Metadata-Version: 2.1
Name: PyShbak
Version: 0.2
Summary: SHAWPACK NLP processing package
Home-page: https://github.com/AbdelrahmanShahrour/PyShbak
Author: AbdelrahmanShahrour
License: UNKNOWN
Keywords: NLP,text-data,AI,DS,Shahrour,arabic-py,arabic-nlp
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: click (==8.1.3)
Requires-Dist: joblib (==1.2.0)
Requires-Dist: nltk (==3.7)
Requires-Dist: regex (==2022.10.31)
Requires-Dist: tqdm (==4.64.1)

# PyShbak
 ![image](https://github.com/AbdelrahmanShahrour/PyShbak/blob/main/logo/SHAWPACK-LOGO.png?raw=true) 

###  Now with PyShbak, dealing with Arabic texts has become easy, and in the future it will become easier with PyShbak 

## Installation

```python
pip3 install PyShbak
```
---
## Structure 

|> PyShbak

| ------> | `Normalization`

|---------| ------> | `Normalization_ar`

|---------|---------| ------> | alef

|---------|---------| ------> | lamalef

|---------|---------| ------> | hamza

|---------|---------| ------> | tah

|---------|---------| ------> | madah

|---------|---------| ------> | normalization_all

| ------> `Processor`

|---------| ------> | `Arabic_Processor`

|---------|---------| ------> | remove_stopword

|---------|---------| ------> | remove_other_lang

|---------|---------| ------> | remove_diacritics

|---------|---------| ------> | remove_arabic_punctuations

|---------|---------| ------> | arabic_only

|---------|---------| ------> | with_out_num

|---------| ------> | `English_Processor`

|---------|---------| ------> | remove_stopword

|---------|---------| ------> | english_only

|---------|---------| ------> | remove_english_punctuations

|---------|---------| ------> | with_out_num

|---------| ------> | `General_Processor`

|---------|---------| ------> | remove_mentions

|---------|---------| ------> | remove_hasgtag

|---------|---------| ------> | remove_links

|---------|---------| ------> | remove_punctation

|---------|---------| ------> | keep_text

|---------|---------| ------> | remove_emojis

|---------|---------| ------> | remove_whitespace

|---------| ------> | `cleaningtext`

|---------|---------| ------> | delete_repeated_characters

|---------|---------| ------> | replace_letters

|---------|---------| ------> | clean_text

|---------|---------| ------> | remove_vowelization

|---------|---------| ------> | remove_stopword

|---------|---------| ------> | stem_text

|---------|---------| ------> | text_prepare

---

## Example:

```python
pip3 install PyShbak
```

```python
from PyShbak.TweetsCleaner import Clean_tweet
```



```python
text = 'akhhh !تَوقَعْت إذا جات داريا بشوفهم كاملين بس لي للحين احس فيه احد ناقْصهم 💔 #Avlu https://www.messenger.com/ @PyShbak '

Clean_tweet.ar(text)
```

output:
`' توقعت اذا جات داريا بشوفهم كاملين بس لي للحين احس فيه احد ناقصهم '
`

