import re
from collections import namedtuple

STEPS = 32

from multiprocessing import Process, Queue
def qual(env, ore_rbt, clay_rbt, obs_rbt, geo_rbt, ore_cnt, clay_cnt, obs_cnt, geo_cnt, t):
    assert max(ore_rbt, clay_rbt, obs_rbt, geo_rbt) < 32
    assert max(ore_cnt, clay_cnt, obs_cnt) < 512
    assert geo_cnt < 128
    code = (t | ore_rbt <<6 | (clay_rbt <<11)| (obs_rbt <<16) | (geo_rbt << 21) |
            (ore_cnt <<26) | (clay_cnt <<35) | (obs_cnt <<44) | (geo_cnt << 53))
    if code in env.cache:
        return env.cache[code]
    if t == STEPS:
        return geo_cnt

    # if fewer geodes than 80% of best solution so far -> discard
    if geo_cnt < env.t_max[t]*8//10:
        return -1

    env.t_max[t] = max(env.t_max[t], geo_cnt)

    n_ore_cnt = ore_cnt + ore_rbt
    n_clay_cnt = clay_cnt + clay_rbt
    n_obs_cnt = obs_cnt + obs_rbt
    n_geo_cnt = geo_cnt + geo_rbt

    maxg = 0
    if ore_cnt >= env.ore_cost and ore_rbt < env.max_ore_needed:
        maxg = max(maxg, qual(env, ore_rbt+1, clay_rbt, obs_rbt, geo_rbt, n_ore_cnt - env.ore_cost, n_clay_cnt, n_obs_cnt, n_geo_cnt, t+1))

    if ore_cnt >= env.clay_cost and clay_rbt < env.obs_cost_clay:
        maxg = max(maxg, qual(env, ore_rbt, clay_rbt+1, obs_rbt, geo_rbt, n_ore_cnt - env.clay_cost, n_clay_cnt, n_obs_cnt, n_geo_cnt, t+1))

    if ore_cnt >= env.obs_cost_ore and clay_cnt >= env.obs_cost_clay and obs_rbt < env.geo_cost_obs:
        maxg = max(maxg, qual(env, ore_rbt, clay_rbt, obs_rbt+1, geo_rbt, n_ore_cnt - env.obs_cost_ore, n_clay_cnt-env.obs_cost_clay, n_obs_cnt, n_geo_cnt, t+1))

    if ore_cnt >= env.geo_cost_ore and obs_cnt >= env.geo_cost_obs:
        maxg = max(maxg, qual(env, ore_rbt, clay_rbt, obs_rbt, geo_rbt+1, n_ore_cnt - env.geo_cost_ore, n_clay_cnt, n_obs_cnt-env.geo_cost_obs, n_geo_cnt, t+1))

    maxg = max(maxg, qual(env, ore_rbt, clay_rbt, obs_rbt, geo_rbt, n_ore_cnt, n_clay_cnt, n_obs_cnt, n_geo_cnt, t+1))

    env.cache[code] = maxg
    return maxg

Env = namedtuple("Env", "ore_cost, clay_cost, obs_cost_ore, obs_cost_clay, geo_cost_ore, geo_cost_obs, cache, t_max, max_ore_needed")

def runline(queue, line):
    bp, ore_cost, clay_cost, obs_cost_ore, obs_cost_clay, geo_cost_ore, geo_cost_obs = [int(x) for x in re.findall("\d+", line)]
    cache={}
    t_max={i:0 for i in range(STEPS)}
    max_ore_needed = max(ore_cost, clay_cost, obs_cost_ore, geo_cost_ore)
    env = Env(ore_cost, clay_cost, obs_cost_ore, obs_cost_clay, geo_cost_ore, geo_cost_obs, cache, t_max, max_ore_needed)
    q = qual(env, 1, 0, 0, 0, 0, 0, 0, 0, 0)
    print (bp, "->", q)
    queue.put(q)

with open("geode_p2.txt") as infile:
    procs = []

    for line in infile:
        queue = Queue()
        proc = Process(target=runline, args=(queue, line))
        proc.start()
        procs.append((proc, queue))

    total = 1
    for p, q in procs:
        p.join() # this blocks until the process terminates
        result = q.get()
        print (result)
        total *= result
    print (total)