adhaamehab / Textblob Ar
Licence: mit
Arabic support for textblob
Stars: ✭ 60
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=========== textblob-ar [WIP]
.. image:: https://travis-ci.org/adhaamehab/textblob-ar.svg?branch=master :target: https://travis-ci.org/adhaamehab/textblob-ar
Arabic language support for TextBlob_.
Features
- Tokenizer
- Sentiment analysis
- Stanford Arabic POS
- Spelling Correction
- Text similarity
- Fasttext arabic word2vec interface
Usage
Tokenizer
.. code-block:: python
>>> from textblob_ar import TextBlob
>>> blob = TextBlob(u"""هندسة البرمجيات هي دراسة تصميم وتنفيذ وتعديل البرمجيات بما يضمن توفر هذه البرمجيات بجودة عالية وتكلفة معقولة متاحة للجميع وقابلة للتطوير فيما بعد وسريعة للبناء. وهندسة البرمجيات تقوم على أسس ونظريات من الهندسة وعلوم الحاسب كمبدأ ال Functional Structure من الهندسة والذي يعتمد على مبدأ تصميم أجزاء صغيرة تتجانس في العمل مع بعضها لتشكل عمل الكل.""")
>>> blob.tokens
WordList(['هندسة', 'البرمجيات', 'هي', 'دراسة', 'تصميم', 'وتنفيذ', 'وتعديل', 'البرمجيات', 'بما', 'يضمن', 'توفر', 'هذه', 'البرمجيات', 'بجودة', 'عالية', 'وتكلفة', 'معقولة', 'متاحة', 'للجميع', 'وقابلة', 'للتطوير', 'فيما', 'بعد', 'وسريعة', 'للبناء', '.', 'وهندسة', 'البرمجيات', 'تقوم', 'على', 'أسس', 'ونظريات', 'من', 'الهندسة', 'وعلوم', 'الحاسب', 'كمبدأ', 'ال', 'Functional', 'Structure', 'من', 'الهندسة', 'والذي', 'يعتمد', 'على', 'مبدأ', 'تصميم', 'أجزاء', 'صغيرة', 'تتجانس', 'في', 'العمل', 'مع', 'بعضها', 'لتشكل', 'عمل', 'الكل', '.'])
Sentiment
.. code-block:: python
>>> from textblob_ar import TextBlob
>>> blob = TextBlob('اعجبني هذا الكتاب. اعترض قليلا مع بعض افكاره لكن مضمونه رائع')
>>> blob.sentiment
Sentiment(polarity=0.8, subjectivity=0.9)
>>> blob = TextBlob('لم يعجبني هذا الكتاب. مضمونه سئ')
>>> blob.sentiment
Sentiment(polarity=-0.6999999999999998, subjectivity=0.6666666666666666)
Stanford POS
Note that Stanford POS is the defualt one untill the main one is released .. code-block:: python
>>> from textblob_ar import TextBlob
>>> from textblob_ar.pos_tagger import StanfordPOSTagger
>>> tagg = StanfordPOSTagger()
>>> text = """ في أنظمة التشغيل متعددة المهام مثل اليونكس عفريت النظام هو برنامج يعمل في خلفية النظام بعيدا عن التحكم المباشر من المستحدم وغالبا ما يبدأ عمله كعملية خلفية مع بداية تشغيل النظام."""
>>> blob = TextBlob(text, pos_tagger=tagger)
>>> print(blob.tags)
[('', 'في/IN'), ('', 'أنظمة/NN'), ('', 'التشغيل/DTNN'), ('', 'متعددة/JJ'), ('', 'المهام/DTNN'), ('', 'مثل/NN'), ('', 'اليونكس/DTNNP'), ('', 'عفريت/NNP'), ('', 'النظام/DTNN'), ('', 'هو/PRP'), ('', 'برنامج/NN'), ('', 'يعمل/VBP'), ('', 'في/IN'), ('', 'خلفية/NN'), ('', 'النظام/DTNN'), ('', 'بعيدا/JJ'), ('', 'عن/IN'), ('', 'التحكم/DTNN'), ('', 'المباشر/DTJJ'), ('', 'من/IN'), ('', 'المستحدم/DTNN'), ('', 'وغالبا/NN'), ('', 'ما/WP'), ('', 'يبدأ/VBP'), ('', 'عمله/NN'), ('', 'كعملية/JJ'), ('', 'خلفية/NN'), ('', 'مع/NN'), ('', 'بداية/NN'), ('', 'تشغيل/NN'), ('', 'النظام/DTNN')]
Text Correction
Thanks for Peter Norvig http://norvig.com/spell-correct.html
.. code-block:: python
>>> from textblob_ar import TextBlob
>>> from textblob_ar.correction import TextCorrection
>>> text = 'الاذدهاز'
>>> TextCorrection().correct(text)
{'الاذهان', 'الازدهار', 'الادهان', 'الاندهاش'}
>>> TextCorrection().correct(text, top=True)
'الازدهاز'
Text Similarity
Based on gensim <https://radimrehurek.com/gensim>_ and Fasttext <https://fasttext.cc/docs/en/pretrained-vectors.html>_ pretrained word2vec model
The procedure used in calculating similarity is calculating mean feature vector for each sentence. Then calculate the cosine distance between those two vectors.
.. code-block:: python
>>> from textblob_ar import TextSimilarity
>>> sim = TextSimilarity()
# takes around 12 second (macbook pro 2017) to load the pretrained word2vec
>>> sent1 = u'الإرهابي الصالح هي رواية خيال سياسي للكاتبة دوريس ليسينج. ظهرت أول طبعة للرواية في سبتمبر من عام 1985 للناشرين جوناثان كيب في المملكة المتحدة وألفريد أ'
>>> sent2 = u'روايه الكاتبه دوريس ليسينج هي روايه خيال سياسي ظهرت في سبتمبر 1985 بعنوان الارهابي الصالح وتم نشرها عن طريق جوناثان كيب والفريد أ في انجلترا'
>>> sim.similarity(sent1, sent2)
0.9611366391181946
Requirements
- Python >= 3.3
Installation
- Development
.. code-block:: shell $ git clone https://github.com/adhaamehab/textblob-ar.git $ cd textblob_ar $ virtualenv -p python3 env $ source env/bin/activate $ pip install -Ur dev-requirements.txt
for text similarity download fasttext arabic word2vec pretrained model from here <https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md>_
TODO
- Part Of Speech tagger
- Noun-phrases extraction
- Parser
- Classification support
- Grammer
License
MIT licensed. See the bundled LICENSE <https://github.com/sloria/textblob-fr/blob/master/LICENSE>_ file for more details.
.. _TextBlob: https://textblob.readthedocs.org/
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