Calculating loot distribution for a given player base

calculate_simulations.py

from random import *

# lock the results for reproducibility
seed(1)

# Staff of shadow flame is estimated to be between 7-8%
drop_rate = .075

# Total players who are competing
pool_size = 3

# How many runs before the pool size gets all their drops
# 52 would be a year, once a week
runs = 52

## How accurate the calcuation is
simulations = 100000

def reset_pool_to_original(n):
    return list(range(n))

def simulate_drop(pool):
    if len(pool) is not 0 and random() < drop_rate:
        pool.remove(choice(pool))
    return pool

def epochs(simultations):
    success_count, failure_count = 0, 0
    for i in range(simulations):
        if i%1000 == 0:
            print(i)
        pool = reset_pool_to_original(pool_size)
        # print('========================')
        # print('\n', 'begin epoch', i)
        for j in range(runs):
            # print('current_pool', pool)
            simulate_drop(pool)
            # print('ending_pool', pool, '\n')
        if len(pool) == 0:
            success_count = success_count + 1
    # print('success count', success_count, 'simulation count', simulations)
    print(success_count/simulations)

epochs(simulations)

# 55% with four people
# 76% with three people