semvec/pypi-packages huggingface dataset:
telget 1.0.0
a Small Library for Getting Info About Telegram Usernames .
Requires Python: >=3.5

# TELGET - getting info about telegram usernames (Ver 1.0.0) .

## a small package for getting info about telegram accounts .

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

# USAGE 

1 - IMPORT PACKAGE
	``>>> from telget import Username``

2 - MAKE OBJECT 
	``>>> username = "telegram_username"``
	``>>> account = Username(username)``

3 - GET INFO ABOUT USERNAME 
- GET Account TYPE (Channel or Group or ....) -> ``>>> account.getType()``
- GET Bio -> ``>>> account.getBio()``
- GET Members (for channels and groups) -> ``>>> account.getMembers()``
- Download And Save Profile Photo -> ``>>> account.getProfilePhoto(path_to_save)``


Have Fun ...
telget-mrpythonblog 1.0.0
a Small Library for Getting Info About Telegram Usernames .
Requires Python: >=3.5

# TELGET - getting info about telegram usernames (Ver 1.0.0) .

## a small package for getting info about telegram accounts .

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

# USAGE 

1 - IMPORT PACKAGE
	``>>> from telget import Username``

2 - MAKE OBJECT 
	``>>> username = "telegram_username"``
	``>>> account = Username(username)``

3 - GET INFO ABOUT USERNAME 
- GET Account TYPE (Channel or Group or ....) -> ``>>> account.getType()``
- GET Bio -> ``>>> account.getBio()``
- GET Members (for channels and groups) -> ``>>> account.getMembers()``
- Download And Save Profile Photo -> ``>>> account.getProfilePhoto(path_to_save)``


Have Fun ...
pedia-cloud 0.0.11
A third-party Python API for Pedia Cloud Dictionary
Requires Python: >=3.7

# Pedia Cloud API

A third-party Python API for [Pedia Cloud Dictionary](https://pedia.cloud.edu.tw/)

## Install

```bash
pip install pedia-cloud
```

## Usage

### Get all words and its meaning

```python
>>> from pedia_cloud import PediaDictionary
>>> PediaDictionary.get_all("早")
[早, ㄗㄠˇ, meanings count: 11]
>>> PediaDictionary.get_all("好")
[好, ㄏㄠˇ, meanings count: 14, 好, ㄏㄠˋ, meanings count: 3]
>>> PediaDictionary.get_all("早")[0].meanings
[{'type': '[名]', 'def': '天剛亮的時候...'}, ...]
```

### Get all possible part-of-speech

```python
>>> from pedia_cloud import PediaDictionary
>>> PediaDictionary.get_all_poss("好")
Counter({'副': 7, '形': 3, '動': 3, '歎': 2, '名': 2})
```

### A word

```python
>>> from pedia_cloud import PediaDictionary
>>> word = PediaDictionary.get_one("好")
>>> word
好, ㄏㄠˇ, meanings count: 14
>>> word.text
'好'
>>> word.zuyin
'ㄏㄠˇ'
>>> word.annotations
['美、善，理想的。', '友愛的。', ...]
>>> word.meanings
[{'type': '[形]', 'def': '美、善，...
>>> word.filter_by_pos(["副"])
[{'type': '[副]', 'def': '很、非常。表示程度深...

>>> word = PediaDictionary.get_one("囫")
>>> word.has_meaning
False
>>> word.annotations
['完整、整個。']
>>> word.meanings
[{'def': '參見「囫圇」條。'}]
>>> word.meta
{'bopomofo': 'ㄏㄨˊ', 'pinyin': 'hú', 'definitions': [{'def': '參見「囫圇」條。'}]}
```

## A meaning

```python
>>> meaning = word.meanings[0]
>>> meaning
{'type': '[形]', 'def': '美、善 ...
>>> meaning.pos
'形'
>>> meaning.full
'美、善，理想的。如：「好東西」...
>>> meaning.annotation
'美、善，理想的。'
```

## Dictionary based idiom segmentation

> I implement it by using pedia-cloud dictionary.  
> This will be slow for long sentence due to api call.

```python
>>> from pedia_cloud import PediaDictionary
>>> PediaDictionary.segment("一鳴驚人")
['一', '鳴', '驚人']
>>> PediaDictionary.segment("匯集了世界各地的新聞來源")
['匯集', '了', '世界', '各', '地', '的', '新聞來源']
```