input_arr])
    return input_arr
   

model.predict()  # here input one img_array and dim have to be [1, 224, 224, 3], 3 means three channels   
```
aids 0.2.2
Client for AI Dynamic Storytelling Services.
Requires Python: >=3.8

# AIDScrapper

Based off a small script made by an Anonymous user. Now it's a full featured client which supports not only [AID][0] but also [Holo][0]. Alternatively, it can transform AID scenario objects in .scenario files for compatibility with the different AI Dynamic Storytelling platforms, specially [NAI][2]
The json files can be transformed into .html for better readability although that's not the main purpose of this tool - you should upload it to one of the supported websites to use the stories.

# Requirements
To install all requirements, use the following snippet after installing python on your machine.

    pip install -r requirements.txt

Or just use:

    pip install aids


# Usage
To install the whole thing. You can manage it directly from console. Use:

    aids help

Afterwards for a list of commands or:

    aids-windows.bat help

If you use Windows.

You can also use the package directly via:

    python3 -m aids help

Or in outside the package directory with:

    python aids/manage.py help

# Testing
If you feel like messing around with the code make sure none of the tests are failing using the *test* command. It uses pytest if you have it installed or unittest as a fallback.

[0]: https://play.aidungeon.io
[1]: https://www.writeholo.com
[2]: https://novelai.net/
make-vcard 1.0.2
用于以excel文件生成.vcf通讯录导入文件

# make_vcard

这是一个将xlsx文件转化为通讯录导入(.vcf)文件的py程序。

## 安装
```
pip install make_vcard
```



## 基本使用方法

```
python -m make_vcard inputFileName.xlsx
```



## HTELP

```
usage: make_vcard [-h] [--example] [--sheet SHEET] [--filetype FILETYPE] [-o O] inputFileName

基本用法 python -m make_vcard inputFileName.xlsx [-o outputFileName]

positional arguments:
  inputFileName        指定读取的文件

optional arguments:
  -h, --help           show this help message and exit
  --example            生成示例excel文件；
  --sheet SHEET        指定读取哪张表；默认为第一张表
  --filetype FILETYPE  指定文件类型（默认为excel）只可以指定为 csv
  -o O                 输出保存的文件名；不需要加后缀！

注意：不同设备对 字段 的支持不一样，可能您按照这个规则并不会得到您想要的结果！
```



说明

只有 姓名和电话 是必要的，其它是可以任意组合

有 电话, 邮箱, 网址, 地址 是可以重复出现的；其规则是 名称+数字；例: 电话A

可重复出现的数据可定义其类型

电话的类型有：优先，住宅，工作，单元，传真，其它 

邮箱的类型有：住宅，工作，其它

网址的类型有：住宅，工作，其它 

地址的类型有：住宅，工作，其它，邮寄 

例如： 邮箱(住宅)

例如： 网址（工作）

注意：不同设备对 字段 的支持不一样，可能您按照这个规则并不会得到您想要的结果！