Metadata-Version: 2.1
Name: ar-corrector
Version: 1.1.4
Summary: Arabic Spelling Correction
Home-page: UNKNOWN
Author: Bassel Kassem
Author-email: bassel.kassem.job@gmail.com
License: UNKNOWN
Download-URL: https://github.com/basselkassem/ar_corrector/archive/refs/tags/v1.1.4
Project-URL: Bug Reports, https://github.com/basselkassem/ar_corrector/issues
Project-URL: Funding, https://donate.pypi.org
Project-URL: Say Thanks!, https://github.com/basselkassem
Project-URL: Source, https://github.com/basselkassem/ar_corrector
Keywords: NLP,Spellingcheck
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.6, <4
Description-Content-Type: text/markdown
Requires-Dist: requests

# Description
Simple library to check the spelling of arabic sentences. This library uses a vocabulary that consists of +500K words, and uses 1-edit_distance and 2-edit_distance to correct the misspelled words. It also uses 1-ngram language model to correct the words depending on the previous context.
# Installation
```
pip install ar-corrector
```
# Usage
## Correct word spelling
```python
from ar_corrector.corrector import Corrector
corr = Corrector()

corr.spell_correct('بختب') # return 5 corrections with top frequencies
# [('بكتب', 61), ('برتب', 22), ('بختم', 21), ('بختي', 9), ('بخت', 7)]

corr.spell_correct('بختب', 2) # return 2 corrections with top frequencies
# [('بكتب', 61), ('برتب', 22),]

corr.spell_correct('بختب', 1) # return 1 correction with top frequency
# [('بكتب', 61)]

corr.spell_correct('لتمشتلميتلكب', 4) # return the same word
# لتمشتلميتلكب

corr.spell_correct('من') # return true
# True
```
## Correct word spelling using the context
```python
from ar_corrector.corrector import Corrector
corr = Corrector()

sent = 'أكدت قواءص التمذد في تشاد أنها تواضضل طريقها للعاحمة'
print(corr.contextual_correct(sent)) 
#أكدت قوات التمرد في تشاد أنها تواصل طريقها للعاصمة

sent = 'اتتنتهى حدث آبل المنتظو بالإعلاخ عن مموعة من المنتجات'
print(corr.contextual_correct(sent))
#انتهى حدث آبل المنتظر الإعلان عن مجموعة من المنتجات
```

