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+# Lily Carpenter
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+# lily-redditchallenge@azrazalea.net
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+# 2049 South Florence Apt. 8
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+# Springfield, MO
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+# 417-379-3326
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+#
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+# Premise:
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+# While I'm sure there is a fancy algorithm to do this very efficiently, I have not gotten far enough into
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+# math/computer science theory in order to be able to come up with it effectively.
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+#
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+# Therefore, here is how my script works:
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+# 1. Sorts all panels in descending order based on value
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+# 2. Starting with the person with the highest yield (me) and going from there
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+# it adds the highest value panels to the set panel list until we reach or surpass goal
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+# 3. If we managed to hit goal exactly, we are done. Otherwise, start second process
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+# 4. In the second process we resort data in ascending order and try until we reach or surpass goal
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+#
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+# This should theoretically result in using the lower yield people the least, as well as getting as close as possible
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+# to the goal without going over.
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+
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+import argparse
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+import sys
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+import locale
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+
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+# Setup command line arguments
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+# I did goal and days partly just because I wanted to play with the values
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+parser = argparse.ArgumentParser(description='Determine panel distribution')
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+parser.add_argument('file_name', metavar='<File Name>', type=str, help='file containing panel data')
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+parser.add_argument('-g', '--goal', metavar='<Goal>', type=int, help='Goal we are trying to reach (default 250000)', default=250000)
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+parser.add_argument('-d', '--days', metavar='<Days>', type=int, help='Number of days to reach goal (default 7)', default=7)
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+
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+
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+# A list of dictionaries containing the necessary data on each person
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+# Also stores the set of panels to be assigned to each person
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+# This is pulled from the problem description, of course
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+people = [
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+ {'name': 'M', 'yield': 1, 'pan_a_day': 1, 'panels': [] },
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+ {'name': 'GM', 'yield': .95, 'pan_a_day': 2, 'panels': [] },
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+ {'name': '?', 'yield': .85, 'pan_a_day': 3, 'panels': [] },
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+ {'name': 'GB', 'yield': .6, 'pan_a_day': 4, 'panels': [] },
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+ ]
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+
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+# Simple function, simply loads data from file_name and converts it to int, puts in list data, and returns data
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+# The data list contains tuples of (index, value) to preserve original index later when sorting
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+# If it gets something that isn't a number it'll tell you about it, make that entry 0, then continue like nothing happened
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+def get_data(file_name):
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+ data = []
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+ with open(file_name, 'r') as _file:
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+ for line_num, line in enumerate(_file, 1):
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+ try:
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+ line = int(line)
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+ except ValueError:
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+ sys.stderr.write('Skipping invalid data at line: ' + str(line_num) + '\n')
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+ # This is so that we don't miss a panel index
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+ data.append(0)
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+ else:
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+ data.append((line_num - 1, int(line)))
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+ return data
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+
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+# Grab the data and arguments
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+args = parser.parse_args()
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+data = get_data(args.file_name)
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+days = args.days
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+goal = args.goal
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+
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+# Grab replacement cost of panels
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+replace_cost = data.pop(0)[1]
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+
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+# Sort by the 'value' column, descending, to get list ready for processing
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+data.sort(key=lambda datem: datem[1], reverse=True)
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+
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+current_money = 0
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+panel = 0
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+# This loop goes through each person, people is already setup to be descending by yield
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+for person in people:
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+ for x in range(0, person['pan_a_day'] * days):
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+ # This is how much the current panel is worth, taking into account yield and
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+ # replacement cost
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+ additional_amt = data[panel][1] * person['yield'] - replace_cost
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+
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+ # If the next panel in list does not meet or go past the goal, add to person's panel set
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+ # and increment current_money by additional_amt
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+ if current_money + additional_amt <= goal:
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+ current_money += additional_amt
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+ person['panels'].append((data[panel][0], data[panel][1]))
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+ panel += 1
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+ # Otherwise, we need to switch gears and look for the smallest possible panel to finish
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+ else:
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+ data.sort(key=lambda datem: datem[1])
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+
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+ # Have to have this up here in case there was a perfect match
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+ if current_money >= goal:
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+ break;
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+
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+ for y in range(0, len(data) - panel):
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+ additional_amt = data[y][1] * person['yield'] - replace_cost
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+ if current_money + additional_amt >= goal:
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+ current_money += additional_amt
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+ person['panels'].append((data[y][0], data[y][1]))
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+ break;
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+
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+ if current_money >= goal:
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+ break;
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+
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+# Print the output, all pretty like
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+for person in people:
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+ print ' '.join([person['name'], '=', repr(person['panels'])])
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+
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+# Add up how much money is left
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+money_left = 0
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+for x in range(panel, len(data)):
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+ money_left += data[x][1]
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+
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+# Print out how much money is left
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+locale.setlocale(locale.LC_ALL, '')
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+print 'Total cash left in bannana stand: $' + format(money_left, "n")
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