import pandas as pd

def distribute_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols: list):
    
    for slack_var in range(1, 20):
        concat_portfolio = pd.DataFrame(columns=portfolio.columns)

        for finishing_range in range(1, 20):
            finish_threshold = (finishing_range / 100)
            lower_threshold = ((finishing_range - 1) / 100)
            rows_to_drop = []
            working_portfolio = portfolio.copy()
            if finishing_range == 1:
                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] <= finish_threshold]
            elif finishing_range == 20:
                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] >= lower_threshold]
            else:
                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] <= finish_threshold]
                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] >= lower_threshold]
            working_portfolio = working_portfolio.sort_values(by='median', ascending = False)
            working_portfolio = working_portfolio.reset_index(drop=True)
            if len(working_portfolio) == 0:
                continue
            elif len(working_portfolio) >= 1:
                curr_own_type_max = working_portfolio.loc[0, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[0, 'Weighted Own'])

                for i in range(1, len(working_portfolio)):
                    if working_portfolio.loc[i, 'Weighted Own'] > curr_own_type_max:
                        rows_to_drop.append(i)
                    else:
                        curr_own_type_max = working_portfolio.loc[i, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[i, 'Weighted Own'])
                
                working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True)
                concat_portfolio = pd.concat([concat_portfolio, working_portfolio.head(10)])

        if len(concat_portfolio) >= lineup_target:
            return concat_portfolio.sort_values(by='Finish_percentile', ascending=True).head(lineup_target)
        
    return concat_portfolio.sort_values(by='Finish_percentile', ascending=True)