Metadata-Version: 2.1
Name: best-choice
Version: 0.0.1
Summary: Algorithm for best choice
Home-page: https://github.com/claudiotorresarbe/best-choice
Author: Claudio Torres Arbe
Author-email: claudiotarbe@gmail.com
License: UNKNOWN
Description: # best-choice
        ## 1 - pip Install
        ```
        pip install best-choice
        ```
        ## 2 - all function
        ```
        #library
        from bestchoice import Generate
        
        #data
        #object,price,importance level
        table = [['pants',75,10],
                 ['jeans',50,7],
                 ['shirt',45,8],
                 ['dress',65,7],
                 ['ball',25,5]]
        
        #call function generate
        gen = Generate(table)
        
        #all possibilities
        for x in gen.list_all():
          print(x)
        
        #call function to generate calculation results
        #parameters 1 and 2 are columns for calculation
        #in this case, the price and importance level
        calc = gen.list_results([1,2])
        
        #all calculated results
        for x in calc:f
          print(x)
        
        #new table after filter
        #the first parameter 1 and 2 are index columns
        #the second parameter 1 <= 200 filter your new table  
        new = gen.list_best([1,2],[[1,'<=',200]])
        
        #all filtered results
        for x in new:
          print(x)
        ```
        
        ## 3 - example to find best choice
        ```
        #library
        from bestchoice import Generate
        
        #data
        #object,price,importance level
        table = [['pants',75,10],
                 ['jeans',50,7],
                 ['shirt',45,8],
                 ['dress',65,7],
                 ['ball',25,5]]
        
        #column for calculation
        #in this case, the price and importance level
        columns = [1,2]
        
        #index of column importance
        importance = 2
        
        #filters where 1 is the price <= 200 dollars
        filters = [[1,'<=',200]]
        
        #call function generate
        gen = Generate(table)
        
        #get all possibilities
        lista = gen.list_all()
        
        #new table after filter
        #the first parameter 1 and 2 are index columns
        #the second parameter 1 <= price filter your new table 
        res = gen.list_best(columns,filters)
        
        #saves the best filtered result
        top = max([sublist[-1] for sublist in res])
        
        filters.append([importance,'==',top])
        #table with new result
        new = gen.list_best(columns,filters)
        
        #set index of top values
        best = [x[0] for x in new][0]
        
        #result
        print(f'This is your best choice: {", ".join([str(x[0]) for x in lista[best]])}')
        
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
