We are working on a Python program where we need to calculate combinations over four different variables: ‘lp’, ‘futures’, ‘option_long’, and ‘option_short’. The ‘lp’ variable should iterate within the range defined by ‘lp_min’ and ‘lp_max’. However, we have specific constraints that need to be considered:

‘lp’ values must be generated from smaller to larger numbers.
Numbers cannot be repeated within a combination.
Our objective is to find the best combination for our model. We plan to execute this later in the program, where we save all the combinations generated. Meanwhile, the other three variables (‘futures’, ‘option_long’, and ‘option_short’) can all be the same within a combination, and their values can be in random order.

We need assistance in implementing a Python function that can generate these combinations while adhering to the specified constraints. Specifically, we’re looking for guidance on how to structure the iteration over ‘lp’ values and how to ensure that the combinations meet the given constraints. I have tried multiple options but lp’s is not generating right way. this is my last try:

Thank you for your help!

def find_best_combination(lp_min, lp_max, budget, tables_by_expiration):
    """ Find the best combination of parameters for each expiration date given a budget and tables of options data """
    
    try:
        best_combinations = {}  # Dictionary to store the best combinations of parameters for each expiration date
        
        for expiration_date, tables_by_exp in tables_by_expiration.items():
            # Initialize minimum deviation and best combination for the current expiration date
            min_deviation_exp = float('inf')
            best_combination_exp = None
            
            # Initialize lists to store the best combination for each LP position
            lp_list, futures_list, opt_long_list, opt_short_list = [], [], [], []
            
            # Fetch strikes
            strikes = [row['strike'] for _, row in tables_by_exp.iterrows()]
            
            for strike in strikes:
                # Initialize best combination for the current strike
                best_combination_strike = None
                min_deviation_strike = float('inf')
                
                # Loop over LP positions within the range of lp_min and lp_max
                for lp_position in range(lp_min, lp_max + 1):
                    lp_cost = calculate_cost(lp_position, budget_percent, df_market)
                    if lp_cost > budget:
                        print(f"{lp_position} LP cost exceeds budget for strike {strike}")
                        break  # Break if LP cost exceeds the budget
                        
                    # Generate combinations of futures, option_long, and option_short
                    for futures, opt_long, opt_short in itertools.product(range(1, 11), range(1, 11), range(1, 11)):
                        if lp_position < futures < opt_long < opt_short < lp_max:  # Ensuring LP position is smaller
                            if len(set([lp_position, futures, opt_long, opt_short])) == 4:
                                # Calculate deviation
                                deviation = abs(lp_cost - (futures + opt_long + opt_short))
                                if deviation < min_deviation_strike:
                                    min_deviation_strike = deviation
                                    best_combination_strike = (lp_position, futures, opt_long, opt_short)
                
                # Append the best combination for the current strike
                if best_combination_strike:
                    lp_list.append(best_combination_strike[0])
                    futures_list.append(best_combination_strike[1])
                    opt_long_list.append(best_combination_strike[2])
                    opt_short_list.append(best_combination_strike[3])
            
            # Store the best combination and minimum deviation for the current expiration date
            best_combinations[expiration_date] = {
                'lp': lp_list,
                'futures': futures_list,
                'opt_long': opt_long_list,
                'opt_short': opt_short_list,
                'min_deviation': min_deviation_strike
            }

        return best_combinations
    
    except Exception as e:
        print(f"Error in find_best_combination: {e}")
        return None