def main():
from helpers.data_access import get_data
data = get_data(day=1).split("\n")
result = expense_check((int(entry) for entry in data))
print(f"Expense check result is {result}")
result_b = expense_check((int(entry) for entry in data), num_numbers=3)
print(f"Extended xpense check result is {result_b}")
def main():
from helpers.data_access import get_data
data = get_data(day=2).split("\n")
inputs = (parse_input_line(line) for line in data)
inputs_1, inputs_2 = tee(inputs)
count = count_valid(inputs_1)
print(f"There are {count} valid passwords.")
count_v2 = count_valid(inputs_2, checker=is_password_valid_v2)
print(f"Actually there's {count_v2} valid passwords.")
seen_lines = [0]
current, acc = 0, 0
while True:
current, acc = run_instruction(data, current, acc)
if current in seen_lines:
return current, acc
if current == len(data) - 1:
if data[current][1] == "acc":
acc += data[current][2]
return current, acc
seen_lines.append(current)
if __name__ == "__main__":
data = get_data(day=8).split("\n")
### Part 1
t0 = time()
data = [x.split() for x in data]
data = [[i, x[0], int(x[1])] for i, x in enumerate(data)]
current, acc = run_data_loop(data)
print(f"first line to repeat itself {current}, value of accumulator {acc}")
print(f"runtime {time()-t0:.4f} seconds")
### Part 2
t0 = time()
current, acc = 0, 0
for i, line in enumerate(data):
if line[1] == "nop":
data_mod = deepcopy(data)
data_mod[line[0]][1] = "jmp"
def check_pid(p_dict):
if len(p_dict["pid"]) == 9:
try:
int(p_dict["pid"])
return True
except ValueError:
return False
else:
return False
if __name__ == "__main__":
data = get_data(day=4).split("\n\n")
### Part 1
valid_passports = 0
t0 = time()
for line in data:
a = re.split(" |\n", line)
p_dict = {x.split(":")[0]: x.split(":")[1] for x in a}
keys = p_dict.keys()
if (len(keys) == 8) or (len(keys) == 7 and "cid" not in keys):
valid_passports += 1
print(f"valid passports: {valid_passports}")
print(f"runtime {time()-t0:.4f} seconds")
### Part 2
t0 = time()
valid_passports = 0
from time import time
import numpy as np
from collections import Counter
def get_cluster_sizes(diff):
cluster_size = 0
cluster_sizes = {}
for i in diff:
if i == 3:
cluster_sizes[cluster_size] += 1
if __name__ == "__main__":
data = list(map(int, get_data(day=10).split("\n")))
### Part 1
t0 = time()
sorted_data = [0] + sorted(data) + [max(data) + 3]
diff = np.diff(sorted_data)
counts = Counter(diff)
print(f"1-jolt diffs: {counts[1]}, 3-jolt diffs: {counts[3]}," +
f" prod = {counts[1]*counts[3]}")
print(f"runtime {time()-t0:.4f} seconds")
### Part 2
t0 = time()
# based on the size of a cluster of 1s (say 311113 is size 4), number of independent
# solutions. Total possible solutions are the product of the number of independent
# solutions per cluster
sols_per_cluster_size = {2: 2, 3: 4, 4: 7}