semvec/pypi-packages huggingface dataset:
googoal 0.0.1
Python software for interfacing with google services.
License: MIT
Requires Python: >=3.6.0

goggles
===

<p align="left">
  <a href="https://github.com/lawrennd/goggles"><img alt="GitHub Actions status" src="https://github.com/lawrennd/goggles/workflows/code-tests/badge.svg"></a>
</p>

Software for interfacing with Google Services. This code was originally incorporated with the `pods` software, but split out in May 2021.


To access a spreadsheet from the script, you need to follow the
protocol for Oauth 2.0, the process is described (here)[https://developers.google.com/identity/protocols/OAuth2]

Once you have the key file, you can specify its location in the
`.ods_user.cfg` file, using for example

```
[google docs]
# Set the email address of an account to access google doc information.
oauth2_keyfile = $HOME/oauth2-key-file-name.json
```
Winglets 0.1.8.0
Winglets by Python
License: MIT
Requires Python: >=3.6.0

# 下载
- python3，推荐python3.6以上
- pip install Winglets 

# 接口
## Winglets
```
drawWinglets(data, colorArray = ['red', 'blue', 'pink', 'orange', 'purple', 'indigo'], onlyWinglets=True)
```
#### 参数
- data: 要添加效果的数据，数据形式可以为数组或者对象
    - 对象: 对象的key为每组数据的类
        ```
        {
            "1" : [ 
                {
                    "x" : 458.545253723722,
                    "y" : 517.796113219558
                }, 
                ...
            ],
            "4" : [ 
                {
                    "x" : 487.798180288922,
                    "y" : 346.750755518256
                }, 
                {
                    "x" : 458.787734845522,
                    "y" : 316.371739750119
                }, 
                ...
            ]
        }
        ```
    - 数组：数组没有标识属于哪个类，所以内部会按照从1往后的顺序设置数据标识类
        ```
        [
            [ 
                [458.545253723722, 517.796113219558], 
                [487.798180288922, 346.750755518256]
                ...
            ],
            [ 
                [487.798180288922, 346.750755518256],
                [458.787734845522, 316.371739750119],
                ...
            ]
        ]
        ```
- colorArray：颜色数组。设定各个类对应的颜色，如:
    ```
    colorArray = ['red', 'blue', 'pink', 'orange']
    data = {
            "1" : [ 
                {
                    "x" : 458.545253723722,
                    "y" : 517.796113219558
                }, 
            ],
            "4" : [ 
                {
                    "x" : 487.798180288922,
                    "y" : 346.750755518256
                }, 
                
            ]
        }
    
    ```
    **注意：若colorArray的长度小于data中类的数量则会报错**
- onlyWinglets：默认为True，程序中不会出现proximity和commonFate对应的按钮，若为False，则会出现所有操作对应的按钮
## CommonFate
```
drawCommonFate(data, colorArray = ['red', 'blue', 'pink', 'orange', 'purple', 'indigo'])
```
#### 参数
- data：同接口Winglets
- colorArray：同接口Winglets
## Proximity
```
drawProximity(data, colorArray = ['red', 'blue', 'pink', 'orange', 'purple', 'indigo'])
```
#### 参数
- data：同接口Winglets
- colorArray：同接口Winglets

## circle
```
drawCirlce(data, colorArray = ['red', 'blue', 'pink', 'orange', 'purple', 'indigo'], onlyCicle=True)
```
#### 参数
- data：同接口Winglets
- colorArray：同接口Winglets
- onlyCircle: 默认为t=True，没有其他操作的按钮，若为False，则所有操作的按钮都有

# 代码步骤简要v0.1
1. 生成density map，会有很多个density值
2. 根据不同的density生成isoValue对应的contour
3. 找到应该保留的最外层contour
4. 根据最外层contour找到centroids，将最外城contour分成sampleNum份，再根据centroids和centroid对应的射线，求出与最外层contour的交集，根据交点插值生成里层的contourNum个contour
5. 遍历当前所有点，找到最近的contour上的最近的点，在contour上根据最近的点生成winglets的左边与右边（其实就是左右端点），然后根据向量计算，分别找到contour上左右点对应的原有点处的左右点，这样就可以根据原有点处的左右点生成满足对应contour弧度的位于原有点处的winglets
6. 根据第五步生成的点使用d3来画线段
sanstem 1.0.2
A rule-based stemmer for Sanskrit Verbs and Nouns
License: MIT
Keywords: Sanskrit Stemmer

# sanstem
Sanstem is a tool used for **stemming** Sanskrit Verbs and Nouns. Stemming is a pre-processing procedure applied for many NLP algorithms by which the suffix of a word is removed to obtain its stem/root form. This tool is built using a simple rule-based approach. 

### Installation
`pip install sanstem`

------------


### Usage
    from sanstem import SanskritStemmer
	
	#create a SanskritStemmer object
	stemmer = SanskritStemmer()

##### Stemming a Noun
    inflected_noun = 'गजेन' 
    stemmed_noun = stemmer.noun_stem(inflected_noun)
    print(stemmed_noun)
	# output : गज्

##### Stemming a Verb
    inflected_verb = 'गच्छामि'
    stemmed_verb = stemmer.verb_stem(inflected_verb)
    print(stemmed_verb)
	# output : गच्छ्

Please note to only enter a **single word** in  **Devanagari**  text as input to the functions `verb_stem()` and `noun_stem()`.

------------


### Contribute
- Currently the tool can stem only Sansrkrit Verbs and Noun. It can be extend to more parts of speech like adjective, adverb etc.
- The tool can be made flexible to accept Sanskrit input in any convention like IAST, HK, iTrans etc.
- Instead of stemming just a single word, it can be made capable of stemming a sentence or even a whole file.

------------


### Issue
Please [open an issue ](https://github.com/sooraj-nair/sanstem/issues "open an issue ")here in case any bug was encountered. 
Mail id : nairsooraj2000@gmail.com