http://hyperpublic.com/challenge/complete

hyperpublic2011.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# http://hyperpublic.com/challenge
# 2011-02-26

# ==== ~ Q1 ==== #

# Hyperpublic users can add their friends by emailing a photo of them to
# [email protected]. We want to determine a user’s influence on the system by
# determining how many users he is responsible for. A user’s influence is
# calculated by giving him 1 point for every user he’s added in addition to the
# sum of the influence scores of each user that he’s added.
# 
# Example: User 0 adds User 1 and User 2. User 1 adds User 3.
# 
# User 0’s influence score is 3. (He added two users and one of them added added
# a third user.) User 1's is 1. User 2’s is 0. User 3’s is 0. The above scenario
# is represented by the following input file. Line i is user ID i and position j
# within the line is marked with an X if user ID i added user ID j. Both row and
# column indicies are 0-based:
# 
#  OXXO OOOX OOOO OOOO
# 
# Use the input file here to determine what the highest influence score is among
# 100 random Hyperpublic users. To compute the answer to problem 1, append the
# top 3 influence totals together in descending order. (For example if they are
# 17, 5, and 3 then submit 1753)

def users_added(userid, grid):
    return [ i for i, x in enumerate(grid[userid]) if x == "X" ]

def radiation(userid, grid):
    r = len(users_added(userid, grid))
    for added in users_added(userid, grid):
        r += radiation(added, grid)
    return r
    
def question_one():
    # grid = "OXXO\nOOOX\nOOOO\nOOOO".split('\n')
    # grid = open('challenge2input.txt', 'r').read().split('\n')
    import urllib
    grid = urllib.urlopen(
        "http://hyperpublic.com/challenge2input.txt").read().split('\n')
        
    print 'Answer question one:', ''.join(
        map(str, sorted(
            [ radiation(x, grid) 
                for x in range(len(grid)) ], reverse=True)[:3]))

# ==== ~ Q2 ==== #

# Hyperpublic has an internal karma system to determine which users are the most
# involved in the ecosystem. Users earn points for the following tasks.
# 
# 2 Points – Add Place 3 Points – Add Thing 17 Points – Tag Object 23 Points –
# Upload Photo 42 Points – Twitter Share 98 Points – Facebook Share Being
# addicted to their own product, the Hyperpublic staff has racked up some big
# karma. The members of the team have the following karma totals:
# 
# Doug – 2349 points Jordan – 2102 points Eric – 2001 points Jonathan – 1747
# points Amazingly, they've all accomplished these totals in the minimum number
# of tasks possible in order to reach each amount. For example, if their total
# was 6 points they would have accomplished this in just 2 tasks (2 "Add Thing"
# tasks), as opposed to accomplishing it by 3 "Add Place" tasks. Your job is to
# compute how many total tasks each user has completed. After you've done so,
# find the answer to Problem 2 using the following formula:
# 
# Problem 2 Answer = Doug's total tasks * Jordan's total tasks * Eric's total
# tasks * Jonathan's total tasks

CACHE = {}

def tasks(target, points):
    next = { 0 : 0 }
    while not target in CACHE:
        current, next = next, {}
        for karma, tasks in current.items():
            for p in points:
                k = p + karma
                if k <= target and not k in CACHE:
                    next[k] = tasks + 1
        CACHE.update(next)  
    return CACHE[target]

def question_two():
    points = (2, 3, 17, 23, 42, 98)
    karmalist = (2349, 2102, 2001, 1747)
    print 'Answer question two:', reduce(
        lambda x, y: x * y, [ tasks(i, points) for i in karmalist ])

if __name__ == '__main__':
    question_one()
    question_two()