Metadata-Version: 1.1
Name: asmai
Version: 0.1
Summary: Asmai: (Al'asma'i) Arabic semantic analysis library for Python
Home-page: http://asmai.sourceforge.net/
Author: Taha Zerrouki
Author-email: taha.zerrouki@gmail.com
License: GPL
Description: Asmai: (Al'asma'i) Arabic semantic analysis
        ===========================================
        
        مكتبة الأصمعي الدلالية
        ======================
        
        Asmai: (Al'asma'i) Arabic semantic analysis library for Python
        
        .. figure:: doc/asmai_header.png
           :alt: asmai logo
        
           asmai logo
        
        .. figure:: https://img.shields.io/pypi/dm/asmai
           :alt: PyPI - Downloads
        
           PyPI - Downloads
        
        Developpers: Taha Zerrouki: http://tahadz.com taha dot zerrouki at gmail
        dot com
        
        +-------------+--------------------------------------------------------------------------------------------+
        | Features    | value                                                                                      |
        +=============+============================================================================================+
        | Authors     | `Authors.md <https://github.com/linuxscout/asmai-arabic-semantic/master/AUTHORS.md>`__     |
        +-------------+--------------------------------------------------------------------------------------------+
        | Release     | 0.1                                                                                        |
        +-------------+--------------------------------------------------------------------------------------------+
        | License     | `GPL <https://github.com/linuxscout/asmai-arabic-semantic/master/LICENSE>`__               |
        +-------------+--------------------------------------------------------------------------------------------+
        | Tracker     | `linuxscout/asmai/Issues <https://github.com/linuxscout/asmai-arabic-semantic/issues>`__   |
        +-------------+--------------------------------------------------------------------------------------------+
        | Source      | `Github <http://github.com/linuxscout/asmai-arabic-semantic>`__                            |
        +-------------+--------------------------------------------------------------------------------------------+
        | Feedbacks   | `Comments <https://github.com/linuxscout/asmai-arabic-semantic/>`__                        |
        +-------------+--------------------------------------------------------------------------------------------+
        | Accounts    | [@Twitter](https://twitter.com/linuxscout)                                                 |
        +-------------+--------------------------------------------------------------------------------------------+
        
        Description
        -----------
        
        Asmai: (Al'asma'i) Arabic semantic analysis library for Python
        
        مزايا:
        ~~~~~~
        
        -  استخلاص ثنائيات الكلمات التي تحمل دلالات من نوع : (فاعلية، مفعولية،
           إضافة)
        
        
        install
        ~~~~~~~
        
        .. code:: shell
        
            pip install asmai
        
        Usage
        ~~~~~
        
        import
        ^^^^^^
        
        .. code:: python
        
            pip install asmai
        
        Test
        ^^^^
        
        .. code:: python
        
            import asmai.anasem as asm
            text  =  u"يعبد الله منذ أن تطلع الشمس"
            result  =  []
            anasem  =  asm.SemanticAnalyzer()    
            result  =  anasem.analyze_text(text)
            # the result contains objets
            anasem.pprint(result)
        
        -  Extract semantic relation, display only found relations
        
        .. code:: python
        
            >>> import pprint
            >>> sem_result = anasem.display_sem(result)
            >>> pprint.pprint(sem_result)      
            [[['الشَّمْسُ', 'تَطْلُعَ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
              ['الشَّمْسُ', 'تَطْلُعُ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
              ['الشَّمْسُ', 'تَطْلُعْ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
              ['الشَّمْسُ', 'تَطْلَعَ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
              ['الشَّمْسُ', 'تَطْلَعُ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
              ['الشَّمْسُ', 'تَطْلَعْ', 'شَمْسٌ', 'طَلَعَ', 'Subject']]]
        
        -  Extract semantic relation, display all words and tags
        
           .. code:: python
        
               >>> sem_result = anasem.display_sem(result, all=True)
               >>> pprint.pprint(sem_result)
               [('يعبد', 'O', []),
                ('الله', 'O', []),
                ('منذ', 'O', []),
                ('أن', 'O', []),
                ('تطلع', 'B', []),
                ('الشمس',
                 'I',
                 [['الشَّمْسُ', 'تَطْلُعَ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
                  ['الشَّمْسُ', 'تَطْلُعُ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
                  ['الشَّمْسُ', 'تَطْلُعْ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
                  ['الشَّمْسُ', 'تَطْلَعَ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
                  ['الشَّمْسُ', 'تَطْلَعُ', 'شَمْسٌ', 'طَلَعَ', 'Subject'],
                  ['الشَّمْسُ', 'تَطْلَعْ', 'شَمْسٌ', 'طَلَعَ', 'Subject']])]
               >>> 
        
        -  convert to pandas \`\`\`python >>> import pandas as pd >>> >>> #
           flatten the result ... df = pd.DataFrame(anasem.decode(result)) >>>
           print(df.head()) action affix affix\_key forced\_word\_case ...
           unvocalized unvoriginal vocalized word 0 -ي-- -ي--\|المضارع
           المنصوب:هو:y False ... يعبد عبد يُعَبِّدَ يعبد 1 -ي-- -ي--\|المضارع
           المجهول المجزوم:هو:y False ... يعبد عبد يُعَبَّدْ يعبد 2 -ي--
           -ي--\|المضارع المجهول:هو:y False ... يعبد عبد يُعَبَّدُ يعبد 3 -ي--
           -ي--\|المضارع المعلوم:هو:y False ... يعبد عبد يُعَبِّدُ يعبد 4 -ي--
           -ي--\|المضارع المجزوم:هو:y False ... يعبد عبد يُعَبِّدْ يعبد
        
        [5 rows x 50 columns] >>> df.to\_csv("output/test.csv", encoding="utf8",
        sep=":raw-latex:'\t'")
        
        
        
        [requirement]
        ^^^^^^^^^^^^^
        
        ::
        
            1- pyarabic 
            2. sqlite
            3. sylajone
        
        Data Structure:
        ---------------
        
        Semantic database
        ~~~~~~~~~~~~~~~~~
        
        .. code:: sql
        
            CREATE TABLE sqlite_sequence(name,seq);
            CREATE TABLE "derivations" (
                "id" INTEGER PRIMARY KEY  AUTOINCREMENT  NOT NULL  UNIQUE ,
                "verb" varchar NOT NULL ,
                "transitive" BOOL NOT NULL  DEFAULT 1,
                "derived" VARCHAR NOT NULL ,
                "type" VARCHAR NOT NULL 
             );
        
        CSV Structure:
        
        -  Derivattion
        
        1. id : id unique in the database
        2. verb : vocalized collocation
        3. transtive : if the verb is transitive
        4. derived : derived word from verb number
        5. type : type
        
        Semantic relations
        ^^^^^^^^^^^^^^^^^^
        
        .. code:: sql
        
            CREATE TABLE "relations" (
                "id" INTEGER PRIMARY KEY  NOT NULL ,
                first" VARCHAR NOT NULL  DEFAULT ('') ,
                "second" VARCHAR NOT NULL  DEFAULT ('') ,
                "rule" VARCHAR NOT NULL  DEFAULT (0) 
             );
        
        CSV Structure:
        
        1. id : id unique in the database
        2. first: first word
        3. second: second word
        4. rule : the extraction rule number :
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: End Users/Desktop
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
