mrchocoborider

  def sort_scores(unsorted_scores, highest_possible_score):
    # List of 0s at indices 0..highest_possible_score
    score_counts = [0] * (highest_possible_score+1)

    # Populate score_counts
    for score in unsorted_scores:
        score_counts[score] += 1

    # Populate the final sorted list
    sorted_scores = []

mrchocoborider

#define the function
def sort_scores(us, hps):
    #Initialize the buckets array, a 0 for each entry from 0-100 (the highest possible score)
    counter = [0] * (hps + 1)
    #loop through the unsorted scores and add one to the counter array where
    #the index is equal to the value of the score.
    for i in us:
        counter[i] += 1
    
    #Initialize sorted list with the same length as the unsorted list

mrchocoborider

def get_max_profit(stock_prices):
    if len(stock_prices) < 2:
        raise ValueError('Getting a profit requires at least 2 prices')
    # We'll greedily update min_price and max_profit, so we initialize
    # them to the first price and the first possible profit
    min_price = stock_prices[0]
    max_profit = stock_prices[1] - stock_prices[0]
    # Start at the second (index 1) time
    # We can't sell at the first time, since we must buy first,
    # and we can't buy and sell at the same time! # If we started at index 0,

mrchocoborider

#Set the max profit to -infinity, because if the first possible trade is a loss (negative #) 
#we still want to keep track of it, and since we're checking if the potential profit is greater,
#-infinity is guaranteed to be smaller than any possible loss.
mp = float('-inf')

def get_max_profit(sp):
    for i, s in enumerate(sp):
        for j in range(i + 1, len(sp)):
            p = sp[j] - sp[i]
            if p > mp:

mrchocoborider

license: mit
scrolling: yes

mrchocoborider

license: mit

mrchocoborider

license: mit
scrolling: yes

mrchocoborider

license: mit