semvec/pypi-packages huggingface dataset:
simple-image-framework 0.0.1
A simple image framework, for digital image processing support on lab.
Requires Python: >=3.7

# Simple Image Framework

This image framework is built for a simple usage of processing images with python. 
It is based on the [Pillow](https://pillow.readthedocs.io/en/stable/) library, (PIL fork). 

I set it for my own usage, but I hope it will be useful for you too. 

## Installation 

如果你想使用 *built distribution* 来安装本库，可以使用以下命令：
```sh
pip install dist/simple_image_framework-0.0.1-py3-none-any.whl
``` 

如果你想使用 *source distribition* 来安装本库，则用以下命令：
```sh
pip install dist/simple_image_framework-0.0.1-tar.gz
``` 

如果你想重新安装，可以使用 `--force-reinstall` 标志来强制重新安装。

如果你想直接使用 git 库得到的源码进行安装，可以在库根目录上直接使用命令：
```sh
pip install . 
``` 

## Usage 

详见 tests 文件夹中的参考样例 

## Contributing 

- Cutie Deng : [Github](github.com/CutieDeng) mail: Dengzr2020@mail.sustech.edu.cn
duoyuantongji 1.0.0
A small example package
Requires Python: >=3.7

``` python
import gzip
def un_gz(file_name):
    #获取文件名，去掉后缀名
    f_name=filename.replace(".gz","")
    #开始解压
    g_file=gzip.GzipFile(file_name)
    #读取解压后的文件，并写入去掉后缀名的同名文件
    open(f_name,"wb+").write(g_file.read())
    g_file.close()
un_gz('D:\D盘\Desktop\cvyuan-0.1.tar.gz')#绝对路劲
```

``` bash
git config --global user.email "moudexiao@gamil.com"
git config --global user.name "moudexiao"
git config http.sslVertify false

echo "# duoyuantongji" >> README.md
git init
git add README.md
git commit -m "first commit"
git branch -M main
git remote add origin https://github.com/moudexiao/duoyuantongji.git
git push -u origin main


git remote add origin https://github.com/moudexiao/duoyuantongji.git
git branch -M main
git push -u origin main
```

# Example Package

This is a simple example package. You can use
[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to write your content.
pandabus 0.0.5
A Simple Event Bus.
Requires Python: >=3
Keywords: eventbus

# PandaBus

This library provided a simple event bus.

## Using Example

### #1：Basic Using

```python
from pandabus import bus

# Create to event listener(printb should called after printa)
@bus.listen("print")
def printa(ent):
    print(f"hello from printa")
@bus.listen("print",after="printa")
def printb(ent):
    print(f'hello from printb')



# send event
bus.send("print")
```

### #2：Pro Using

```python
from pandabus import bus, Event


class StaticEvent(Event, static=True):
    msg: str
class DynaEvent(Event, cancelable=True):
    msg:str

# Create to event listener(printb should called after printa,printc)
@bus.listen(StaticEvent)
def printa(ent):
    print(f"{ent.msg} from printa")
@bus.listen(StaticEvent)
def printb(ent):
    print(f"{ent.msg} from printb")
@bus.listen(StaticEvent, after=["printa","printb"])
def printc(ent):
    print(f'{ent.msg} from printc')
@bus.listen(DynaEvent)
def printd(ent):
    print(f"{ent.msg} from printd")
    ent.cancel()
@bus.listen(DynaEvent,after="printd")
def printe(ent):
    print(f"{ent.msg} from printe")



# send event
bus.send(StaticEvent,"hello")
bus.send(DynaEvent,"hello again")
```

### #3：Own Bus?

```python
from pandabus import buses, Bus

bus1 = buses.bus1  # Simplely get a own bus.
bus2 = Bus("bus2")  # Work too.
```
ngram-extration 0.0.4
用于提取语料库的最大词频情况下的最长字符串，即用于挖掘语料库中的高频长字符串

# ngram_extration
## 概述  
- 目的  
用于提取语料库的最大词频情况下的最长字符串，即用于挖掘语料库中的高频长字符串，这类字符串可能是脏文本，也可能是特征文本；  
示例：  
corpus.txt中存在大量的高频字符串，如：  
```text
<sprite=3>  
【坐标分享】3级土地 (777,225)    
1级码头-(372,737) 
``` 
通过ngram_extration可以快速挖掘这类特征字符串。  

- 安装  
```shell script
pip install ngram_extration
```

- 用法  
```python
from ngram_extration import NgramExtration

def load_list_from_text(path):
    res = []
    with open(path) as f:
        for l in f:
            res.append(l[:-1])
    return res

ngram_extration = NgramExtration()
contents = load_list_from_text('corpus.txt')
final_feature_list = ngram_extration.extract_ngram(contents, min_df=10, ngram_range=(5,30), analyzer='char', lowercase=False)
```