Metadata-Version: 2.1
Name: wordslicer
Version: 0.1.0
Summary: A tool to separate truncated text.
Home-page: https://github.com/bishop19/wordslicer
Author: Pedro Moreira, Nelson Sousa
Author-email: a82364@alunos.uminho.pt, a82053@alunos.uminho.pt
License: UNKNOWN
Description: Word Slicer
        ==========
        
        Cut your unspaced (or 'too spaced') long texts.
        
        
        
        Usage
        -----
        ```python
        import wordslicer
        
        model = wordslicer.train('train_file')
        text = open('input_file', 'r').read()
        text = wordslicer.separate(model, text) # or wordslicer.join(model, text)
        save('output_file', text)
        ```
        
        Performance
        -----------
        
        For an input of:
        * 161029 words to train
        * 1000 lines to separate
        
        The results:
        * Text with 36889 words
        * Time: real    0m1,368s
        
        
        Example:
        ```
        >>> wordslicer.separate(model, "Boromirhesitatedforasecond.'Yes,andno,'heansweredslowly.'Yes:Ifoundhimsomewayupthehill,andIspoketohim.IurgedhimtocometoMinasTirithandnottogoeast.Igrewangryandheleftme.Hevanished.Ihaveneverseensuchathinghappenbefore.thoughIhaveheardofitintales.HemusthaveputtheRingon.Icouldnotfindhimagain.Ithoughthewouldreturntoyou.'")
        
        Boromir hesitated for a second. 'Yes, and no,' he answered slowly. 'Yes: I found him some way up the hill, and I spoke to him. I urged him to come to Minas Tirith and not to go east. I grew angry and he left me. He vanished. I have never seen such a thing happen before. though I have heard of it in tales. He must have put the Ring on. I could not find him again. I though the would return to you.'
        ```
        
        
        How to Install
        --------------
        
        ```
        pip3 install wordslicer
        ```
        
        Features
        ----------------------
        
        * Train your model: with the training ability, this package works with every language.
        
        * Evaluate your model: check if your training text is good enough for your input text:
        
        ![image](https://i.imgur.com/bnEqlEP.png)
        
        
        Credits
        ----------------------
        This project was inspired by Generic Human on http://stackoverflow.com/a/11642687/2449774 . 
        Thank you!
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
