def cosine_join(ltable, rtable, l_key_attr, r_key_attr, l_join_attr,
    r_join_attr, tokenizer, threshold, comp_op='>=', allow_empty=True,
    allow_missing=False, l_out_attrs=None, r_out_attrs=None, l_out_prefix=
    'l_', r_out_prefix='r_', out_sim_score=True, n_jobs=1, show_progress=True):
    """Join two tables using a variant of cosine similarity known as Ochiai     
    coefficient.                                                                
                                                                                
    This is not the cosine measure that computes the cosine of the angle        
    between two given vectors. Rather, it is a variant of cosine measure known  
    as Ochiai coefficient (see the Wikipedia page                               
    `Cosine Similarity <https://en.wikipedia.org/wiki/Cosine_similarity>`_).    
    Specifically, for two sets X and Y, this measure computes:                  
                                                                                
        :math:`cosine(X, Y) = \\frac{|X \\cap Y|}{\\sqrt{|X| \\cdot |Y|}}`      
                                                                                
    In the case where one of X and Y is an empty set and the other is a         
    non-empty set, we define their cosine score to be 0. In the case where both 
    X and Y are empty sets, we define their cosine score to be 1.               
                                                                                
    Finds tuple pairs from left table and right table such that the cosine      
    similarity between the join attributes satisfies the condition on input     
    threshold. For example, if the comparison operator is '>=', finds tuple     
    pairs whose cosine similarity between the strings that are the values of    
    the join attributes is greater than or equal to the input threshold, as     
    specified in "threshold".                                                   
                                                                                
    Args:                                                                       
        ltable (DataFrame): left input table.                                   
                                                                                
        rtable (DataFrame): right input table.                                  
                                                                                
        l_key_attr (string): key attribute in left table.                       
                                                                                
        r_key_attr (string): key attribute in right table.                      
                                                                                
        l_join_attr (string): join attribute in left table.                     
                                                                                
        r_join_attr (string): join attribute in right table.                    
                                                                                
        tokenizer (Tokenizer): tokenizer to be used to tokenize join            
            attributes.                                                         
                                                                                
        threshold (float): cosine similarity threshold to be satisfied.         
                                                                                
        comp_op (string): comparison operator. Supported values are '>=', '>'   
            and '=' (defaults to '>=').           

        allow_empty (boolean): flag to indicate whether tuple pairs with empty  
            set of tokens in both the join attributes should be included in the 
            output (defaults to True).                                          
                                                                                
        allow_missing (boolean): flag to indicate whether tuple pairs with      
            missing value in at least one of the join attributes should be      
            included in the output (defaults to False). If this flag is set to  
            True, a tuple in ltable with missing value in the join attribute    
            will be matched with every tuple in rtable and vice versa.          
                                                                                
        l_out_attrs (list): list of attribute names from the left table to be   
            included in the output table (defaults to None).                    
                                                                                
        r_out_attrs (list): list of attribute names from the right table to be  
            included in the output table (defaults to None).                    
                                                                                
        l_out_prefix (string): prefix to be used for the attribute names coming 
            from the left table, in the output table (defaults to 'l\\_').       
                                                                                
        r_out_prefix (string): prefix to be used for the attribute names coming 
            from the right table, in the output table (defaults to 'r\\_').      
                                                                                
        out_sim_score (boolean): flag to indicate whether similarity score      
            should be included in the output table (defaults to True). Setting  
            this flag to True will add a column named '_sim_score' in the       
            output table. This column will contain the similarity scores for the
            tuple pairs in the output.                                          
                                                                                
        n_jobs (int): number of parallel jobs to use for the computation        
            (defaults to 1). If -1 is given, all CPUs are used. If 1 is given,  
            no parallel computing code is used at all, which is useful for      
            debugging. For n_jobs below -1, (n_cpus + 1 + n_jobs) are used      
            (where n_cpus is the total number of CPUs in the machine). Thus for 
            n_jobs = -2, all CPUs but one are used. If (n_cpus + 1 + n_jobs)    
            becomes less than 1, then no parallel computing code will be used   
            (i.e., equivalent to the default).                                                                                 
                                                                                
        show_progress (boolean): flag to indicate whether task progress should  
            be displayed to the user (defaults to True).                        
                                                                                
    Returns:                                                                    
        An output table containing tuple pairs that satisfy the join            
        condition (DataFrame).                                                  
    """
    from py_stringsimjoin import __use_cython__
    if __use_cython__:
        from py_stringsimjoin.join.cosine_join_cy import cosine_join_cy
        return cosine_join_cy(ltable, rtable, l_key_attr, r_key_attr,
            l_join_attr, r_join_attr, tokenizer, threshold, comp_op,
            allow_empty, allow_missing, l_out_attrs, r_out_attrs,
            l_out_prefix, r_out_prefix, out_sim_score, n_jobs, show_progress)
    else:
        from py_stringsimjoin.join.cosine_join_py import cosine_join_py
        return cosine_join_py(ltable, rtable, l_key_attr, r_key_attr,
            l_join_attr, r_join_attr, tokenizer, threshold, comp_op,
            allow_empty, allow_missing, l_out_attrs, r_out_attrs,
            l_out_prefix, r_out_prefix, out_sim_score, n_jobs, show_progress)
