nlptoolkit-spellchecker-cy 1.0.15

Turkish Spell Checker ============

    This tool is a spelling checker for Modern Turkish. It detects spelling errors and corrects them appropriately, through its list of misspellings and matching to the Turkish dictionary.
    
    Video Lectures
    ============
    
    [<img src="https://github.com/StarlangSoftware/TurkishSpellChecker/blob/master/video.jpg" width="50%">](https://youtu.be/wKwTKv6Jlo0)
    
    For Developers
    ============
    
    You can also see [Python](https://github.com/starlangsoftware/TurkishSpellChecker-Py), [Java](https://github.com/starlangsoftware/TurkishSpellChecker), [C++](https://github.com/starlangsoftware/TurkishSpellChecker-CPP), [C](https://github.com/starlangsoftware/TurkishSpellChecker-C), [Swift](https://github.com/starlangsoftware/TurkishSpellChecker-Swift), [Js](https://github.com/starlangsoftware/TurkishSpellChecker-Js), or [C#](https://github.com/starlangsoftware/TurkishSpellChecker-CS) repository.
    
    ## Requirements
    
    * [Python 3.7 or higher](#python)
    * [Git](#git)
    
    ### Python 
    
    To check if you have a compatible version of Python installed, use the following command:
    
        python -V
        
    You can find the latest version of Python [here](https://www.python.org/downloads/).
    
    ### Git
    
    Install the [latest version of Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git).
    
    ## Pip Install
    
    	pip3 install NlpToolkit-SpellChecker-Cy
    
    ## Download Code
    
    In order to work on code, create a fork from GitHub page. 
    Use Git for cloning the code to your local or below line for Ubuntu:
    
    	git clone <your-fork-git-link>
    
    A directory called SpellChecker will be created. Or you can use below link for exploring the code:
    
    	git clone https://github.com/starlangsoftware/TurkishSpellChecker-Cy.git
    
    ## Open project with Pycharm IDE
    
    Steps for opening the cloned project:
    
    * Start IDE
    * Select **File | Open** from main menu
    * Choose `DataStructure-CY` file
    * Select open as project option
    * Couple of seconds, project will be downloaded. 
    
    Detailed Description
    ============
    
    + [Creating SpellChecker](#creating-spellchecker)
    + [Spell Correction](#spell-correction)
    
    ## Creating SpellChecker
    
    SpellChecker finds spelling errors and corrects them in Turkish. There are two types of spell checker available:
    
    * `SimpleSpellChecker`
        
        * To instantiate this, a `FsmMorphologicalAnalyzer` is needed. 
            
                fsm = FsmMorphologicalAnalyzer()
                spellChecker = SimpleSpellChecker(fsm)   
         
    * `NGramSpellChecker`,
        
        * To create an instance of this, both a `FsmMorphologicalAnalyzer` and a `NGram` is required. 
        
        * `FsmMorphologicalAnalyzer` can be instantiated as follows:
            
                fsm = FsmMorphologicalAnalyzer()
        
        * `NGram` can be either trained from scratch or loaded from an existing model.
            
            * Training from scratch:
                    
                    corpus = Corpus("corpus.txt");
                    ngram = NGram(corpus.getAllWordsAsArrayList(), 1)
                    ngram.calculateNGramProbabilities(LaplaceSmoothing())
                    
            *There are many smoothing methods available. For other smoothing methods, check [here](https://github.com/olcaytaner/NGram).*       
            * Loading from an existing model:
         
                    ngram = NGram("ngram.txt")
    
    	*For further details, please check [here](https://github.com/starlangsoftware/NGram).*        
                
        * Afterwards, `NGramSpellChecker` can be created as below:
            
                spellChecker = NGramSpellChecker(fsm, ngram)
         
    
    ## Spell Correction
    
    Spell correction can be done as follows:
    
        sentence = Sentence("Dıktor olaç yazdı")
        corrected = spellChecker.spellCheck(sentence)
        print(corrected)
        
    Output:
    
        Doktor ilaç yazdı