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Code Jam 2008 Round 1A, Problem B: Milkshakes




You want to make N batches of milkshakes, so that:

  • The minimum possible number of batches are malted.





  customers = [] # Start empty customer list

    customer = []
      malted = custList.pop(0) # Second element is malted preference
      customer.append(flavor, malted) # Add preference to customer

    customers.append(customer) # When done, add customer to list

  impossible = False
  solved = False
  while not impossible and not solved: # While not finished
    redo = False
    for customer in customers: # Examine all customers
      unsatisfied = []
      for flavor, malt in customer: # Examine all their preferences
          unsatisfied = []
        else: # If unsatisfied, take note of it
          unsatisfied.append([flavor, malt])

      for flavor, malt in unsatisfied: # Check unsatisfied flavors
          shakes[flavor] = 1 # Attend the malted preference
          redo = True # Restart checking customers

      if redo:

        impossible = True # Then we can't solve it




Code Jam 2008 Round 1A, Problem A: Minimum Scalar Product







  x.sort()                               # Sort both vectors
  y.sort()                               # And sort-reverse Y

  msp = 0



On unmantainable software



CodeJam trouble, hard problems ahead!




Difficult CodeJam problem and Free Software Documentary




Code Jam 2010 Africa – Problem C

Whoa, that was a tough problem. Ironically it’s called Qualification Round:

You’ve just advanced from the Qualification Round of Google Code Jam Africa 2010, and you want to know how many of your fellow contestants advanced with you. To give yourself a challenge, you’ve decided only to look at how many people solved each problem.

The Qualification Round consisted of P problems; the ith problem was fully solved by Scontestants. Contestants had to solve C problems in order to advance to the next round. Your job is to figure out, using only that information, the maximum number of contestants who could have advanced.

Well, at first it seems pretty simple, but there is quite some math involved. The first case of the example input is easy to solve, but the second will most likely get you scratching your head thinking “where the #$%* that number came from” (at least I did). 🙂 Well the secret is that you should not look at the inputs as they are, but instead, find the maximum amount of solved problem combinations there are.

I studied a bit but still could not solve it, and surrendered by checking the contest analysis. It was quite complicated to understand, until they wrote about a clever solution from the winning candidate: it consisted in lowering the possible scores to max at the division of the scores by the amount of needed problems. Just do it (don’t ask why) until there are no scores over the result of that division. That same result will be the answer. Creepy! Python code time:

    info = map(int, raw_input().split(" "))       # Get test case information
    problems = info[0]                            # Fetch number of problems
    needed = info[1]                              # Fetch number of needed problems to pass
    results = info[2:]                            # Fetch results for each problem

    qualified = 0                                 # Initialize our results

    if (problems == needed):                      # For this case, we can expect
        results.sort()                            # as many contestants as the
        qualified = results[len(results)-needed]  # least solved problem

    else:                                         # For this case, we use a solution
        out = False                               # similar to the winning one
        while not out:
            out = True
            qualified = sum(results)/needed       # Reduce the number of possible qualifiers
            for i in range(len(results)):         # And for all results
                if results[i] > qualified:        # Limit their values to the current qualifiers
                    results[i] = qualified
                    out = False                   # Until they all "match" the qualifiers number

    print "Case #%d: %s" % (case, str(qualified)) # Report results

Interestingly enough, this code is smaller than the last, and solves a more complicated problem (at least in my opinion). I don’t think I could have done a better job on this one. 🙂 That’s the beauty in learning!

CodeJam Quickie: 2010 Africa – Problem B

Howdy! This time, problems started getting more and more complex, and that’s good, because I like the challenge! The next problem is Get to Work:

You work for a company that has E employees working in town T. There are N towns in the area where the employees live. You want to ensure that everyone will be able to make it to work. Some of the employees are drivers and can drive P passengers. A capacity of P == 1 indicates that the driver can only transport themselves to work. You want to ensure that everyone will be able to make it to work and you would like to minimize the number of cars on the road.

You want to calculate the number of cars on the road, with these requirements:

  • Every employee can get to town T.
  • The only way an employee may travel between towns is in a car belonging to an employee.
  • Employees can only take rides from other employees that live in the same town.
  • The minimum number of cars is used.

Find whether it is possible for everyone to make it to work, and if it is, how many cars will end up driving to the office.

Whoa, that’s way more complex than the other problems, but still, not that hard! What we need to do is: check who are drivers and passengers for each town (since they can only help same town buddies), if the total capacity of cars from a town is inferior to the number of passengers, the problem cannot be solved and so, reported as “IMPOSSIBLE”. If we can carry everyone, start filling the cars from the “minivan” (can carry more passengers) to the “mini cooper”. 😀 That way we can make sure there are fewer cars on the road.

Some rough, but commented, and validated (!) python code follows:

    town_len, office = map(int, raw_input().split(" "))   # Get amount of towns and office

    carriers = [[] for x in xrange(town_len)]             # Create new lists for every town
    capacities = town_len * [0]                           # Initialize "capacity of transportation"
    payload = town_len * [0]                              # Initialize "cargo" for each town

    for i in range(int(raw_input())):                     # Get and go through employee list
        town, capacity = map(int, raw_input().split(" ")) # Get the current employee info
        if town == office:                                # If employee is from office town
            continue                                      #   No need to commute, ignore

        town -= 1                                         # Adjust "town" to zero-based index
        payload[town] += 1                                # Employee needs to commute, count

        if capacity != 0:                                 # If employee has a car
            capacities[town] += capacity                  # Add to our capacities for the town
            carriers[town].append(capacity)               # Append its car capacity

    resultStr = ""                                        # Create our result string

    for i in range(town_len):                             # For all towns
        if capacities[i] < payload[i]:                    # If we can't carry everyone
            resultStr = "IMPOSSIBLE "                     #   declare it impossible, give up

        cars = 0                                          # We can carry, start with 0 cars
        carriers[i].sort()                                # Sort and reverse the car list
        for car in carriers[i]:                           # So we can start from the bigger ones
            if (payload[i] <= 0):                         # If we're carrying everybody already
                break                                     #  we're done for this town

            payload[i] -= car                             # Else, fill a car, report as being used
            cars += 1

        resultStr += str(cars)+" "                        # Add this town filled vehicles

    print "Case #%d: %s" % (case, resultStr[:-1])         # Report results, remove last space

As the last problem, the same can be told about this code. There are many ways to improve its performance, but this way it can already solve the large inputs in an instant. Bitbangers apart, it solves the problem and everybody gets happy. Also, I think it is quite clear to understand, even more with the comments. 🙂 Bye!

CodeJam Quickie: 2010 Africa – Problem A

Hey there! So, another day, another problem! This time, it is called Odd Man Out, and it is quite simple to “get”:

You are hosting a party with G guests and notice that there is an odd number of guests! When planning the party you deliberately invited only couples and gave each couple a unique number C on their invitation. You would like to single out whoever came alone by asking all of the guests for their invitation numbers.

Well, just get the number that’s not duplicated! There are many ways to do this, be it counting the occurrences of every member of the list and finding the “odd man”, or the way I did, which is basically some push and pop into a new list. Python code follows:

    raw_input()                                 # Discard the guest list size
    guests = raw_input().split(" ")             # Get the list of guest IDs

    guestList = []                              # Create an empty guest list

    for guest in guests:                        # For all guests
        if guestList.count(guest) > 0:          # If it's already on the final list
            guestList.remove(guest)             #    if is a couple, remove
        else:                                   # If it's not in the list yet
            guestList.append(guest)             #    Add its ID

    print "Case #%d: %s" % (case, guestList[0]) # Reports results

Needless to say, I bet there are many ways to improve this algorithm, but for this problem it performs decently, so no worries (unless you’re a hardcore bit banger). 🙂 See you tomorrow!