Metadata-Version: 1.1
Name: labels2tables
Version: 0.1.0
Summary: Turns bibtex keywords into an academic summary table
Home-page: https://github.com/anjsimmo/labels2tables
Author: Andrew Simmons
Author-email: anjsimmo@gmail.com
License: MIT
Description: Labels To Tables
        ========================
        
        labels2tables extracts keywords from a bibtex file, and uses them to generate an academic summary table comparing the articles.
        
        Example
        --------
        
        Input:
        
        ::
        
          @article{duch_quantifying_2010,
                   keywords = {game:soccer, model:network:centrality, open-access}}
          @article{yamamoto_common_2011,
                   keywords = {game:soccer, model:network:scale-free, open-access}}
          @article{yaari_hot_2011,
                   keywords = {game:basketball, model:sequence, open-access}}
        
        Transformation:
        
        ::
        
          import labels2tables
          labels = labels2tables.bib2labels("examples/sport.in.bib")
          labels2tables.labels2txt(labels, "examples/sport.out.txt")
        
        Output:
        
        ::
        
          ========================================================
          game       model       open-access reference            
          ========================================================
          soccer     network                                      
                      centrality Y           duch_quantifying_2010
                      scale-free Y           yamamoto_common_2011 
          basketball sequence    Y           yaari_hot_2011       
          ========================================================
        
        Advanced
        --------
        The intermediate labels format encodes table data using standard Python dictionaries, lists and tuples. See `examples/*.spec.txt` for example tables, and how to describe them as a labels dictionary.
        
        Acknowledgements
        ----------------
        Powered by `bibtexparser`
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Text Processing :: Markup
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
