Backup local 2022 day 16.

2021/day5.py

@@ -0,0 +1,52 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+from collections import defaultdict
+
+import numpy as np
+
+lines: list[str] = sys.stdin.read().splitlines()
+
+sections: list[tuple[tuple[int, int], tuple[int, int]]] = [
+    (
+        (
+            int(line.split(" -> ")[0].split(",")[0]),
+            int(line.split(" -> ")[0].split(",")[1]),
+        ),
+        (
+            int(line.split(" -> ")[1].split(",")[0]),
+            int(line.split(" -> ")[1].split(",")[1]),
+        ),
+    )
+    for line in lines
+]
+
+np_sections = np.array(sections).reshape(-1, 4)
+
+x_min, x_max, y_min, y_max = (
+    min(np_sections[:, 0].min(), np_sections[:, 2].min()),
+    max(np_sections[:, 0].max(), np_sections[:, 2].max()),
+    min(np_sections[:, 1].min(), np_sections[:, 3].min()),
+    max(np_sections[:, 1].max(), np_sections[:, 3].max()),
+)
+
+counts_1 = np.zeros((y_max + 1, x_max + 1), dtype=int)
+counts_2 = counts_1.copy()
+
+for (x1, y1), (x2, y2) in sections:
+
+    x_rng = range(x1, x2 + 1, 1) if x2 >= x1 else range(x1, x2 - 1, -1)
+    y_rng = range(y1, y2 + 1, 1) if y2 >= y1 else range(y1, y2 - 1, -1)
+
+    if x1 == x2 or y1 == y2:
+        counts_1[list(y_rng), list(x_rng)] += 1
+        counts_2[list(y_rng), list(x_rng)] += 1
+    elif abs(x2 - x1) == abs(y2 - y1):
+        for i, j in zip(y_rng, x_rng):
+            counts_2[i, j] += 1
+
+answer_1 = (counts_1 >= 2).sum()
+print(f"answer 1 is {answer_1}")
+
+answer_2 = (counts_2 >= 2).sum()
+print(f"answer 2 is {answer_2}")

2021/inputs/day5.txt

@@ -0,0 +1,500 @@
+657,934 -> 657,926
+130,34 -> 570,474
+478,716 -> 226,464
+861,110 -> 861,167
+448,831 -> 370,831
+75,738 -> 390,738
+26,880 -> 864,42
+965,658 -> 527,220
+208,381 -> 80,381
+523,475 -> 807,475
+219,69 -> 219,434
+793,538 -> 534,797
+754,602 -> 754,148
+443,327 -> 443,611
+606,395 -> 546,395
+980,56 -> 51,985
+619,325 -> 354,325
+342,123 -> 819,600
+290,533 -> 374,533
+598,77 -> 598,75
+605,302 -> 605,636
+97,981 -> 692,386
+278,779 -> 278,800
+661,377 -> 661,10
+726,108 -> 518,316
+271,883 -> 271,50
+382,271 -> 606,271
+963,358 -> 891,286
+496,880 -> 496,855
+211,142 -> 211,49
+841,866 -> 260,285
+841,849 -> 173,181
+927,326 -> 391,862
+396,558 -> 459,558
+753,183 -> 953,183
+941,698 -> 941,407
+347,612 -> 347,476
+18,340 -> 18,612
+140,299 -> 797,956
+714,907 -> 714,228
+966,155 -> 194,927
+769,674 -> 712,674
+644,675 -> 948,979
+703,872 -> 812,763
+26,629 -> 120,535
+844,738 -> 844,253
+798,133 -> 798,795
+27,318 -> 288,57
+38,545 -> 872,545
+827,351 -> 195,983
+818,45 -> 21,842
+257,559 -> 626,928
+145,925 -> 886,184
+83,618 -> 590,111
+326,243 -> 53,243
+489,278 -> 526,278
+783,693 -> 783,525
+495,636 -> 495,585
+374,716 -> 215,557
+839,536 -> 839,966
+850,468 -> 955,468
+55,799 -> 55,447
+472,722 -> 296,898
+390,731 -> 120,461
+405,493 -> 208,296
+807,42 -> 56,793
+476,327 -> 655,327
+24,965 -> 967,22
+776,211 -> 776,850
+489,20 -> 822,20
+630,740 -> 871,499
+743,493 -> 283,953
+62,429 -> 62,720
+806,270 -> 806,332
+550,154 -> 107,597
+71,713 -> 533,251
+620,575 -> 620,156
+726,829 -> 143,246
+944,553 -> 468,553
+185,582 -> 185,468
+845,266 -> 212,899
+654,97 -> 265,486
+726,609 -> 726,147
+631,76 -> 860,76
+835,24 -> 928,24
+712,719 -> 74,81
+616,478 -> 616,117
+903,226 -> 903,577
+440,699 -> 136,395
+215,705 -> 890,30
+20,24 -> 981,985
+102,144 -> 850,892
+695,967 -> 582,967
+219,284 -> 219,388
+359,833 -> 665,833
+389,55 -> 305,55
+59,32 -> 957,930
+815,198 -> 64,949
+699,540 -> 717,558
+215,682 -> 182,682
+805,489 -> 328,489
+43,546 -> 578,546
+489,181 -> 489,363
+266,391 -> 266,582
+863,368 -> 448,368
+83,236 -> 83,487
+874,875 -> 874,413
+799,90 -> 799,802
+253,29 -> 253,905
+136,446 -> 435,745
+830,534 -> 550,534
+183,785 -> 107,785
+81,517 -> 159,517
+359,941 -> 359,560
+71,546 -> 948,546
+596,811 -> 596,791
+255,960 -> 255,159
+788,15 -> 788,682
+240,55 -> 240,244
+51,423 -> 137,423
+504,418 -> 809,723
+131,842 -> 914,59
+727,790 -> 82,145
+281,509 -> 841,509
+797,807 -> 834,807
+333,499 -> 790,499
+215,328 -> 215,139
+500,898 -> 500,862
+75,217 -> 777,919
+17,264 -> 17,446
+852,755 -> 150,755
+865,186 -> 385,186
+158,192 -> 158,733
+196,261 -> 196,128
+989,960 -> 131,102
+807,393 -> 807,153
+507,579 -> 507,764
+468,76 -> 535,76
+381,357 -> 659,357
+794,277 -> 749,277
+51,152 -> 546,647
+797,959 -> 458,959
+82,156 -> 967,156
+261,624 -> 460,624
+597,53 -> 197,53
+153,507 -> 411,765
+305,717 -> 768,717
+344,954 -> 344,217
+194,432 -> 545,432
+346,46 -> 557,46
+685,599 -> 685,312
+49,719 -> 49,631
+499,668 -> 304,863
+262,405 -> 554,405
+87,64 -> 295,64
+859,675 -> 74,675
+663,776 -> 99,212
+232,189 -> 232,904
+777,276 -> 703,276
+704,492 -> 86,492
+142,736 -> 514,364
+418,611 -> 224,417
+602,571 -> 602,424
+152,603 -> 248,603
+915,673 -> 143,673
+538,32 -> 128,32
+975,885 -> 975,344
+870,511 -> 870,756
+330,798 -> 46,798
+440,195 -> 587,195
+739,237 -> 568,66
+54,838 -> 196,980
+370,556 -> 47,556
+124,575 -> 748,575
+261,283 -> 880,902
+784,91 -> 426,449
+764,670 -> 148,670
+32,51 -> 967,986
+807,906 -> 10,906
+470,488 -> 579,597
+274,649 -> 285,649
+221,540 -> 221,94
+914,957 -> 914,510
+879,825 -> 145,91
+438,833 -> 438,775
+191,844 -> 911,124
+145,763 -> 595,763
+504,81 -> 622,199
+834,206 -> 834,704
+908,308 -> 815,308
+929,567 -> 929,322
+805,50 -> 620,235
+36,409 -> 133,312
+345,375 -> 19,701
+468,948 -> 468,108
+109,547 -> 446,547
+929,916 -> 69,56
+927,857 -> 318,248
+833,948 -> 833,61
+559,787 -> 559,982
+293,825 -> 293,775
+508,744 -> 545,744
+827,713 -> 753,639
+88,775 -> 555,775
+523,812 -> 684,812
+307,142 -> 307,265
+636,40 -> 355,321
+891,875 -> 891,25
+301,423 -> 712,12
+922,187 -> 219,890
+45,447 -> 230,262
+114,568 -> 233,687
+573,398 -> 677,398
+334,101 -> 324,101
+957,277 -> 957,652
+943,834 -> 610,834
+523,632 -> 523,379
+958,361 -> 90,361
+408,824 -> 380,824
+647,314 -> 647,449
+747,83 -> 59,83
+776,104 -> 937,104
+16,984 -> 989,11
+362,581 -> 362,226
+72,962 -> 940,94
+319,877 -> 319,122
+310,206 -> 986,882
+794,877 -> 267,877
+855,58 -> 976,58
+699,971 -> 598,971
+162,556 -> 162,440
+494,859 -> 494,255
+794,210 -> 142,862
+275,510 -> 548,510
+739,592 -> 739,793
+376,985 -> 376,990
+755,264 -> 280,739
+187,34 -> 187,688
+770,827 -> 770,548
+10,68 -> 913,971
+571,427 -> 571,944
+153,211 -> 153,560
+976,972 -> 55,51
+103,611 -> 674,40
+95,972 -> 924,143
+929,94 -> 38,985
+777,330 -> 60,330
+312,430 -> 312,326
+549,433 -> 269,433
+477,267 -> 477,403
+598,375 -> 19,375
+512,799 -> 512,831
+348,700 -> 348,43
+165,97 -> 63,199
+38,835 -> 38,828
+282,334 -> 282,909
+14,891 -> 390,515
+930,657 -> 334,61
+630,341 -> 630,85
+671,464 -> 319,112
+949,340 -> 894,285
+663,916 -> 245,916
+114,395 -> 286,223
+335,804 -> 529,804
+567,338 -> 14,891
+623,705 -> 379,949
+82,864 -> 545,401
+932,128 -> 932,134
+291,294 -> 291,101
+739,765 -> 739,757
+460,94 -> 892,94
+375,673 -> 367,681
+81,831 -> 90,831
+890,402 -> 890,138
+775,547 -> 790,547
+49,927 -> 966,10
+23,116 -> 257,116
+923,75 -> 18,980
+63,986 -> 687,362
+369,844 -> 357,844
+790,188 -> 644,188
+557,282 -> 557,669
+861,173 -> 390,644
+480,529 -> 893,529
+32,960 -> 830,162
+368,725 -> 368,40
+502,600 -> 701,600
+63,977 -> 873,167
+463,518 -> 788,193
+738,406 -> 324,406
+162,931 -> 822,931
+377,487 -> 707,817
+610,319 -> 901,319
+586,658 -> 690,658
+25,288 -> 53,288
+760,602 -> 760,628
+294,62 -> 951,62
+222,773 -> 661,334
+151,483 -> 646,483
+272,852 -> 317,852
+557,906 -> 503,960
+736,445 -> 736,703
+241,376 -> 241,692
+835,41 -> 835,369
+987,743 -> 987,210
+42,700 -> 42,244
+646,136 -> 646,440
+544,751 -> 404,751
+295,651 -> 295,805
+687,878 -> 113,878
+290,142 -> 604,142
+579,920 -> 579,807
+12,985 -> 987,10
+919,940 -> 919,808
+770,143 -> 770,832
+114,76 -> 962,76
+876,882 -> 428,434
+861,139 -> 861,320
+888,59 -> 888,39
+629,823 -> 707,823
+296,598 -> 296,305
+61,54 -> 578,54
+864,58 -> 253,58
+71,861 -> 306,861
+682,181 -> 326,537
+307,418 -> 307,910
+810,251 -> 810,431
+151,836 -> 602,385
+954,987 -> 243,276
+724,272 -> 350,646
+134,295 -> 434,295
+178,235 -> 802,859
+832,688 -> 832,573
+165,334 -> 165,378
+816,26 -> 114,728
+668,192 -> 540,192
+730,341 -> 969,341
+951,169 -> 286,834
+647,115 -> 886,115
+664,288 -> 507,131
+609,362 -> 609,295
+747,479 -> 287,19
+350,967 -> 350,725
+117,383 -> 311,383
+871,124 -> 292,124
+654,271 -> 547,271
+525,773 -> 345,953
+401,670 -> 610,670
+930,196 -> 301,825
+336,37 -> 961,662
+714,212 -> 714,667
+454,848 -> 454,107
+587,390 -> 587,577
+530,437 -> 542,437
+304,229 -> 517,229
+340,571 -> 766,571
+727,941 -> 138,352
+831,325 -> 11,325
+241,294 -> 403,456
+788,658 -> 788,126
+337,360 -> 337,589
+799,402 -> 342,402
+530,820 -> 530,319
+982,27 -> 20,989
+923,936 -> 923,721
+581,395 -> 64,912
+61,509 -> 61,827
+989,580 -> 610,580
+477,592 -> 219,592
+296,775 -> 296,58
+204,12 -> 204,457
+190,171 -> 190,673
+939,200 -> 939,457
+472,282 -> 472,631
+983,331 -> 734,331
+365,609 -> 365,817
+640,698 -> 145,698
+103,618 -> 549,618
+454,319 -> 454,346
+650,815 -> 381,546
+624,603 -> 507,603
+966,445 -> 723,445
+763,129 -> 763,784
+695,145 -> 695,511
+498,84 -> 435,147
+188,716 -> 967,716
+810,446 -> 810,924
+731,483 -> 731,51
+307,783 -> 307,533
+15,956 -> 956,15
+192,210 -> 882,210
+303,173 -> 38,438
+769,952 -> 769,863
+135,781 -> 405,781
+494,436 -> 494,892
+705,394 -> 714,394
+164,37 -> 164,633
+813,232 -> 813,620
+227,906 -> 222,906
+542,432 -> 414,432
+549,858 -> 88,397
+200,101 -> 958,859
+235,565 -> 469,331
+492,871 -> 503,882
+704,398 -> 869,563
+450,736 -> 746,736
+420,706 -> 420,635
+717,493 -> 686,524
+187,554 -> 717,24
+31,851 -> 315,851
+800,230 -> 466,230
+226,324 -> 226,614
+937,927 -> 937,798
+143,26 -> 534,417
+952,344 -> 12,344
+181,361 -> 782,361
+925,906 -> 415,396
+685,944 -> 470,944
+200,627 -> 290,627
+728,285 -> 728,326
+271,864 -> 271,34
+802,558 -> 207,558
+963,26 -> 84,905
+504,60 -> 529,60
+840,292 -> 180,292
+914,272 -> 914,330
+82,107 -> 925,950
+33,245 -> 33,134
+463,663 -> 463,82
+27,305 -> 27,675
+276,894 -> 891,279
+746,325 -> 746,948
+249,657 -> 341,749
+530,848 -> 28,346
+798,617 -> 798,609
+119,767 -> 312,767
+80,18 -> 674,18
+723,374 -> 583,374
+582,985 -> 239,642
+217,765 -> 217,395
+811,159 -> 609,159
+689,896 -> 501,896
+562,881 -> 562,96
+244,621 -> 629,621
+277,379 -> 277,287
+856,153 -> 20,153
+518,228 -> 518,898
+230,789 -> 243,789
+534,335 -> 534,592
+240,790 -> 413,617
+768,615 -> 768,560
+773,101 -> 912,101
+252,571 -> 767,56
+370,595 -> 681,906
+565,176 -> 565,318
+750,465 -> 750,724
+979,130 -> 120,989
+160,153 -> 160,785
+610,222 -> 610,191
+873,124 -> 130,867
+519,593 -> 519,32
+525,947 -> 525,562
+50,292 -> 291,533
+558,927 -> 960,525
+536,694 -> 249,981
+954,896 -> 277,896
+732,202 -> 732,288
+447,989 -> 541,895
+890,754 -> 367,231
+368,89 -> 564,285
+588,100 -> 588,156
+282,313 -> 943,974
+16,792 -> 495,792
+111,591 -> 111,493
+57,713 -> 685,85
+676,632 -> 676,575
+560,708 -> 560,602
+489,288 -> 489,404
+904,515 -> 443,54
+70,977 -> 985,62
+11,119 -> 11,403
+215,859 -> 937,137
+78,469 -> 110,437
+747,605 -> 747,369
+847,598 -> 847,299
+742,695 -> 159,112
+986,370 -> 986,460
+631,900 -> 771,760
+228,406 -> 683,861
+189,639 -> 61,639
+221,650 -> 820,650
+558,569 -> 834,845
+655,533 -> 558,630
+967,921 -> 967,169
+230,308 -> 429,308
+873,762 -> 873,528
+412,151 -> 412,538
+881,587 -> 881,21
+941,45 -> 26,960
+377,126 -> 700,126

2022/day1.py

@@ -1,19 +1,9 @@
 # -*- encoding: utf-8 -*-
 
-from pathlib import Path
+import sys
 
-with open(Path(__file__).parent.joinpath("inputs", "day1.txt")) as fp:
+blocks = sys.stdin.read().split("\n\n")
-    lines = fp.readlines()
+values = sorted(sum(map(int, block.split())) for block in blocks)
 
-values: list[int] = [0]
+print(f"answer 1 is {values[-1]}")
-for line in lines:
+print(f"answer 2 is {sum(values[-3:])}")
-    if not line.strip():
-        values = values + [0]
-    else:
-        values[-1] += int(line.strip())
-
-# part 1
-print(f"max is {max(values)}")
-
-# part 2
-print(f"sum of top 3 is {sum(sorted(values)[-3:])}")

2022/day10.py

@@ -0,0 +1,40 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+lines = sys.stdin.read().splitlines()
+
+cycle = 1
+x = 1
+
+values = {cycle: x}
+
+for line in lines:
+    cycle += 1
+
+    if line == "noop":
+        pass
+    else:
+        r = int(line.split()[1])
+
+        values[cycle] = x
+
+        cycle += 1
+        x += r
+
+    values[cycle] = x
+
+answer_1 = sum(c * values[c] for c in range(20, max(values.keys()) + 1, 40))
+print(f"answer 1 is {answer_1}")
+
+
+for i in range(6):
+    for j in range(40):
+        v = values[1 + i * 40 + j]
+
+        if j >= v - 1 and j <= v + 1:
+            print("#", end="")
+        else:
+            print(".", end="")
+
+    print()

2022/day11.py

@@ -0,0 +1,146 @@
+# -*- encoding: utf-8 -*-
+
+import copy
+import sys
+from functools import reduce
+from typing import Callable, Final, Mapping, Sequence
+
+
+class Monkey:
+
+    id: Final[int]
+    items: Final[Sequence[int]]
+    worry_fn: Final[Callable[[int], int]]
+    test_value: Final[int]
+    throw_targets: Final[Mapping[bool, int]]
+
+    def __init__(
+        self,
+        id: int,
+        items: list[int],
+        worry_fn: Callable[[int], int],
+        test_value: int,
+        throw_targets: dict[bool, int],
+    ):
+        self.id = id
+        self.items = items
+        self.worry_fn = worry_fn
+        self.test_value = test_value
+        self.throw_targets = throw_targets
+
+    def __eq__(self, o: object) -> bool:
+        if not isinstance(o, Monkey):
+            return False
+        return self.id == o.id
+
+    def __hash__(self) -> int:
+        return hash(self.id)
+
+
+def parse_monkey(lines: list[str]) -> Monkey:
+    assert lines[0].startswith("Monkey")
+
+    monkey_id = int(lines[0].split()[-1][:-1])
+
+    # parse items
+    items = [int(r.strip()) for r in lines[1].split(":")[1].split(",")]
+
+    # parse worry
+    worry_fn: Callable[[int], int]
+    worry_s = lines[2].split("new =")[1].strip()
+    operand = worry_s.split()[2].strip()
+
+    if worry_s.startswith("old *"):
+        if operand == "old":
+            worry_fn = lambda w: w * w  # noqa: E731
+        else:
+            worry_fn = lambda w: w * int(operand)  # noqa: E731
+    elif worry_s.startswith("old +"):
+        if operand == "old":
+            worry_fn = lambda w: w + w  # noqa: E731
+        else:
+            worry_fn = lambda w: w + int(operand)  # noqa: E731
+    else:
+        assert False, worry_s
+
+    # parse test
+    assert lines[3].split(":")[1].strip().startswith("divisible by")
+    test_value = int(lines[3].split()[-1])
+
+    assert lines[4].strip().startswith("If true")
+    assert lines[5].strip().startswith("If false")
+    throw_targets = {True: int(lines[4].split()[-1]), False: int(lines[5].split()[-1])}
+
+    assert monkey_id not in throw_targets.values()
+
+    return Monkey(monkey_id, items, worry_fn, test_value, throw_targets)
+
+
+def run(
+    monkeys: list[Monkey], n_rounds: int, me_worry_fn: Callable[[int], int]
+) -> dict[Monkey, int]:
+    """
+    Perform a full run.
+
+    Args:
+        monkeys: Initial list of monkeys. The Monkey are not modified.
+        n_rounds: Number of rounds to run.
+        me_worry_fn: Worry function to apply after the Monkey operation (e.g., divide
+            by 3 for round 1).
+
+    Returns:
+        A mapping containing, for each monkey, the number of items inspected.
+    """
+    # copy of the items
+    items = {monkey: list(monkey.items) for monkey in monkeys}
+
+    # number of inspects
+    inspects = {monkey: 0 for monkey in monkeys}
+
+    for round in range(n_rounds):
+
+        for monkey in monkeys:
+            for item in items[monkey]:
+                inspects[monkey] += 1
+
+                # compute the new worry level
+                item = me_worry_fn(monkey.worry_fn(item))
+
+                # find the target
+                target = monkey.throw_targets[item % monkey.test_value == 0]
+                assert target != monkey.id
+
+                items[monkeys[target]].append(item)
+
+            # clear after the loop
+            items[monkey].clear()
+
+    return inspects
+
+
+def monkey_business(inspects: dict[Monkey, int]) -> int:
+    sorted_levels = sorted(inspects.values())
+    return sorted_levels[-2] * sorted_levels[-1]
+
+
+monkeys = [parse_monkey(block.splitlines()) for block in sys.stdin.read().split("\n\n")]
+
+# case 1: we simply divide the worry by 3 after applying the monkey worry operation
+answer_1 = monkey_business(
+    run(copy.deepcopy(monkeys), 20, me_worry_fn=lambda w: w // 3)
+)
+print(f"answer 1 is {answer_1}")
+
+# case 2: to keep reasonable level values, we can use a modulo operation, we need to
+# use the product of all "divisible by" test so that the test remains valid
+#
+# (a + b) % c == ((a % c) + (b % c)) % c --- this would work for a single test value
+#
+# (a + b) % c == ((a % d) + (b % d)) % c --- if d is a multiple of c, which is why here
+# we use the product of all test value
+#
+total_test_value = reduce(lambda w, m: w * m.test_value, monkeys, 1)
+answer_2 = monkey_business(
+    run(copy.deepcopy(monkeys), 10_000, me_worry_fn=lambda w: w % total_test_value)
+)
+print(f"answer 2 is {answer_2}")

2022/day12.py

@@ -0,0 +1,165 @@
+# -*- encoding: utf-8 -*-
+
+import heapq
+import sys
+from typing import Callable, Iterator, TypeVar
+
+Node = TypeVar("Node")
+
+
+def dijkstra(
+    start: Node,
+    neighbors: Callable[[Node], Iterator[Node]],
+    cost: Callable[[Node, Node], float],
+) -> tuple[dict[Node, float], dict[Node, Node]]:
+    """
+    Compute shortest paths from one node to all reachable ones.
+
+    Args:
+        start: Starting node.
+        neighbors: Function returning the neighbors of a node.
+        cost: Function to compute the cost of an edge.
+
+    Returns:
+        A tuple (lengths, parents) where lengths is a mapping from Node to distance
+        (from the starting node) and parents a mapping from parents Node (in the
+        shortest path). If keyset of lengths and parents is the same. If a Node is not
+        in the mapping, it cannot be reached from the starting node.
+    """
+
+    queue: list[tuple[float, Node]] = []
+
+    visited: set[Node] = set()
+    lengths: dict[Node, float] = {start: 0}
+    parents: dict[Node, Node] = {}
+
+    heapq.heappush(queue, (0, start))
+
+    while queue:
+        length, current = heapq.heappop(queue)
+
+        if current in visited:
+            continue
+
+        visited.add(current)
+
+        for neighbor in neighbors(current):
+
+            if neighbor in visited:
+                continue
+
+            neighbor_cost = length + cost(current, neighbor)
+
+            if neighbor_cost < lengths.get(neighbor, float("inf")):
+                lengths[neighbor] = neighbor_cost
+                parents[neighbor] = current
+
+                heapq.heappush(queue, (neighbor_cost, neighbor))
+
+    return lengths, parents
+
+
+def make_path(parents: dict[Node, Node], start: Node, end: Node) -> list[Node] | None:
+
+    if end not in parents:
+        return None
+
+    path: list[Node] = [end]
+
+    while path[-1] is not start:
+        path.append(parents[path[-1]])
+
+    return list(reversed(path))
+
+
+def print_path(path: list[tuple[int, int]], n_rows: int, n_cols: int) -> None:
+    end = path[-1]
+
+    graph = [["." for _c in range(n_cols)] for _r in range(n_rows)]
+    graph[end[0]][end[1]] = "E"
+
+    for i in range(0, len(path) - 1):
+        cr, cc = path[i]
+        nr, nc = path[i + 1]
+
+        if cr == nr and nc == cc - 1:
+            graph[cr][cc] = "<"
+        elif cr == nr and nc == cc + 1:
+            graph[cr][cc] = ">"
+        elif cr == nr - 1 and nc == cc:
+            graph[cr][cc] = "v"
+        elif cr == nr + 1 and nc == cc:
+            graph[cr][cc] = "^"
+        else:
+            assert False, "{} -> {} infeasible".format(path[i], path[i + 1])
+
+    print("\n".join("".join(row) for row in graph))
+
+
+def neighbors(
+    grid: list[list[int]], node: tuple[int, int], up: bool
+) -> Iterator[tuple[int, int]]:
+    n_rows = len(grid)
+    n_cols = len(grid[0])
+
+    c_row, c_col = node
+    for n_row, n_col in (
+        (c_row - 1, c_col),
+        (c_row + 1, c_col),
+        (c_row, c_col - 1),
+        (c_row, c_col + 1),
+    ):
+
+        if not (n_row >= 0 and n_row < n_rows and n_col >= 0 and n_col < n_cols):
+            continue
+
+        if up and grid[n_row][n_col] > grid[c_row][c_col] + 1:
+            continue
+        elif not up and grid[n_row][n_col] < grid[c_row][c_col] - 1:
+            continue
+
+        yield n_row, n_col
+
+
+# === main code ===
+
+lines = sys.stdin.read().splitlines()
+
+grid = [[ord(cell) - ord("a") for cell in line] for line in lines]
+
+start: tuple[int, int]
+end: tuple[int, int]
+
+# for part 2
+start_s: list[tuple[int, int]] = []
+
+for i_row, row in enumerate(grid):
+    for i_col, col in enumerate(row):
+        if chr(col + ord("a")) == "S":
+            start = (i_row, i_col)
+            start_s.append(start)
+        elif chr(col + ord("a")) == "E":
+            end = (i_row, i_col)
+        elif col == 0:
+            start_s.append((i_row, i_col))
+
+# fix values
+grid[start[0]][start[1]] = 0
+grid[end[0]][end[1]] = ord("z") - ord("a")
+
+
+lengths_1, parents_1 = dijkstra(
+    start=start, neighbors=lambda n: neighbors(grid, n, True), cost=lambda lhs, rhs: 1
+)
+path_1 = make_path(parents_1, start, end)
+assert path_1 is not None
+
+print_path(path_1, n_rows=len(grid), n_cols=len(grid[0]))
+
+print(f"answer 1 is {lengths_1[end] - 1}")
+
+lengths_2, parents_2 = dijkstra(
+    start=end, neighbors=lambda n: neighbors(grid, n, False), cost=lambda lhs, rhs: 1
+)
+answer_2 = min(lengths_2.get(start, float("inf")) for start in start_s)
+print(f"answer 2 is {answer_2}")

2022/day13.py

@@ -0,0 +1,41 @@
+# -*- encoding: utf-8 -*-
+
+import json
+import sys
+from functools import cmp_to_key
+
+blocks = sys.stdin.read().strip().split("\n\n")
+
+pairs = [tuple(json.loads(p) for p in block.split("\n")) for block in blocks]
+
+
+def compare(lhs: list[int | list], rhs: list[int | list]) -> int:
+
+    for lhs_a, rhs_a in zip(lhs, rhs):
+        if isinstance(lhs_a, int) and isinstance(rhs_a, int):
+            if lhs_a != rhs_a:
+                return rhs_a - lhs_a
+        else:
+            if not isinstance(lhs_a, list):
+                lhs_a = [lhs_a]
+            elif not isinstance(rhs_a, list):
+                rhs_a = [rhs_a]
+            assert isinstance(rhs_a, list) and isinstance(lhs_a, list)
+            r = compare(lhs_a, rhs_a)
+            if r != 0:
+                return r
+
+    return len(rhs) - len(lhs)
+
+
+answer_1 = sum(i + 1 for i, (lhs, rhs) in enumerate(pairs) if compare(lhs, rhs) > 0)
+print(f"answer_1 is {answer_1}")
+
+dividers = [[[2]], [[6]]]
+
+packets = [packet for packets in pairs for packet in packets]
+packets.extend(dividers)
+packets = list(reversed(sorted(packets, key=cmp_to_key(compare))))
+
+d_index = [packets.index(d) + 1 for d in dividers]
+print(f"answer 2 is {d_index[0] * d_index[1]}")

2022/day14.py

@@ -0,0 +1,144 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+from collections import defaultdict
+from enum import Enum, auto
+from typing import Callable, cast
+
+
+class Cell(Enum):
+    AIR = auto()
+    ROCK = auto()
+    SAND = auto()
+
+    def __str__(self) -> str:
+        return {Cell.AIR: ".", Cell.ROCK: "#", Cell.SAND: "O"}[self]
+
+
+def print_blocks(blocks: dict[tuple[int, int], Cell]):
+    """
+    Print the given set of blocks on a grid.
+
+    Args:
+        blocks: Set of blocks to print.
+    """
+    x_min, y_min, x_max, y_max = (
+        min(x for x, y in blocks),
+        0,
+        max(x for x, y in blocks),
+        max(y for x, y in blocks),
+    )
+
+    for y in range(y_min, y_max + 1):
+        print(
+            "".join(str(blocks.get((x, y), Cell.AIR)) for x in range(x_min, x_max + 1))
+        )
+
+
+def flow(
+    blocks: dict[tuple[int, int], Cell],
+    stop_fn: Callable[[int, int], bool],
+    fill_fn: Callable[[int, int], Cell],
+) -> dict[tuple[int, int], Cell]:
+    """
+    Flow sands onto the given set of blocks
+
+    Args:
+        blocks: Blocks containing ROCK position. Modified in-place.
+        stop_fn: Function called with the last (assumed) position of a grain of
+            sand BEFORE adding it to blocks. If the function returns True, the grain
+            is added and a new one is flowed, otherwise, the whole procedure stops
+            and the function returns (without adding the final grain).
+        fill_fn: Function called when the target position of a grain (during the
+            flowing process) is missing from blocks.
+
+    Returns:
+        The input blocks.
+    """
+
+    y_max = max(y for x, y in blocks)
+
+    while True:
+        x, y = 500, 0
+
+        while y <= y_max:
+
+            moved = False
+            for cx, cy in ((x, y + 1), (x - 1, y + 1), (x + 1, y + 1)):
+                if (cx, cy) not in blocks and fill_fn(cx, cy) == Cell.AIR:
+                    x, y = cx, cy
+                    moved = True
+                elif blocks[cx, cy] == Cell.AIR:
+                    x, y = cx, cy
+                    moved = True
+
+                if moved:
+                    break
+
+            if not moved:
+                break
+
+        if stop_fn(x, y):
+            break
+
+        blocks[x, y] = Cell.SAND
+
+    return blocks
+
+
+# === inputs ===
+
+lines = sys.stdin.read().splitlines()
+
+paths: list[list[tuple[int, int]]] = []
+for line in lines:
+    parts = line.split(" -> ")
+    paths.append(
+        [
+            cast(tuple[int, int], tuple(int(c.strip()) for c in part.split(",")))
+            for part in parts
+        ]
+    )
+
+
+blocks: dict[tuple[int, int], Cell] = {}
+for path in paths:
+    for start, end in zip(path[:-1], path[1:]):
+        x_start = min(start[0], end[0])
+        x_end = max(start[0], end[0]) + 1
+        y_start = min(start[1], end[1])
+        y_end = max(start[1], end[1]) + 1
+
+        for x in range(x_start, x_end):
+            for y in range(y_start, y_end):
+                blocks[x, y] = Cell.ROCK
+
+print_blocks(blocks)
+print()
+
+x_min, y_min, x_max, y_max = (
+    min(x for x, y in blocks),
+    0,
+    max(x for x, y in blocks),
+    max(y for x, y in blocks),
+)
+
+# === part 1 ===
+
+blocks_1 = flow(
+    blocks.copy(), stop_fn=lambda x, y: y > y_max, fill_fn=lambda x, y: Cell.AIR
+)
+print_blocks(blocks_1)
+print(f"answer 1 is {sum(v == Cell.SAND for v in blocks_1.values())}")
+print()
+
+# === part 2 ===
+
+blocks_2 = flow(
+    blocks.copy(),
+    stop_fn=lambda x, y: x == 500 and y == 0,
+    fill_fn=lambda x, y: Cell.AIR if y < y_max + 2 else Cell.ROCK,
+)
+blocks_2[500, 0] = Cell.SAND
+print_blocks(blocks_2)
+print(f"answer 2 is {sum(v == Cell.SAND for v in blocks_2.values())}")

2022/day15.py

@@ -0,0 +1,90 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+import numpy as np
+import parse
+
+
+def part1(sensor_to_beacon: dict[tuple[int, int], tuple[int, int]], row: int) -> int:
+
+    no_beacons_row_l: list[np.ndarray] = []
+
+    for (sx, sy), (bx, by) in sensor_to_beacon.items():
+        d = abs(sx - bx) + abs(sy - by)  # closest
+
+        no_beacons_row_l.append(sx - np.arange(0, d - abs(sy - row) + 1))
+        no_beacons_row_l.append(sx + np.arange(0, d - abs(sy - row) + 1))
+
+    beacons_at_row = set(bx for (bx, by) in sensor_to_beacon.values() if by == row)
+    no_beacons_row = set(np.concatenate(no_beacons_row_l)).difference(beacons_at_row)
+
+    return len(no_beacons_row)
+
+
+def part2_intervals(
+    sensor_to_beacon: dict[tuple[int, int], tuple[int, int]], xy_max: int
+) -> tuple[int, int, int]:
+    from tqdm import trange
+
+    for y in trange(xy_max + 1):
+        its: list[tuple[int, int]] = []
+        for (sx, sy), (bx, by) in sensor_to_beacon.items():
+            d = abs(sx - bx) + abs(sy - by)
+            dx = d - abs(sy - y)
+
+            if dx >= 0:
+                its.append((max(0, sx - dx), min(sx + dx, xy_max)))
+
+        its = sorted(its)
+        s, e = its[0]
+
+        for si, ei in its[1:]:
+            if si > e + 1:
+                return si - 1, y, 4_000_000 * (si - 1) + y
+            if ei > e:
+                e = ei
+
+    return (0, 0, 0)
+
+
+def part2_cplex(
+    sensor_to_beacon: dict[tuple[int, int], tuple[int, int]], xy_max: int
+) -> tuple[int, int, int]:
+    from docplex.mp.model import Model
+
+    m = Model()
+
+    x, y = m.continuous_var_list(2, ub=xy_max, name=["x", "y"])
+
+    for (sx, sy), (bx, by) in sensor_to_beacon.items():
+        d = abs(sx - bx) + abs(sy - by)
+        m.add_constraint(m.abs(x - sx) + m.abs(y - sy) >= d + 1, ctname=f"ct_{sx}_{sy}")
+
+    m.set_objective("min", x + y)
+
+    s = m.solve()
+
+    vx = int(s.get_value(x))
+    vy = int(s.get_value(y))
+    return vx, vy, 4_000_000 * vx + vy
+
+
+lines = sys.stdin.read().splitlines()
+
+sensor_to_beacon: dict[tuple[int, int], tuple[int, int]] = {}
+
+for line in lines:
+    r = parse.parse(
+        "Sensor at x={sx}, y={sy}: closest beacon is at x={bx}, y={by}", line
+    )
+    sensor_to_beacon[int(r["sx"]), int(r["sy"])] = (int(r["bx"]), int(r["by"]))
+
+xy_max = 4_000_000 if max(sensor_to_beacon) > (1_000, 0) else 20
+row = 2_000_000 if max(sensor_to_beacon) > (1_000, 0) else 10
+
+print(f"answer 1 is {part1(sensor_to_beacon, row)}")
+
+# x, y, a2 = part2_cplex(sensor_to_beacon, xy_max)
+x, y, a2 = part2_intervals(sensor_to_beacon, xy_max)
+print(f"answer 2 is {a2} (x={x}, y={y})")

2022/day16.py

@@ -0,0 +1,270 @@
+# -*- encoding: utf-8 -*-
+
+from __future__ import annotations
+
+import heapq
+import itertools
+import re
+import sys
+import time as time_p
+from collections import defaultdict
+from typing import FrozenSet, NamedTuple
+
+from tqdm import tqdm, trange
+
+
+class Pipe(NamedTuple):
+    name: str
+    flow: int
+    tunnels: list[str]
+
+    def __lt__(self, other: object) -> bool:
+        return isinstance(other, Pipe) and other.name < self.name
+
+    def __eq__(self, other: object) -> bool:
+        return isinstance(other, Pipe) and other.name == self.name
+
+    def __hash__(self) -> int:
+        return hash(self.name)
+
+    def __str__(self) -> str:
+        return self.name
+
+    def __repr__(self) -> str:
+        return self.name
+
+
+def breadth_first_search(pipes: dict[str, Pipe], pipe: Pipe) -> dict[Pipe, int]:
+    """
+    Runs a BFS from the given pipe and return the shortest distance (in term of hops)
+    to all other pipes.
+    """
+    queue = [(0, pipe_1)]
+    visited = set()
+    distances: dict[Pipe, int] = {}
+
+    while len(distances) < len(pipes):
+        distance, current = heapq.heappop(queue)
+
+        if current in visited:
+            continue
+
+        visited.add(current)
+        distances[current] = distance
+
+        for tunnel in current.tunnels:
+            heapq.heappush(queue, (distance + 1, pipes[tunnel]))
+
+    return distances
+
+
+def update_with_better(
+    node_at_times: dict[FrozenSet[Pipe], int], flow: int, flowing: FrozenSet[Pipe]
+) -> None:
+    node_at_times[flowing] = max(node_at_times[flowing], flow)
+
+
+def part_1(
+    start_pipe: Pipe,
+    max_time: int,
+    distances: dict[tuple[Pipe, Pipe], int],
+    relevant_pipes: FrozenSet[Pipe],
+):
+
+    node_at_times: dict[int, dict[Pipe, dict[FrozenSet[Pipe], int]]] = defaultdict(
+        lambda: defaultdict(lambda: defaultdict(lambda: 0))
+    )
+    node_at_times[0] = {start_pipe: {frozenset(): 0}}
+
+    for time in range(max_time):
+        for c_pipe, nodes in node_at_times[time].items():
+            for flowing, flow in nodes.items():
+                for target in relevant_pipes:
+
+                    distance = distances[c_pipe, target] + 1
+                    if time + distance >= max_time or target in flowing:
+                        continue
+
+                    update_with_better(
+                        node_at_times[time + distance][target],
+                        flow + sum(pipe.flow for pipe in flowing) * distance,
+                        flowing | {target},
+                    )
+
+                update_with_better(
+                    node_at_times[max_time][c_pipe],
+                    flow + sum(pipe.flow for pipe in flowing) * (max_time - time),
+                    flowing,
+                )
+
+    return max(
+        flow
+        for nodes_of_pipe in node_at_times[max_time].values()
+        for flow in nodes_of_pipe.values()
+    )
+
+
+def part_2(
+    start_pipe: Pipe,
+    max_time: int,
+    pipes: dict[str, Pipe],
+    relevant_pipes: FrozenSet[Pipe],
+    distances: dict[tuple[Pipe, Pipe], int],
+):
+
+    node_at_times: dict[
+        int, dict[tuple[Pipe, Pipe], dict[FrozenSet[Pipe], int]]
+    ] = defaultdict(lambda: defaultdict(lambda: defaultdict(lambda: 0)))
+    node_at_times[0] = {(start_pipe, start_pipe): {frozenset(): 0}}
+
+    # map node + distance to
+    d1, d2, d3, d4 = 0, 0, 0, 0
+    best_flow = 0
+
+    for time in range(max_time):
+        print(
+            f"{time + 1:2d}/{max_time} - {best_flow:4d} - "
+            f"{sum(map(len, node_at_times[time].values())):7d} - "
+            f"{d1:.3f} {d2:.3f} {d3:.3f} {d4:.3f}"
+        )
+
+        d1, d2, d3, d4 = 0, 0, 0, 0
+        for (c_pipe, e_pipe), nodes in node_at_times[time].items():
+            for flowing, flow in nodes.items():
+
+                t1 = time_p.time()
+
+                c_best_flow = (
+                    flow
+                    + sum(pipe.flow for pipe in flowing) * (max_time - time)
+                    + sum(
+                        (
+                            pipe.flow
+                            * (
+                                max_time
+                                - time
+                                - 1
+                                - min(distances[c_pipe, pipe], distances[e_pipe, pipe])
+                            )
+                            for pipe in relevant_pipes
+                            if pipe not in flowing
+                        ),
+                        start=0,
+                    )
+                )
+
+                d1 += time_p.time() - t1
+
+                if c_best_flow < best_flow:
+                    continue
+
+                best_flow = max(
+                    best_flow,
+                    flow + sum(pipe.flow for pipe in flowing) * (max_time - time),
+                )
+
+                t1 = time_p.time()
+
+                if flowing != relevant_pipes:
+                    for c_next_s, e_next_s in itertools.product(
+                        c_pipe.tunnels, e_pipe.tunnels
+                    ):
+
+                        c_next = pipes[c_next_s]
+                        e_next = pipes[e_next_s]
+                        update_with_better(
+                            node_at_times[time + 1][c_next, e_next],
+                            flow + sum(pipe.flow for pipe in flowing),
+                            flowing,
+                        )
+
+                d2 += time_p.time() - t1
+
+                t1 = time_p.time()
+
+                if c_pipe in relevant_pipes and c_pipe not in flowing:
+                    for e_next_s in e_pipe.tunnels:
+
+                        e_next = pipes[e_next_s]
+
+                        update_with_better(
+                            node_at_times[time + 1][c_pipe, e_next],
+                            flow + sum(pipe.flow for pipe in flowing),
+                            flowing | {c_pipe},
+                        )
+
+                if e_pipe in relevant_pipes and e_pipe not in flowing:
+                    for c_next_s in c_pipe.tunnels:
+
+                        c_next = pipes[c_next_s]
+
+                        update_with_better(
+                            node_at_times[time + 1][c_next, e_pipe],
+                            flow + sum(pipe.flow for pipe in flowing),
+                            flowing | {e_pipe},
+                        )
+
+                if (
+                    e_pipe in relevant_pipes
+                    and c_pipe in relevant_pipes
+                    and e_pipe not in flowing
+                    and c_pipe not in flowing
+                ):
+                    update_with_better(
+                        node_at_times[time + 1][c_pipe, e_pipe],
+                        flow + sum(pipe.flow for pipe in flowing),
+                        flowing | {c_pipe, e_pipe},
+                    )
+
+                update_with_better(
+                    node_at_times[max_time][c_pipe, e_pipe],
+                    flow + sum(pipe.flow for pipe in flowing) * (max_time - time),
+                    flowing,
+                )
+
+                d3 += time_p.time() - t1
+
+    return max(
+        flow
+        for nodes_of_pipe in node_at_times[max_time].values()
+        for flow in nodes_of_pipe.values()
+    )
+
+
+# === MAIN ===
+
+
+lines = sys.stdin.read().splitlines()
+
+
+pipes: dict[str, Pipe] = {}
+for line in lines:
+    r = re.match(
+        R"Valve ([A-Z]+) has flow rate=([0-9]+); tunnels? leads? to valves? (.+)",
+        line,
+    )
+    assert r
+
+    g = r.groups()
+
+    pipes[g[0]] = Pipe(g[0], int(g[1]), g[2].split(", "))
+
+# compute distances from one valve to any other
+distances: dict[tuple[Pipe, Pipe], int] = {}
+for pipe_1 in pipes.values():
+    distances.update(
+        {
+            (pipe_1, pipe_2): distance
+            for pipe_2, distance in breadth_first_search(pipes, pipe_1).items()
+        }
+    )
+
+# valves with flow
+relevant_pipes = frozenset(pipe for pipe in pipes.values() if pipe.flow > 0)
+
+
+# 1651, 1653
+print(part_1(pipes["AA"], 30, distances, relevant_pipes))
+
+# 1707, 2223
+print(part_2(pipes["AA"], 26, pipes, relevant_pipes, distances))

2022/day17.py

@@ -0,0 +1,125 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+from typing import Sequence, TypeVar
+
+import numpy as np
+
+T = TypeVar("T")
+
+
+def print_tower(tower: np.ndarray, out: str = "#"):
+    print("-" * (tower.shape[1] + 2))
+    non_empty = False
+    for row in reversed(range(1, tower.shape[0])):
+        if not non_empty and not tower[row, :].any():
+            continue
+        non_empty = True
+        print("|" + "".join(out if c else "." for c in tower[row, :]) + "|")
+    print("+" + "-" * tower.shape[1] + "+")
+
+
+def tower_height(tower: np.ndarray) -> int:
+    return int(tower.shape[0] - tower[::-1, :].argmax(axis=0).min() - 1)
+
+
+def next_cycle(sequence: Sequence[T], index: int) -> tuple[T, int]:
+    t = sequence[index]
+    index = (index + 1) % len(sequence)
+    return t, index
+
+
+ROCKS = [
+    np.array([(0, 0), (0, 1), (0, 2), (0, 3)]),
+    np.array([(0, 1), (1, 0), (1, 1), (1, 2), (2, 1)]),
+    np.array([(0, 0), (0, 1), (0, 2), (1, 2), (2, 2)]),
+    np.array([(0, 0), (1, 0), (2, 0), (3, 0)]),
+    np.array([(0, 0), (0, 1), (1, 0), (1, 1)]),
+]
+
+WIDTH = 7
+START_X = 2
+
+EMPTY_BLOCKS = np.zeros((10, WIDTH), dtype=bool)
+
+
+def build_tower(
+    n_rocks: int,
+    jets: str,
+    early_stop: bool = False,
+    init: np.ndarray = np.ones(WIDTH, dtype=bool),
+) -> tuple[np.ndarray, int, int, dict[int, int]]:
+
+    tower = EMPTY_BLOCKS.copy()
+    tower[0, :] = init
+
+    done_at: dict[tuple[int, int], int] = {}
+    heights: dict[int, int] = {}
+    i_jet, i_rock = 0, 0
+    rock_count = 0
+
+    for rock_count in range(n_rocks):
+
+        if early_stop:
+            if i_rock == 0 and (i_rock, i_jet) in done_at:
+                break
+            done_at[i_rock, i_jet] = rock_count
+
+        y_start = tower.shape[0] - tower[::-1, :].argmax(axis=0).min() + 3
+        rock, i_rock = next_cycle(ROCKS, i_rock)
+
+        rock_y = rock[:, 0] + y_start
+        rock_x = rock[:, 1] + START_X
+
+        if rock_y.max() >= tower.shape[0]:
+            tower = np.concatenate([tower, EMPTY_BLOCKS], axis=0)
+
+        while True:
+
+            jet, i_jet = next_cycle(jets, i_jet)
+
+            dx = 0
+            if jet == ">" and rock_x.max() < WIDTH - 1:
+                dx = 1
+            elif jet == "<" and rock_x.min() > 0:
+                dx = -1
+
+            if dx != 0 and not tower[rock_y, rock_x + dx].any():
+                rock_x = rock_x + dx
+
+            # move down
+            rock_y -= 1
+
+            if tower[rock_y, rock_x].any():
+                rock_y += 1
+                break
+
+        heights[rock_count] = tower_height(tower)
+        tower[rock_y, rock_x] = True
+
+    return tower, rock_count, done_at.get((i_rock, i_jet), -1), heights
+
+
+line = sys.stdin.read().strip()
+
+tower, *_ = build_tower(2022, line)
+answer_1 = tower_height(tower)
+print(f"answer 1 is {answer_1}")
+
+TOTAL_ROCKS = 1_000_000_000_000
+tower_1, n_rocks_1, prev_1, heights_1 = build_tower(TOTAL_ROCKS, line, True)
+assert prev_1 > 0
+
+# 2767 1513
+remaining_rocks = TOTAL_ROCKS - n_rocks_1
+n_repeat_rocks = n_rocks_1 - prev_1
+n_repeat_towers = remaining_rocks // n_repeat_rocks
+
+base_height = heights_1[prev_1]
+repeat_height = heights_1[prev_1 + n_repeat_rocks - 1] - heights_1[prev_1]
+remaining_height = (
+    heights_1[prev_1 + remaining_rocks % n_repeat_rocks] - heights_1[prev_1]
+)
+
+answer_2 = base_height + (n_repeat_towers + 1) * repeat_height + remaining_height
+print(f"answer 2 is {answer_2}")

2022/day18.py

@@ -0,0 +1,53 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+from typing import FrozenSet
+
+import numpy as np
+
+xyz = np.asarray(
+    [
+        tuple(int(x) for x in row.split(","))  # type: ignore
+        for row in sys.stdin.read().splitlines()
+    ]
+)
+
+xyz = xyz - xyz.min(axis=0) + 1
+
+cubes = np.zeros(xyz.max(axis=0) + 3, dtype=bool)
+cubes[xyz[:, 0], xyz[:, 1], xyz[:, 2]] = True
+
+n_dims = len(cubes.shape)
+
+faces = [(-1, 0, 0), (1, 0, 0), (0, -1, 0), (0, 1, 0), (0, 0, -1), (0, 0, 1)]
+
+answer_1 = sum(
+    1 for x, y, z in xyz for dx, dy, dz in faces if not cubes[x + dx, y + dy, z + dz]
+)
+print(f"answer 1 is {answer_1}")
+
+visited = np.zeros_like(cubes, dtype=bool)
+queue = [(0, 0, 0)]
+
+n_faces = 0
+while queue:
+    x, y, z = queue.pop(0)
+
+    if visited[x, y, z]:
+        continue
+
+    visited[x, y, z] = True
+
+    for dx, dy, dz in faces:
+        nx, ny, nz = x + dx, y + dy, z + dz
+        if not all(n >= 0 and n < cubes.shape[i] for i, n in enumerate((nx, ny, nz))):
+            continue
+
+        if visited[nx, ny, nz]:
+            continue
+
+        if cubes[nx, ny, nz]:
+            n_faces += 1
+        else:
+            queue.append((nx, ny, nz))
+print(f"answer 2 is {n_faces}")

2022/day19.py

@@ -0,0 +1,186 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+from typing import Literal
+
+import numpy as np
+import parse
+from tqdm import tqdm
+
+Reagent = Literal["ore", "clay", "obsidian", "geode"]
+REAGENTS: tuple[Reagent, ...] = (
+    "ore",
+    "clay",
+    "obsidian",
+    "geode",
+)
+
+IntOfReagent = dict[Reagent, int]
+
+
+class State:
+    robots: IntOfReagent
+    reagents: IntOfReagent
+
+    def __init__(
+        self,
+        robots: IntOfReagent | None = None,
+        reagents: IntOfReagent | None = None,
+    ):
+        if robots is None:
+            assert reagents is None
+            self.reagents = {reagent: 0 for reagent in REAGENTS}
+            self.robots = {reagent: 0 for reagent in REAGENTS}
+            self.robots["ore"] = 1
+        else:
+            assert robots is not None and reagents is not None
+            self.robots = robots
+            self.reagents = reagents
+
+    def __eq__(self, other) -> bool:
+        return (
+            isinstance(other, State)
+            and self.robots == other.robots
+            and self.reagents == other.reagents
+        )
+
+    def __hash__(self) -> int:
+        return hash(tuple((self.robots[r], self.reagents[r]) for r in REAGENTS))
+
+    def __str__(self) -> str:
+        return "State({}, {})".format(
+            "/".join(str(self.robots[k]) for k in REAGENTS),
+            "/".join(str(self.reagents[k]) for k in REAGENTS),
+        )
+
+    def __repr__(self) -> str:
+        return str(self)
+
+
+def dominates(lhs: State, rhs: State):
+    return all(
+        lhs.robots[r] >= rhs.robots[r] and lhs.reagents[r] >= rhs.reagents[r]
+        for r in REAGENTS
+    )
+
+
+lines = sys.stdin.read().splitlines()
+
+blueprints: list[dict[Reagent, IntOfReagent]] = []
+for line in lines:
+    r = parse.parse(
+        "Blueprint {}: "
+        "Each ore robot costs {:d} ore. "
+        "Each clay robot costs {:d} ore. "
+        "Each obsidian robot costs {:d} ore and {:d} clay. "
+        "Each geode robot costs {:d} ore and {:d} obsidian.",
+        line,
+    )
+
+    blueprints.append(
+        {
+            "ore": {"ore": r[1]},
+            "clay": {"ore": r[2]},
+            "obsidian": {"ore": r[3], "clay": r[4]},
+            "geode": {"ore": r[5], "obsidian": r[6]},
+        }
+    )
+
+
+def run(blueprint: dict[Reagent, dict[Reagent, int]], max_time: int) -> int:
+
+    # since we can only build one robot per time, we do not need more than X robots
+    # of type K where X is the maximum number of K required among all robots, e.g.,
+    # in the first toy blueprint, we need at most 4 ore robots, 14 clay ones and 7
+    # obsidian ones
+    maximums = {
+        name: max(blueprint[r].get(name, 0) for r in REAGENTS) for name in REAGENTS
+    }
+
+    state_after_t: dict[int, set[State]] = {0: [State()]}
+
+    for t in range(1, max_time + 1):
+
+        # list of new states at the end of step t that we are going to prune later
+        states_for_t: set[State] = set()
+
+        for state in state_after_t[t - 1]:
+            robots_that_can_be_built = [
+                robot
+                for robot in REAGENTS
+                if all(
+                    state.reagents[reagent] >= blueprint[robot].get(reagent, 0)
+                    for reagent in REAGENTS
+                )
+            ]
+
+            states_for_t.add(
+                State(
+                    robots=state.robots,
+                    reagents={
+                        reagent: state.reagents[reagent] + state.robots[reagent]
+                        for reagent in REAGENTS
+                    },
+                )
+            )
+
+            if "geode" in robots_that_can_be_built:
+                robots_that_can_be_built = ["geode"]
+            else:
+                robots_that_can_be_built = [
+                    robot
+                    for robot in robots_that_can_be_built
+                    if state.robots[robot] < maximums[robot]
+                ]
+
+            for robot in robots_that_can_be_built:
+                robots = state.robots.copy()
+                robots[robot] += 1
+                reagents = {
+                    reagent: state.reagents[reagent]
+                    + state.robots[reagent]
+                    - blueprint[robot].get(reagent, 0)
+                    for reagent in REAGENTS
+                }
+                states_for_t.add(State(robots=robots, reagents=reagents))
+
+        # use numpy to switch computation of dominated states -> store each state
+        # as a 8 array and use numpy broadcasting to find dominated states
+        states_after = np.asarray(list(states_for_t))
+        np_states = np.array(
+            [
+                [state.robots[r] for r in REAGENTS]
+                + [state.reagents[r] for r in REAGENTS]
+                for state in states_after
+            ]
+        )
+
+        to_keep = []
+        while len(np_states) > 0:
+            first_dom = (np_states[1:] >= np_states[0]).all(axis=1).any()
+
+            if first_dom:
+                np_states = np_states[1:]
+            else:
+                to_keep.append(np_states[0])
+                np_states = np_states[1:][~(np_states[1:] <= np_states[0]).all(axis=1)]
+
+        state_after_t[t] = {
+            State(
+                robots=dict(zip(REAGENTS, row[:4])),
+                reagents=dict(zip(REAGENTS, row[4:])),
+            )
+            for row in to_keep
+        }
+
+    return max(state.reagents["geode"] for state in state_after_t[max_time])
+
+
+answer_1 = sum(
+    (i_blueprint + 1) * run(blueprint, 24)
+    for i_blueprint, blueprint in enumerate(blueprints)
+)
+print(f"answer 1 is {answer_1}")
+
+answer_2 = run(blueprints[0], 32) * run(blueprints[1], 32) * run(blueprints[2], 32)
+print(f"answer 2 is {answer_2}")

2022/day2.py

@@ -0,0 +1,55 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+
+def score_1(ux: int, vx: int) -> int:
+    # here ux and vx are both moves: 0 = rock, 1 = paper, 2 = scissor
+    #
+
+    # 1. to get the score of the move/shape, we simply add 1 -> vx + 1
+    # 2. to get the score of the outcome (loss/draw/win), we use the fact that the
+    #    winning hand is always the opponent hand (ux) + 1 in modulo-3 arithmetic:
+    #    - (ux - vx) % 3 gives us 0 for a draw, 1 for a loss and 2 for a win
+    #    - 1 - ((ux - vx) % 3) gives us -1 for a win, 0 for a loss and 1 for a draw
+    #    - (1 - ((ux - vx) % 3)) gives us 0 / 1 / 2 for loss / draw / win
+    #    - the above can be rewritten as ((1 - (ux - vx)) % 3)
+    #    we can then simply multiply this by 3 to get the outcome score
+    #
+    return (vx + 1) + ((1 - (ux - vx)) % 3) * 3
+
+
+def score_2(ux: int, vx: int) -> int:
+    # here ux is the opponent move (0 = rock, 1 = paper, 2 = scissor) and vx is the
+    # outcome (0 = loss, 1 = draw, 2 = win)
+    #
+
+    # 1. to get the score to the move/shape, we need to find it (as 0, 1 or 2) and then
+    #    add 1 to it
+    #    - (vx - 1) gives the offset from the opponent shape (-1 for a loss, 0 for a
+    #      draw and 1 for a win)
+    #    - from the offset, we can retrieve the shape by adding the opponent shape and
+    #      using modulo-3 arithmetic -> (ux + vx - 1) % 3
+    #    - we then add 1 to get the final shape score
+    # 2. to get the score of the outcome, we can simply multiply vx by 3 -> vx * 3
+    return (ux + vx - 1) % 3 + 1 + vx * 3
+
+
+lines = sys.stdin.readlines()
+
+# the solution relies on replacing rock / paper / scissor by values 0 / 1 / 2 and using
+# modulo-3 arithmetic
+#
+# in modulo-3 arithmetic, the winning move is 1 + the opponent move (e.g., winning move
+# if opponent plays 0 is 1, or 0 if opponent plays 2 (0 = (2 + 1 % 3)))
+#
+
+# we read the lines in a Nx2 in array with value 0/1/2 instead of A/B/C or X/Y/Z for
+# easier manipulation
+values = [(ord(row[0]) - ord("A"), ord(row[2]) - ord("X")) for row in lines]
+
+# part 1 - 13526
+print(f"score 1 is {sum(score_1(*v) for v in values)}")
+
+# part 2 - 14204
+print(f"score 2 is {sum(score_2(*v) for v in values)}")

2022/day20.py

@@ -0,0 +1,77 @@
+# -*- encoding: utf-8 -*-
+
+from __future__ import annotations
+
+import sys
+
+
+class Number:
+    current: int
+    value: int
+
+    def __init__(self, value: int):
+        self.current = 0
+        self.value = value
+
+    def __str__(self):
+        return str(self.value)
+
+    def __repr__(self):
+        return str(self)
+
+
+def decrypt(numbers: list[Number], key: int, rounds: int) -> int:
+
+    numbers = numbers.copy()
+    original = numbers.copy()
+
+    for index, number in enumerate(numbers):
+        number.current = index
+
+    for _ in range(rounds):
+        for number in original:
+            index = number.current
+            offset = (number.value * key) % (len(numbers) - 1)
+            target = index + offset
+
+            # need to wrap
+            if target >= len(numbers):
+                target = offset - (len(numbers) - index) + 1
+
+                for number_2 in numbers[target:index]:
+                    number_2.current += 1
+
+                numbers = (
+                    numbers[:target]
+                    + [number]
+                    + numbers[target:index]
+                    + numbers[index + 1 :]
+                )
+            else:
+                for number_2 in numbers[index : target + 1]:
+                    number_2.current -= 1
+
+                numbers = (
+                    numbers[:index]
+                    + numbers[index + 1 : target + 1]
+                    + [number]
+                    + numbers[target + 1 :]
+                )
+            number.current = target
+
+    index_of_0 = next(
+        filter(lambda index: numbers[index].value == 0, range(len(numbers)))
+    )
+    return sum(
+        numbers[(index_of_0 + offset) % len(numbers)].value * key
+        for offset in (1000, 2000, 3000)
+    )
+
+
+numbers = [Number(int(x)) for i, x in enumerate(sys.stdin.readlines())]
+
+answer_1 = decrypt(numbers, 1, 1)
+print(f"answer 1 is {answer_1}")
+
+answer_2 = decrypt(numbers, 811589153, 10)
+print(f"answer 2 is {answer_2}")

2022/day21.py

@@ -0,0 +1,109 @@
+# -*- encoding: utf-8 -*-
+
+import operator
+import sys
+from typing import Callable
+
+
+def compute(monkeys: dict[str, int | tuple[str, str, str]], monkey: str) -> int:
+    value = monkeys[monkey]
+    if isinstance(value, int):
+        return value
+    else:
+        op: dict[str, Callable[[int, int], int]] = {
+            "+": operator.add,
+            "-": operator.sub,
+            "*": operator.mul,
+            "/": operator.floordiv,
+        }
+        value = op[value[1]](compute(monkeys, value[0]), compute(monkeys, value[2]))
+        monkeys[monkey] = value
+        return value
+
+
+def invert(
+    monkeys: dict[str, int | tuple[str, str, str]], monkey: str, target: int
+) -> dict[str, int | tuple[str, str, str]]:
+    """
+    Revert the given mapping from monkey name to value or operation such that
+    the value from 'monkey' is computable by inverting operation until the root is
+    found.
+
+    Args:
+        monkeys: Dictionary of monkeys, that will be updated and returned.
+        monkey: Name of the monkey to start from.
+        target: Target value to set for the monkey that depends on root.
+
+    Returns:
+        The given dictionary of monkeys.
+    """
+
+    monkeys = monkeys.copy()
+
+    depends: dict[str, str] = {}
+    for m, v in monkeys.items():
+        if isinstance(v, int):
+            continue
+
+        op1, _, op2 = v
+
+        assert op1 not in depends
+        assert op2 not in depends
+        depends[op1] = m
+        depends[op2] = m
+
+    invert_op = {"+": "-", "-": "+", "*": "/", "/": "*"}
+
+    current = monkey
+    while True:
+        dep = depends[current]
+
+        if dep == "root":
+            monkeys[current] = target
+            break
+
+        val = monkeys[dep]
+        assert not isinstance(val, int)
+
+        op1, ope, op2 = val
+
+        if op1 == current:
+            monkeys[current] = (dep, invert_op[ope], op2)
+        elif ope in ("+", "*"):
+            monkeys[current] = (dep, invert_op[ope], op1)
+        else:
+            monkeys[current] = (op1, ope, dep)
+
+        current = dep
+
+    return monkeys
+
+
+lines = sys.stdin.read().splitlines()
+
+monkeys: dict[str, int | tuple[str, str, str]] = {}
+
+op_monkeys: set[str] = set()
+
+for line in lines:
+    parts = line.split(":")
+    name = parts[0].strip()
+
+    try:
+        value = int(parts[1].strip())
+        monkeys[name] = value
+    except ValueError:
+        op1, ope, op2 = parts[1].strip().split()
+        monkeys[name] = (op1, ope, op2)
+
+        op_monkeys.add(name)
+
+
+answer_1 = compute(monkeys.copy(), "root")
+print(f"answer 1 is {answer_1}")
+
+# assume the second operand of 'root' can be computed, and the first one depends on
+# humn, which is the case is my input and the test input
+p1, _, p2 = monkeys["root"]  # type: ignore
+answer_2 = compute(invert(monkeys, "humn", compute(monkeys.copy(), p2)), "humn")
+print(f"answer 2 is {answer_2}")

2022/day22.py

@@ -0,0 +1,226 @@
+# -*- encoding: utf-8 -*-
+
+import re
+import sys
+from typing import Callable
+
+import numpy as np
+
+VOID, EMPTY, WALL = 0, 1, 2
+TILE_FROM_CHAR = {" ": VOID, ".": EMPTY, "#": WALL}
+
+SCORES = {"E": 0, "S": 1, "W": 2, "N": 3}
+
+
+board_map_s, direction_s = sys.stdin.read().split("\n\n")
+
+# board
+board_lines = board_map_s.splitlines()
+max_line = max(len(line) for line in board_lines)
+board = np.array(
+    [
+        [TILE_FROM_CHAR[c] for c in row] + [VOID] * (max_line - len(row))
+        for row in board_map_s.splitlines()
+    ]
+)
+
+directions = [
+    int(p1) if p2 else p1 for p1, p2 in re.findall(R"(([0-9])+|L|R)", direction_s)
+]
+
+
+# find on each row and column the first and last non-void
+row_first_non_void = np.argmax(board != VOID, axis=1)
+row_last_non_void = board.shape[1] - np.argmax(board[:, ::-1] != VOID, axis=1) - 1
+col_first_non_void = np.argmax(board != VOID, axis=0)
+col_last_non_void = board.shape[0] - np.argmax(board[::-1, :] != VOID, axis=0) - 1
+
+
+faces = np.zeros_like(board)
+size = np.gcd(board.shape[0], board.shape[1])
+for row in range(0, board.shape[0], size):
+    for col in range(row_first_non_void[row], row_last_non_void[row], size):
+        faces[row : row + size, col : col + size] = faces.max() + 1
+
+SIZE = np.gcd(*board.shape)
+
+# TODO: deduce this from the actual cube...
+faces_wrap: dict[int, dict[str, Callable[[int, int], tuple[int, int, str]]]]
+
+if board.shape == (12, 16):  # example
+    faces_wrap = {
+        1: {
+            "W": lambda y, x: (4, 4 + y, "S"),  # 3N
+            "N": lambda y, x: (4, 11 - x, "S"),  # 2N
+            "E": lambda y, x: (11 - y, 15, "W"),  # 6E
+        },
+        2: {
+            "W": lambda y, x: (11, 19 - y, "N"),  # 6S
+            "N": lambda y, x: (0, 11 - y, "S"),  # 1N
+            "S": lambda y, x: (11, 11 - x, "N"),  # 5S
+        },
+        3: {
+            "N": lambda y, x: (x - 4, 8, "E"),  # 1W
+            "S": lambda y, x: (15 - x, 8, "E"),  # 5W
+        },
+        4: {"E": lambda y, x: (8, 19 - y, "S")},  # 6N
+        5: {
+            "W": lambda y, x: (7, 15 - y, "N"),  # 3S
+            "S": lambda y, x: (7, 11 - x, "N"),  # 2S
+        },
+        6: {
+            "N": lambda y, x: (19 - x, 11, "W"),  # 4E
+            "E": lambda y, x: (11 - y, 11, "W"),  # 1E
+            "S": lambda y, x: (19 - x, 0, "E"),  # 2W
+        },
+    }
+
+else:
+    faces_wrap = {
+        1: {
+            "W": lambda y, x: (3 * SIZE - y - 1, 0, "E"),  # 4W
+            "N": lambda y, x: (2 * SIZE + x, 0, "E"),  # 6W
+        },
+        2: {
+            "N": lambda y, x: (4 * SIZE - 1, x - 2 * SIZE, "N"),  # 6S
+            "E": lambda y, x: (3 * SIZE - y - 1, 2 * SIZE - 1, "W"),  # 5E
+            "S": lambda y, x: (x - SIZE, 2 * SIZE - 1, "W"),  # 3E
+        },
+        3: {
+            "W": lambda y, x: (2 * SIZE, y - SIZE, "S"),  # 4N
+            "E": lambda y, x: (SIZE - 1, SIZE + y, "N"),  # 2S
+        },
+        4: {
+            "W": lambda y, x: (3 * SIZE - y - 1, SIZE, "E"),  # 1W
+            "N": lambda y, x: (SIZE + x, SIZE, "E"),  # 3W
+        },
+        5: {
+            "E": lambda y, x: (3 * SIZE - y - 1, 3 * SIZE - 1, "W"),  # 2E
+            "S": lambda y, x: (2 * SIZE + x, SIZE - 1, "W"),  # 6E
+        },
+        6: {
+            "W": lambda y, x: (0, y - 2 * SIZE, "S"),  # 1N
+            "E": lambda y, x: (3 * SIZE - 1, y - 2 * SIZE, "N"),  # 5S
+            "S": lambda y, x: (0, x + 2 * SIZE, "S"),  # 2N
+        },
+    }
+
+
+def wrap_part_1(y0: int, x0: int, r0: str) -> tuple[int, int, str]:
+    if r0 == "E":
+        return y0, row_first_non_void[y0], r0
+    elif r0 == "S":
+        return col_first_non_void[x0], x0, r0
+    elif r0 == "W":
+        return y0, row_last_non_void[y0], r0
+    elif r0 == "N":
+        return col_last_non_void[x0], x0, r0
+
+    assert False
+
+
+def wrap_part_2(y0: int, x0: int, r0: str) -> tuple[int, int, str]:
+    cube = faces[y0, x0]
+    assert r0 in faces_wrap[cube]
+    return faces_wrap[cube][r0](y0, x0)
+
+
+def run(wrap: Callable[[int, int, str], tuple[int, int, str]]) -> tuple[int, int, str]:
+
+    y0 = 0
+    x0 = np.where(board[0] == EMPTY)[0][0]
+    r0 = "E"
+
+    for direction in directions:
+        if isinstance(direction, int):
+            while direction > 0:
+                if r0 == "E":
+                    xi = np.where(board[y0, x0 + 1 : x0 + direction + 1] == WALL)[0]
+                    if len(xi):
+                        x0 = x0 + xi[0]
+                        direction = 0
+                    elif (
+                        x0 + direction < board.shape[1]
+                        and board[y0, x0 + direction] == EMPTY
+                    ):
+                        x0 = x0 + direction
+                        direction = 0
+                    else:
+                        y0_t, x0_t, r0_t = wrap(y0, x0, r0)
+                        if board[y0_t, x0_t] == WALL:
+                            x0 = row_last_non_void[y0]
+                            direction = 0
+                        else:
+                            direction = direction - (row_last_non_void[y0] - x0) - 1
+                            y0, x0, r0 = y0_t, x0_t, r0_t
+                elif r0 == "S":
+                    yi = np.where(board[y0 + 1 : y0 + direction + 1, x0] == WALL)[0]
+                    if len(yi):
+                        y0 = y0 + yi[0]
+                        direction = 0
+                    elif (
+                        y0 + direction < board.shape[0]
+                        and board[y0 + direction, x0] == EMPTY
+                    ):
+                        y0 = y0 + direction
+                        direction = 0
+                    else:
+                        y0_t, x0_t, r0_t = wrap(y0, x0, r0)
+                        if board[y0_t, x0_t] == WALL:
+                            y0 = col_last_non_void[x0]
+                            direction = 0
+                        else:
+                            direction = direction - (col_last_non_void[x0] - y0) - 1
+                            y0, x0, r0 = y0_t, x0_t, r0_t
+                elif r0 == "W":
+                    left = max(x0 - direction - 1, 0)
+                    xi = np.where(board[y0, left:x0] == WALL)[0]
+                    if len(xi):
+                        x0 = left + xi[-1] + 1
+                        direction = 0
+                    elif x0 - direction >= 0 and board[y0, x0 - direction] == EMPTY:
+                        x0 = x0 - direction
+                        direction = 0
+                    else:
+                        y0_t, x0_t, r0_t = wrap(y0, x0, r0)
+                        if board[y0_t, x0_t] == WALL:
+                            x0 = row_first_non_void[y0]
+                            direction = 0
+                        else:
+                            direction = direction - (x0 - row_first_non_void[y0]) - 1
+                            y0, x0, r0 = y0_t, x0_t, r0_t
+                elif r0 == "N":
+                    top = max(y0 - direction - 1, 0)
+                    yi = np.where(board[top:y0, x0] == WALL)[0]
+                    if len(yi):
+                        y0 = top + yi[-1] + 1
+                        direction = 0
+                    elif y0 - direction >= 0 and board[y0 - direction, x0] == EMPTY:
+                        y0 = y0 - direction
+                        direction = 0
+                    else:
+                        y0_t, x0_t, r0_t = wrap(y0, x0, r0)
+                        if board[y0_t, x0_t] == WALL:
+                            y0 = col_first_non_void[x0]
+                            direction = 0
+                        else:
+                            direction = direction - (y0 - col_first_non_void[x0]) - 1
+                            y0, x0, r0 = y0_t, x0_t, r0_t
+        else:
+            r0 = {
+                "E": {"L": "N", "R": "S"},
+                "N": {"L": "W", "R": "E"},
+                "W": {"L": "S", "R": "N"},
+                "S": {"L": "E", "R": "W"},
+            }[r0][direction]
+
+    return y0, x0, r0
+
+
+y1, x1, r1 = run(wrap_part_1)
+answer_1 = 1000 * (1 + y1) + 4 * (1 + x1) + SCORES[r1]
+print(f"answer 1 is {answer_1}")
+
+y2, x2, r2 = run(wrap_part_2)
+answer_2 = 1000 * (1 + y2) + 4 * (1 + x2) + SCORES[r2]
+print(f"answer 2 is {answer_2}")

2022/day23.py

@@ -0,0 +1,105 @@
+# -*- encoding: utf-8 -*-
+
+import itertools
+import sys
+from collections import defaultdict
+
+Directions = list[
+    tuple[
+        str, tuple[int, int], tuple[tuple[int, int], tuple[int, int], tuple[int, int]]
+    ]
+]
+
+# (Y, X)
+DIRECTIONS: Directions = [
+    ("N", (-1, 0), ((-1, -1), (-1, 0), (-1, 1))),
+    ("S", (1, 0), ((1, -1), (1, 0), (1, 1))),
+    ("W", (0, -1), ((-1, -1), (0, -1), (1, -1))),
+    ("E", (0, 1), ((-1, 1), (0, 1), (1, 1))),
+]
+
+
+def min_max_yx(positions: set[tuple[int, int]]) -> tuple[int, int, int, int]:
+    ys, xs = {y for y, x in positions}, {x for y, x in positions}
+    return min(ys), min(xs), max(ys), max(xs)
+
+
+def print_positions(positions: set[tuple[int, int]]):
+    min_y, min_x, max_y, max_x = min_max_yx(positions)
+    print(
+        "\n".join(
+            "".join(
+                "#" if (y, x) in positions else "." for x in range(min_x - 1, max_x + 2)
+            )
+            for y in range(min_y - 1, max_y + 2)
+        )
+    )
+
+
+def round(
+    positions: set[tuple[int, int]],
+    directions: Directions,
+):
+    to_move: dict[tuple[int, int], list[tuple[int, int]]] = defaultdict(lambda: [])
+    for (y, x) in positions:
+        elves = {
+            (dy, dx): (y + dy, x + dx) in positions
+            for dy, dx in itertools.product((-1, 0, 1), (-1, 0, 1))
+            if (dy, dx) != (0, 0)
+        }
+
+        if not any(elves.values()):
+            to_move[y, x].append((y, x))
+            continue
+
+        found: str | None = None
+        for d, (dy, dx), d_yx_check in directions:
+            if not any(elves[dy, dx] for dy, dx in d_yx_check):
+                found = d
+                to_move[y + dy, x + dx].append((y, x))
+                break
+        if found is None:
+            to_move[y, x].append((y, x))
+
+    positions.clear()
+    for ty, tx in to_move:
+        if len(to_move[ty, tx]) > 1:
+            positions.update(to_move[ty, tx])
+        else:
+            positions.add((ty, tx))
+
+    directions.append(directions.pop(0))
+
+
+POSITIONS = {
+    (i, j)
+    for i, row in enumerate(sys.stdin.read().splitlines())
+    for j, col in enumerate(row)
+    if col == "#"
+}
+
+# === part 1 ===
+
+p1, d1 = POSITIONS.copy(), DIRECTIONS.copy()
+for r in range(10):
+    round(p1, d1)
+
+min_y, min_x, max_y, max_x = min_max_yx(p1)
+answer_1 = sum(
+    (y, x) not in p1 for y in range(min_y, max_y + 1) for x in range(min_x, max_x + 1)
+)
+print(f"answer 1 is {answer_1}")
+
+# === part 2 ===
+
+p2, d2 = POSITIONS.copy(), DIRECTIONS.copy()
+answer_2 = 0
+while True:
+    answer_2 += 1
+    backup = p2.copy()
+    round(p2, d2)
+
+    if backup == p2:
+        break
+
+print(f"answer 2 is {answer_2}")

2022/day24.py

@@ -0,0 +1,100 @@
+# -*- encoding: utf-8 -*-
+
+import heapq
+import math
+import sys
+from collections import defaultdict
+
+lines = sys.stdin.read().splitlines()
+
+winds = {
+    (i - 1, j - 1, lines[i][j])
+    for i in range(1, len(lines) - 1)
+    for j in range(1, len(lines[i]) - 1)
+    if lines[i][j] != "."
+}
+
+n_rows, n_cols = len(lines) - 2, len(lines[0]) - 2
+CYCLE = math.lcm(n_rows, n_cols)
+
+east_winds = [{j for j in range(n_cols) if (i, j, ">") in winds} for i in range(n_rows)]
+west_winds = [{j for j in range(n_cols) if (i, j, "<") in winds} for i in range(n_rows)]
+north_winds = [
+    {i for i in range(n_rows) if (i, j, "^") in winds} for j in range(n_cols)
+]
+south_winds = [
+    {i for i in range(n_rows) if (i, j, "v") in winds} for j in range(n_cols)
+]
+
+
+def run(start: tuple[int, int], start_cycle: int, end: tuple[int, int]):
+    def heuristic(y: int, x: int) -> int:
+        return abs(end[0] - y) + abs(end[1] - x)
+
+    # (distance + heuristic, distance, (start_pos, cycle))
+    queue = [(heuristic(start[0], start[1]), 0, ((start[0], start[1]), start_cycle))]
+    visited: set[tuple[tuple[int, int], int]] = set()
+    distances: dict[tuple[int, int], dict[int, int]] = defaultdict(lambda: {})
+
+    while queue:
+        _, distance, ((y, x), cycle) = heapq.heappop(queue)
+
+        if ((y, x), cycle) in visited:
+            continue
+
+        distances[y, x][cycle] = distance
+
+        visited.add(((y, x), cycle))
+
+        if (y, x) == (end[0], end[1]):
+            break
+
+        for dy, dx in (0, 0), (-1, 0), (1, 0), (0, -1), (0, 1):
+            ty = y + dy
+            tx = x + dx
+
+            n_cycle = (cycle + 1) % CYCLE
+
+            if (ty, tx) == end:
+                heapq.heappush(queue, (distance + 1, distance + 1, ((ty, tx), n_cycle)))
+                break
+
+            if ((ty, tx), n_cycle) in visited:
+                continue
+
+            if (ty, tx) != start and (ty < 0 or tx < 0 or ty >= n_rows or tx >= n_cols):
+                continue
+
+            if (ty, tx) != start:
+                if (ty - n_cycle) % n_rows in south_winds[tx]:
+                    continue
+                if (ty + n_cycle) % n_rows in north_winds[tx]:
+                    continue
+                if (tx + n_cycle) % n_cols in west_winds[ty]:
+                    continue
+                if (tx - n_cycle) % n_cols in east_winds[ty]:
+                    continue
+
+            heapq.heappush(
+                queue,
+                ((heuristic(ty, tx) + distance + 1, distance + 1, ((ty, tx), n_cycle))),
+            )
+
+    return distances, next(iter(distances[end].values()))
+
+
+start = (
+    -1,
+    next(j for j in range(1, len(lines[0]) - 1) if lines[0][j] == ".") - 1,
+)
+end = (
+    n_rows,
+    next(j for j in range(1, len(lines[-1]) - 1) if lines[-1][j] == ".") - 1,
+)
+
+distances_1, forward_1 = run(start, 0, end)
+print(f"answer 1 is {forward_1}")
+
+distances_2, return_1 = run(end, next(iter(distances_1[end].keys())), start)
+distances_3, forward_2 = run(start, next(iter(distances_2[start].keys())), end)
+print(f"answer 2 is {forward_1 + return_1 + forward_2}")

2022/day25.py

@@ -0,0 +1,29 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+lines = sys.stdin.read().splitlines()
+
+coeffs = {"2": 2, "1": 1, "0": 0, "-": -1, "=": -2}
+
+
+def snafu2number(number: str) -> int:
+    value = 0
+    for c in number:
+        value *= 5
+        value += coeffs[c]
+    return value
+
+
+def number2snafu(number: int) -> str:
+    values = ["0", "1", "2", "=", "-"]
+    res = ""
+    while number > 0:
+        mod = number % 5
+        res = res + values[mod]
+        number = number // 5 + int(mod >= 3)
+    return "".join(reversed(res))
+
+
+answer_1 = number2snafu(sum(map(snafu2number, lines)))
+print(f"answer 1 is {answer_1}")

2022/day3.py

@@ -0,0 +1,25 @@
+# -*- encoding: utf-8 -*-
+
+import string
+import sys
+
+lines = [line.strip() for line in sys.stdin.readlines()]
+
+# extract content of each part
+parts = [(set(line[: len(line) // 2]), set(line[len(line) // 2 :])) for line in lines]
+
+# priorities
+priorities = {c: i + 1 for i, c in enumerate(string.ascii_letters)}
+
+# part 1
+part1 = sum(priorities[c] for p1, p2 in parts for c in p1.intersection(p2))
+print(f"score 1 is {part1}")
+
+# part 2
+n_per_group = 3
+part2 = sum(
+    priorities[c]
+    for i in range(0, len(lines), n_per_group)
+    for c in set(lines[i]).intersection(*lines[i + 1 : i + n_per_group])
+)
+print(f"score 2 is {part2}")

2022/day4.py

@@ -0,0 +1,19 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+lines = [line.strip() for line in sys.stdin.readlines()]
+
+
+def make_range(value: str) -> set[int]:
+    parts = value.split("-")
+    return set(range(int(parts[0]), int(parts[1]) + 1))
+
+
+sections = [tuple(make_range(part) for part in line.split(",")) for line in lines]
+
+score_1 = sum(s1.issubset(s2) or s2.issubset(s1) for s1, s2 in sections)
+print(f"score 1 is {score_1}")
+
+score_2 = sum(bool(s1.intersection(s2)) for s1, s2 in sections)
+print(f"score 1 is {score_2}")

2022/day5.py

@@ -0,0 +1,43 @@
+# -*- encoding: utf-8 -*-
+
+import copy
+import sys
+
+blocks_s, moves_s = (part.splitlines() for part in sys.stdin.read().split("\n\n"))
+
+blocks: dict[str, list[str]] = {stack: [] for stack in blocks_s[-1].split()}
+
+# this codes assumes that the lines are regular, i.e., 4 characters per "crate" in the
+# form of '[X] ' (including the trailing space)
+#
+for block in blocks_s[-2::-1]:
+    for stack, index in zip(blocks, range(0, len(block), 4)):
+        crate = block[index + 1 : index + 2].strip()
+
+        if crate:
+            blocks[stack].append(crate)
+
+# part 1 - deep copy for part 2
+blocks_1 = copy.deepcopy(blocks)
+
+for move in moves_s:
+    _, count_s, _, from_, _, to_ = move.strip().split()
+
+    for _i in range(int(count_s)):
+        blocks_1[to_].append(blocks_1[from_].pop())
+
+# part 2
+blocks_2 = copy.deepcopy(blocks)
+
+for move in moves_s:
+    _, count_s, _, from_, _, to_ = move.strip().split()
+    count = int(count_s)
+
+    blocks_2[to_].extend(blocks_2[from_][-count:])
+    del blocks_2[from_][-count:]
+
+answer_1 = "".join(s[-1] for s in blocks_1.values())
+print(f"answer 1 is {answer_1}")
+
+answer_2 = "".join(s[-1] for s in blocks_2.values())
+print(f"answer 2 is {answer_2}")

2022/day6.py

@@ -0,0 +1,17 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+
+def index_of_first_n_differents(data: str, n: int) -> int:
+    for i in range(len(data)):
+        if len(set(data[i : i + n])) == n:
+            return i + n
+    return -1
+
+
+data = sys.stdin.read().strip()
+
+
+print(f"answer 1 is {index_of_first_n_differents(data, 4)}")
+print(f"answer 2 is {index_of_first_n_differents(data, 14)}")

2022/day7.py

@@ -0,0 +1,82 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+from pathlib import Path
+
+lines = sys.stdin.read().splitlines()
+
+# we are going to use Path to create path and go up/down in the file tree since it
+# implements everything we need
+#
+# we can use .resolve() to get normalized path, although this will add C:\ to all paths
+# on Windows but that is not an issue since only the sizes matter
+#
+
+# mapping from path to list of files or directories
+trees: dict[Path, list[Path]] = {}
+
+# mapping from paths to either size (for file) or -1 for directory
+sizes: dict[Path, int] = {}
+
+# first line must be a cd otherwise we have no idea where we are
+assert lines[0].startswith("$ cd")
+base_path = Path(lines[0].strip("$").split()[1]).resolve()
+cur_path = base_path
+
+trees[cur_path] = []
+sizes[cur_path] = -1
+
+for line in lines[1:]:
+    # command
+    if line.startswith("$"):
+        parts = line.strip("$").strip().split()
+        command = parts[0]
+
+        if command == "cd":
+            cur_path = cur_path.joinpath(parts[1]).resolve()
+
+            # just initialize the lis of files if not already done
+            if cur_path not in trees:
+                trees[cur_path] = []
+        else:
+            # nothing to do here
+            pass
+
+    # fill the current path
+    else:
+        parts = line.split()
+        name: str = parts[1]
+        if line.startswith("dir"):
+            size = -1
+        else:
+            size = int(parts[0])
+
+        path = cur_path.joinpath(name)
+        trees[cur_path].append(path)
+        sizes[path] = size
+
+
+def compute_size(path: Path) -> int:
+    size = sizes[path]
+
+    if size >= 0:
+        return size
+
+    return sum(compute_size(sub) for sub in trees[path])
+
+
+acc_sizes = {path: compute_size(path) for path in trees}
+
+# part 1
+answer_1 = sum(size for size in acc_sizes.values() if size <= 100_000)
+print(f"answer 1 is {answer_1}")
+
+# part 2
+total_space = 70_000_000
+update_space = 30_000_000
+free_space = total_space - acc_sizes[base_path]
+
+to_free_space = update_space - free_space
+
+answer_2 = min(size for size in acc_sizes.values() if size >= to_free_space)
+print(f"answer 2 is {answer_2}")

2022/day8.py

@@ -0,0 +1,54 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+import numpy as np
+
+lines = sys.stdin.read().splitlines()
+
+trees = np.array([[int(x) for x in row] for row in lines])
+
+# answer 1
+highest_trees = np.ones(trees.shape + (4,), dtype=int) * -1
+highest_trees[1:-1, 1:-1] = [
+    [
+        [
+            trees[:i, j].max(),
+            trees[i + 1 :, j].max(),
+            trees[i, :j].max(),
+            trees[i, j + 1 :].max(),
+        ]
+        for j in range(1, trees.shape[1] - 1)
+    ]
+    for i in range(1, trees.shape[0] - 1)
+]
+
+answer_1 = (highest_trees.min(axis=2) < trees).sum()
+print(f"answer 1 is {answer_1}")
+
+
+def viewing_distance(row_of_trees: np.ndarray, value: int) -> int:
+    w = np.where(row_of_trees >= value)[0]
+
+    if not w.size:
+        return len(row_of_trees)
+
+    return w[0] + 1
+
+
+# answer 2
+v_distances = np.zeros(trees.shape + (4,), dtype=int)
+v_distances[1:-1, 1:-1, :] = [
+    [
+        [
+            viewing_distance(trees[i - 1 :: -1, j], trees[i, j]),
+            viewing_distance(trees[i, j - 1 :: -1], trees[i, j]),
+            viewing_distance(trees[i, j + 1 :], trees[i, j]),
+            viewing_distance(trees[i + 1 :, j], trees[i, j]),
+        ]
+        for j in range(1, trees.shape[1] - 1)
+    ]
+    for i in range(1, trees.shape[0] - 1)
+]
+answer_2 = np.prod(v_distances, axis=2).max()
+print(f"answer 2 is {answer_2}")

2022/day9.py

@@ -0,0 +1,64 @@
+# -*- encoding: utf-8 -*-
+
+import sys
+
+import numpy as np
+
+
+def move(head: tuple[int, int], command: str) -> tuple[int, int]:
+
+    h_col, h_row = head
+
+    if command == "L":
+        head = (h_col - 1, h_row)
+    elif command == "R":
+        head = (h_col + 1, h_row)
+    elif command == "U":
+        head = (h_col, h_row + 1)
+    elif command == "D":
+        head = (h_col, h_row - 1)
+
+    return head
+
+
+def follow(head: tuple[int, int], tail: tuple[int, int]) -> tuple[int, int]:
+
+    h_col, h_row = head
+    t_col, t_row = tail
+
+    if abs(t_col - h_col) <= 1 and abs(t_row - h_row) <= 1:
+        return tail
+
+    return t_col + np.sign(h_col - t_col), t_row + np.sign(h_row - t_row)
+
+
+def run(commands: list[str], n_blocks: int) -> list[tuple[int, int]]:
+
+    blocks = [(0, 0) for _ in range(n_blocks)]
+    visited = [blocks[-1]]
+
+    for command in commands:
+        blocks[0] = move(blocks[0], command)
+
+        for i in range(0, n_blocks - 1):
+            blocks[i + 1] = follow(blocks[i], blocks[i + 1])
+
+        visited.append(blocks[-1])
+
+    return visited
+
+
+lines = sys.stdin.read().splitlines()
+
+# flatten the commands
+commands: list[str] = []
+for line in lines:
+    d, c = line.split()
+    commands.extend(d * int(c))
+
+
+visited_1 = run(commands, n_blocks=2)
+print(f"answer 1 is {len(set(visited_1))}")
+
+visited_2 = run(commands, n_blocks=10)
+print(f"answer 2 is {len(set(visited_2))}")

2022/inputs/day10.txt

@@ -0,0 +1,144 @@
+addx 1
+addx 4
+addx 1
+noop
+addx 4
+addx 3
+addx -2
+addx 5
+addx -1
+noop
+addx 3
+noop
+addx 7
+addx -1
+addx 1
+noop
+addx 6
+addx -1
+addx 5
+noop
+noop
+noop
+addx -37
+addx 7
+noop
+noop
+noop
+addx 5
+noop
+noop
+noop
+addx 9
+addx -8
+addx 2
+addx 5
+addx 2
+addx 5
+noop
+noop
+addx -2
+noop
+addx 3
+addx 2
+noop
+addx 3
+addx 2
+noop
+addx 3
+addx -36
+noop
+addx 26
+addx -21
+noop
+noop
+noop
+addx 3
+addx 5
+addx 2
+addx -4
+noop
+addx 9
+addx 5
+noop
+noop
+noop
+addx -6
+addx 7
+addx 2
+noop
+addx 3
+addx 2
+addx 5
+addx -39
+addx 34
+addx 5
+addx -35
+noop
+addx 26
+addx -21
+addx 5
+addx 2
+addx 2
+noop
+addx 3
+addx 12
+addx -7
+noop
+noop
+noop
+noop
+noop
+addx 5
+addx 2
+addx 3
+noop
+noop
+noop
+noop
+addx -37
+addx 21
+addx -14
+addx 16
+addx -11
+noop
+addx -2
+addx 3
+addx 2
+addx 5
+addx 2
+addx -15
+addx 6
+addx 12
+addx -2
+addx 9
+addx -6
+addx 7
+addx 2
+noop
+noop
+noop
+addx -33
+addx 1
+noop
+addx 2
+addx 13
+addx 15
+addx -21
+addx 21
+addx -15
+noop
+noop
+addx 4
+addx 1
+noop
+addx 4
+addx 8
+addx 6
+addx -11
+addx 5
+addx 2
+addx -35
+addx -1
+noop
+noop

2022/inputs/day11.txt

@@ -0,0 +1,55 @@
+Monkey 0:
+  Starting items: 54, 53
+  Operation: new = old * 3
+  Test: divisible by 2
+    If true: throw to monkey 2
+    If false: throw to monkey 6
+
+Monkey 1:
+  Starting items: 95, 88, 75, 81, 91, 67, 65, 84
+  Operation: new = old * 11
+  Test: divisible by 7
+    If true: throw to monkey 3
+    If false: throw to monkey 4
+
+Monkey 2:
+  Starting items: 76, 81, 50, 93, 96, 81, 83
+  Operation: new = old + 6
+  Test: divisible by 3
+    If true: throw to monkey 5
+    If false: throw to monkey 1
+
+Monkey 3:
+  Starting items: 83, 85, 85, 63
+  Operation: new = old + 4
+  Test: divisible by 11
+    If true: throw to monkey 7
+    If false: throw to monkey 4
+
+Monkey 4:
+  Starting items: 85, 52, 64
+  Operation: new = old + 8
+  Test: divisible by 17
+    If true: throw to monkey 0
+    If false: throw to monkey 7
+
+Monkey 5:
+  Starting items: 57
+  Operation: new = old + 2
+  Test: divisible by 5
+    If true: throw to monkey 1
+    If false: throw to monkey 3
+
+Monkey 6:
+  Starting items: 60, 95, 76, 66, 91
+  Operation: new = old * old
+  Test: divisible by 13
+    If true: throw to monkey 2
+    If false: throw to monkey 5
+
+Monkey 7:
+  Starting items: 65, 84, 76, 72, 79, 65
+  Operation: new = old + 5
+  Test: divisible by 19
+    If true: throw to monkey 6
+    If false: throw to monkey 0

2022/inputs/day12.txt

@@ -0,0 +1,41 @@
+abcccccccaaaaaaaaccccccccccaaaaaaccccccaccaaaaaaaccccccaacccccccccaaaaaaaaaaccccccccccccccccccccccccccccccccaaaaa
+abcccccccaaaaaaaaacccccccccaaaaaacccccaaacaaaaaaaaaaaccaacccccccccccaaaaaaccccccccccccccccccccccccccccccccccaaaaa
+abcccccccaaaaaaaaaaccccccccaaaaaacaaacaaaaaaaaaaaaaaaaaaccccccccccccaaaaaaccccccccccccccaaacccccccccccccccccaaaaa
+abaaacccccccaaaaaaacccccccccaaacccaaaaaaaaaaaaaaaaaaaaaaaaacccccccccaaaaaaccccccccccccccaaacccccccccccccccccaaaaa
+abaaaaccccccaaaccccccccccccccccccccaaaaaaaaacaaaacacaaaaaacccccccccaaaaaaaacccccccccccccaaaaccaaacccccccccccaccaa
+abaaaaccccccaaccccaaccccccccccccccccaaaaaaacaaaaccccaaaaaccccccccccccccccacccccccccccccccaaaaaaaaacccccccccccccca
+abaaaaccccccccccccaaaacccccccccaacaaaaaaaacccaaacccaaacaacccccccccccccccccccccccccccciiiiaaaaaaaacccccccccccccccc
+abaaacccccccccccaaaaaacccccccccaaaaaaaaaaacccaaacccccccaacccccccccccaacccccccccccccciiiiiiijaaaaccccccccaaccccccc
+abaaaccccccccccccaaaacccccccccaaaaaaaacaaacccaaaccccccccccccccccccccaaacaaacccccccciiiiiiiijjjacccccccccaaacccccc
+abcccccaacaacccccaaaaaccccccccaaaaaacccccacaacccccccccccccccccccccccaaaaaaaccccccciiiinnnoijjjjjjjjkkkaaaaaaacccc
+abcccccaaaaacccccaacaaccccccccccaaaacccaaaaaaccccccccccccccccccccccccaaaaaaccccccciiinnnnooojjjjjjjkkkkaaaaaacccc
+abccccaaaaacccccccccccccccccccccaccccccaaaaaaaccccccccccccccccccccaaaaaaaaccccccchhinnnnnoooojjooopkkkkkaaaaccccc
+abccccaaaaaaccccccccccccccccccccccccccccaaaaaaacccccccccccccccccccaaaaaaaaacccccchhhnnntttuooooooopppkkkaaaaccccc
+abccccccaaaaccccccccccacccccccccccccccccaaaaaaacccaaccccccccccccccaaaaaaaaaaccccchhhnnttttuuoooooppppkkkaaaaccccc
+abccccccaccccccccccccaaaacaaaccccccccccaaaaaacaaccaacccaaccccccccccccaaacaaacccchhhnnnttttuuuuuuuuupppkkccaaccccc
+abccccccccccccccaaccccaaaaaaaccccccccccaaaaaacaaaaaacccaaaaaaccccccccaaacccccccchhhnnntttxxxuuuuuuupppkkccccccccc
+abcccccccccccccaaaacccaaaaaaacccaccccccccccaaccaaaaaaacaaaaaaccccccccaacccaaccchhhhnnnttxxxxuuyyyuupppkkccccccccc
+abcccccccccccccaaaaccaaaaaaaaacaaacccccccccccccaaaaaaaaaaaaaccccccccccccccaaachhhhmnnnttxxxxxxyyyuvppkkkccccccccc
+abcccccccccccccaaaacaaaaaaaaaaaaaaccccccccccccaaaaaacaaaaaaaccccccccccccccaaaghhhmmmttttxxxxxyyyyvvpplllccccccccc
+abccacccccccccccccccaaaaaaaaaaaaaaccccccccccccaaaaaacccaaaaaacccaacaacccaaaaagggmmmttttxxxxxyyyyvvppplllccccccccc
+SbaaaccccccccccccccccccaaacaaaaaaaacccccccccccccccaacccaaccaacccaaaaacccaaaagggmmmsttxxxEzzzzyyvvvppplllccccccccc
+abaaaccccccccccccccccccaaaaaaaaaaaaacaaccccccccccccccccaaccccccccaaaaaccccaagggmmmsssxxxxxyyyyyyvvvqqqlllcccccccc
+abaaacccccccccccccccccccaaaaaaaaaaaaaaaaacccccccccccccccccccccccaaaaaaccccaagggmmmsssxxxwywyyyyyyvvvqqlllcccccccc
+abaaaaacccccccccccccccccccaacaaaccaaaaaaacccccccccccccccccccccccaaaaccccccaagggmmmssswwwwwyyyyyyyvvvqqqllcccccccc
+abaaaaaccccccccccccccccccccccaaaccccaaaacccccccccccccccccaaccaacccaaccccccccgggmmmmssssswwyywwvvvvvvqqqlllccccccc
+abaaaaacccccccccccccaccacccccaaaccccaaaacccccccccccccccccaaaaaacccccccccccaaggggmllllsssswwywwwvvvvqqqqlllccccccc
+abaaccccccccccccccccaaaaccccccccccccaccaccccccccccccccccccaaaaacccccccccccaaagggglllllssswwwwwrrqqqqqqmmllccccccc
+abaaccccccccccccccccaaaaaccccccaaccaaccccccccccccccccccccaaaaaaccaacccccccaaaaggfffllllsswwwwrrrrqqqqqmmmcccccccc
+abacaaaccccccccccccaaaaaaccccccaaaaaaccccccaacccccccccccaaaaaaaacaaacaaccccaaaaffffflllsrrwwwrrrmmmmmmmmmcccccccc
+abaaaaaccccccccccccaaaaaaccccccaaaaaccccccaaaaccccccccccaaaaaaaacaaaaaaccccaaaaccfffflllrrrrrrkkmmmmmmmccccaccccc
+abaaaacccccccccccccccaaccccccccaaaaaacccccaaaacccccccccccccaaccaaaaaaaccccccccccccffflllrrrrrkkkmmmmmccccccaccccc
+abaaacccccccccccccccccccccccccaaaaaaaaccccaaaacccccccccccccaaccaaaaaaacccccccccccccfffllkrrrkkkkmddddcccccaaacccc
+abaaacccccccccccccccccccccccccaaaaaaaacccccccccccccccccccccccccccaaaaaaccccccccccccfffllkkkkkkkdddddddcaaaaaacccc
+abaaaacccccccccccccccccccccccccccaaccccccccccccccccccccccccccccccaacaaacccccccccccccfeekkkkkkkddddddcccaaaccccccc
+abcaaacccccccccccaaaccccccccaacccaaccccaaaaaccccaaaccccccccccccccaaccccccccccccccccceeeeekkkkdddddccccccaaccccccc
+abccccccccccccccaaaaaaccccccaaacaaccacaaaaaaaccaaaaccccccccccaccaaccccccccccccccccccceeeeeeeedddacccccccccccccccc
+abccccccccccccccaaaaaacccccccaaaaacaaaaaccaaaaaaaacccccccccccaaaaacccccccccccccccccccceeeeeeedaaacccccccccccccaaa
+abccccccaaacccccaaaaacccccccaaaaaacaaaaaaaaaaaaaaaccccccccccccaaaaaccccccccccccccccccccceeeeecaaacccccccccccccaaa
+abccccccaaaccccccaaaaacccccaaaaaaaaccaaaaacaaaaaaccccccccccccaaaaaacccccccccccccccccccccaaaccccaccccccccccccccaaa
+abccccaacaaaaacccaaaaacccccaaaaaaaacaaaaaaaaaaaaaaaccccaaaaccaaaacccccccccccccccccccccccaccccccccccccccccccaaaaaa
+abccccaaaaaaaaccccccccccccccccaaccccaacaaaaaaaaaaaaaaccaaaaccccaaacccccccccccccccccccccccccccccccccccccccccaaaaaa

2022/inputs/day13.txt

@@ -0,0 +1,449 @@
+[[],[],[[],10,[[7,0,1,1,10],9,6],[1,[4,9,1],6,[4,6,0]],[0,3,0]],[1,[10,[7,4,3,4],[]],[2,2],7,[[10],5,3]]]
+[[8,1,[2,3,3,[6,7,7,2,6]],[[8,10,1]],[9]],[1,7,[7,[3,6],7,7,10]]]
+
+[[[[3,0,4,4],9,2],8,[[1],3,[2,0,9,3],[5,3,6,4,5]]],[],[]]
+[[[],[]],[[[8,4],[5,5,9,9],[1,9,1,8],0]]]
+
+[[5,[4,[8,3,4],1,1,[3,8,9,4,0]],4]]
+[[7,1,[[9,0,5,5,9],[5,0,3],[0,5,5,10,0],3,7],1],[9,[[1,6,3,2,2],7,[8,9],[7,7,2,10]],[],[]],[[8,0,[0],5],[[3]],3,[[1,0,0,9],[10,7,0,10]]],[[],8,2,3,[[10],[10,6,10],0,9]]]
+
+[[4,8,6,8]]
+[[[3,[],[4,7,4,4],1],1,[6,[5],[1,1,6,8]],3,10],[2,[3,6,[],6],10]]
+
+[[1],[[0],5]]
+[[10,[[2],10,[6,4,0],[],9]],[4,9,[[9,6,10,7]]]]
+
+[[8,[[4,1,1,4],[6,10,6,6],7,6,[9,9,1]],[[0,9],3]],[1,[5],5,[]]]
+[[],[[]]]
+
+[[[[3,9],[],[5,9,8,3]],2,5,9,8]]
+[[[9,0],4,[9,10],[5,6,10,0,[6]]]]
+
+[[],[9],[4,[[10]],8,10,[10,10,[],[]]],[[],[[10,4,6]],[[1,1,6],[]],5],[[[1,7,5],[10,1,6],6,[]],[],2,3,9]]
+[[],[[4,[5,4,8,7],[10]]],[10,7,[3],8],[[6,[1,2,9,5]],[],[[2,4,3]],[3,[3,8,9,8],[9]]],[[[6,0,0,7,3],9,3],[9,[0,4]],[[8,8],[2,1,8],[]],3,[]]]
+
+[[[9,0,9],3,10,5,7],[8,10],[[[1,6],[3,5,2,7],[2,3,0,5,8],[1,3],10],[],8],[[4,[]]]]
+[[7,[3,10,3],[[],[3],2,[5,4,3,10]],5,2],[6],[3,[],[[3,0,4,0]]]]
+
+[[[10,3,[8]],10,1]]
+[[[],5,1,[10,[3,8,7],[5],[1,3,6,0],[4,8,10,6]],[[7,7,1],[0,2],8,[2,1,9,8],8]]]
+
+[[6,[9,[1]],10,[7],10],[[10,4,9],5]]
+[[6,10,[[7,10,1]]],[[[2,9,0,3],[4,5,10,0,6],[2,4,2],9]],[],[[[5,0,8],[2,2,1,1],[1,6],5],[]]]
+
+[[3,10,[7]],[4,[[0,3,8]],5,10],[],[[[8,9,4,8,10],[5,9,7,1,0],[6,5],8,7]],[]]
+[[2,6,[7,7,[3,8]],[[1,6,7,1,9],7,7,[5]],3],[8,[8,[4,7,1,2,4],[2,8],[6,9,9,8,4],9],[[3,10,2,0]]],[[5,[6,9],[]],0],[7],[[[]],3,[3],1]]
+
+[[6],[],[[[1,5,1,9,5]],7,10]]
+[[],[5,[]],[[[1,2,1,1,7],[5,4,5]],8,3,3,8],[1,[5,[10,0,7],[7,4,9]]]]
+
+[[1,2,8,[[4,10,2],[7,4,1,2,5],9],[7,0,[5,10,2,5,1],[5,4,9,2],0]],[1,10,[[5,10,4],[6],[8]],[[8],[2,9,10,1,3]],5],[[4],0],[]]
+[[9,[[2,9,6,7],6,[6]],7]]
+
+[[[]],[[],5,[2,3]],[],[8,[],3],[9]]
+[[9,[6,6,9,[6,3,6,8],[]],[[],8,[0,8],[9],0],1,[]]]
+
+[[0,[],10,[4,[8,7,10]],8],[[[],[10,6]]],[10,[1,[1,8,1,2],5,2],[[0,8,0],[1,9,1,1],[3,8,3],0],7,[0,5]]]
+[[8,4,[6,9,2,[4,5,6],4],[[10,9,0,0,1],[6,7,8,8]]],[[[2,5,6,1],2,8,[6,8,3,9]],[[4,10,0]],0,9]]
+
+[4,6,8,10,9]
+[4,6,8,10]
+
+[[[10,2,[0,1,2,0],0],7,[2],[[],[0],9]]]
+[[],[[]],[9]]
+
+[[1]]
+[[],[[10],10]]
+
+[[],[],[],[[[1]],9,10,[1,0,5]],[]]
+[[6,[[4,4,9],[10,3,10,1,4],[10,5]],4,[[1,7,5,0,1],[3,7,10,1,1]]]]
+
+[[[[9],[8]],[6,3,4],5],[[6,3],[7],[[5,10]],10],[],[3,5,[3,0,[0,3,3]],8,[]]]
+[[3,[10,10],4],[8,[[7,1,0,6]],1],[8,[[5,0,7,4],[1,4],1],5,[[7,1],[2],[0,9,5,7,5]]],[[5,[6,3],[0,8,3,2],10,[10]]]]
+
+[[],[[[1],0],[9,7,7,[3,9,3,9,10]],8,[5,10,[5,5,8,3,7],7,[9,0,7]]],[[8,2,[0],7],4]]
+[[[8,0,4],5,3,2,5],[4,7,6]]
+
+[[3,1,[[6],[2],[4,8,7,10],2],1],[[[6,2,8,6,4]],6,[9]],[8,[0],1],[]]
+[[],[[[0],3,[2,10],10,[2,0,6,3]],9],[1,[[],10,[],8],[[6],2,7,8],[10,[4,3,4],[10,3,5,3,5]]],[[2,[],8],2,0,8]]
+
+[[],[[[1,7],[0,2],[3,2,8],[7]],0],[1,[1,[7]]],[6],[[[7],[],[8,8,10],[0,5,1]],2,5,[[4,6,6,8],8,[0,9,4,5,4],4],[1,5,6,[2,4,6],[4]]]]
+[[4,[5,[5],6]]]
+
+[[[[6,10,4],7,[],[5],[5]],1,9,7]]
+[[[]],[[[5,0,6,3,5],[]],8,[8,10,5,2],4,10],[7,[[8,0,9],9,[6,9],1,1],4,10],[6,4,6,9,5],[]]
+
+[[[],1,9],[6,3,[[8,10,4,1]]],[[[0,4],9,7,[0,0,5]]],[[]]]
+[[[9,3],[[]]]]
+
+[[9,0,8,0],[[1,[0],8,[]]],[],[5,8,[[8,9,0,8,0],0,8,[],[]],[1,2,5],[[],5]],[[3,1,6,[],[4,9,3,6]],[5,[10,10,4],3]]]
+[[6,[[],2,9],[1,9,[6,2,5,1],[1,5,0,8]]],[[2,[4,4,2,6,1],6],[],[],8,[[]]],[[[7,8,10,2,10],[1,4,9,5,2],7,[6,6,4,10,9],[7,3,3,0,0]]],[],[7,3,[2,[1,2],[2,2]]]]
+
+[[1,[[2,6,1,6],[4,6],[3],[],[1]],8],[[8],6,5,[5,[4]],6],[[[],5,10,[10,7],[3,7,5,9,10]],0]]
+[[[9,[7],1,[],5]]]
+
+[[[9,2,1,0,6],[[0,4,8],5],[[],[],0,[8]]],[[[],2],[[7,7,7,8,10],10,[0],[0,2]],[],[]],[],[]]
+[[],[5],[[[],5,[8,8,1,5],9],[7],[1,3,5,[0,0,0]]],[]]
+
+[[[],[5,4,[],10,[1,8,1]]],[7],[[[1,4,10,10,4],[],9,[7,10,10,0,2],[10,4]],[4,[3,5,1],6,1]],[[[1,1,9,3,5],10,[2,1,3,9,3],[6,10]],[[],[]],2]]
+[[[[1,3,7,8,5]],[1,[1,8,3],[4,1,3]],0,2,4],[],[],[[5,[7,9,2,5,2]],[[10,10,10,8,3],2,[]]]]
+
+[[[[1,0,3],[10,8],[],[9,1,9],[0,5,2,4]],[],3,[[6,8,7],[6,0,7,1,0],3,10],2],[1,7,[4,[5,7],[4,6]],9],[[],[[1,2,0,5],1,3,[9],0],5],[]]
+[[[[7,7,1,2]]]]
+
+[[5,9],[[9,[1,9,2,2]],[[],8,[1,1]],[[],[6,4,0,3,3],[8,0]],[8],7],[[1],5,6,10],[]]
+[[[]],[[[0,2,8,5,4],[4,5],5],7],[[[0,10,3,4],8,[0,7,10,2],[6,1,9,9,10]],9,2,6],[1,[2,7,[6,6,2,2],[10,0,9,4,3],2],6,[[2,1,4,1],10,[7,5]]]]
+
+[[[[5,2,7,9],[10,0,8,1,1],[]],[6,6,3,[8,7,1,9,1],4],[[6,1,4,8,1]],[0,[5,10,2],5],1],[[],[5,10,1,4]],[0,[10,10],[1,[7,0,5],[4],[10,5,3,4,2],[8,10,1]],[],[5,[0,6,3,7,4],2,9,4]],[[6],[],0]]
+[[[2,[10,9,9,9],7],[9,[1],10],1,[[5,10,5,4],2,1,1,[]],[10,[2,10],[0,7,2,5],0,1]]]
+
+[[[4,9,[5,6,9,6],[7],[0,9,5,8,1]],[[8,0,2,5]]],[],[6,[[7,10],9]],[[5,2,[]],2],[[9,0],5,[[2]]]]
+[[[]],[],[[[2,9],0],2,[[6,2],6,[3,8,1,1],1]],[]]
+
+[[3,6,4,[2,5,0,[8,6,8],4],[[1],[5]]],[0,[2]],[],[5,[],[5,4,[10,9,4],9,6]]]
+[[[[5,10,3],6,[2],[]],[[8,1,7,7,10],0,[6,8,9,3,9],[10,5,4],[9]],[[]],[[6,1,4,3,9],[10,9,9]],8],[9,7,6,[[3,8,0,1,1],1],8]]
+
+[[[[0,3,8,10,5],2,[],[],[9]],3,6,[5,[0]],[5,[]]],[]]
+[[0,3]]
+
+[[[3]],[9],[],[[4,1,9,[5],[]]]]
+[[[9,[5,6,3],4,[4]],[[],[5,6,4],[7,5,10,8]]],[[0,[8,3],4,6,[9,9,4,1,0]],[[3,5,1,7]],8,[]],[[],0,[8,2,9]],[4,[[],5,[10,10,10,6,6],[8,7,3]],[5,[1]]]]
+
+[[[[1,0,3,6],6,[10,10,6,8]],[]],[[1,2,[9,7,1,10],[]],[[10,3,0,8,8]],2,8,[7,4]],[[[10,8,4]],[2,3],6],[[[10,6],[5],9,1],[],7]]
+[[],[[],[[3,8,4],0,[]],[],6,[[3,7,1,0],10,8]],[[9,4,[]]]]
+
+[[[8,[4]],6,3,10],[[5,1,8,[0,6],2]],[],[[],[[10],[6,6],0,[1,7]],8],[[[1],0,5,[],10],7,2,[10,[8,3],9,3,[]],4]]
+[[[6],3,[]],[[[1,3,1],[1],[9,7]],[6,[1,9,9,7,9],2]]]
+
+[[],[[8,4],0,[10,[]],5],[5]]
+[[[4,[],[],7]],[[6,[3,5],[0,5,8],8,7],[7,0,[8]]]]
+
+[[[2,[6],[9,7,1,2,5]],8,[3,[4,0,4,7,3],[],3],[[1,3,1,8],[5],4],4],[10,4,7,3],[[]]]
+[[9,0,7,[],[8,5,10,[2,0,1,7,4],6]],[[8,[],10,6],1,[[5,0,7,0],[]]],[[9,[8,4,0],[0,8,8]]]]
+
+[[[7]],[[3,1,3,[6,3],8],[],[[10,3,1,5],[9,5,6,4],1,[],5],2]]
+[[5]]
+
+[[[1,2,0],[[2,7,3,5],0,[9,7,0],10]],[6],[3,7]]
+[[[[6,0,7],7,0],0,6,2,2],[5,6,5,7],[8,[]],[],[[[1],[0,5,10,6,9],[10],8,10],[[8,10,8,7],[],4]]]
+
+[[4,[6,2,[9]],3],[0,8,10,[[2,9,1,1,8],7,5,5],[9,[],6]],[],[4]]
+[[9,[[10,3,10,8]],4],[0],[],[7,[[5,0,9],9],[[7,5,3,9,0]]],[]]
+
+[[[7],1,[9,0,4,[4,10,9],[4]],10],[6,4,[[]]],[[[3]],[[4,1,0,9,4],4],9,[[9,0,2,10]]],[[2,9,[0,3,10,7],8,8],[[10]],5,[[3,7,4]]]]
+[[[10,[7,0],0,6,[3,3]],[[3,5,10,3]]],[[[1,6],[2,7,3,3,8],[8,0,7,3],8,[10,9,7,8]],2,[7,[1,9,0,9,1],2],[5,10,0,8,2]],[[[9,6,9,0,3]],9,3],[[[6,8,9,8],[0,2],[4,1,0,6,5],7]],[3,[[1],[7],1],[[3,7],10,[8,4,7,6],10],[9,[3,5,3,9],[6,3],3,[3,1]],[[5,3,10],[10,10,5,7],7,[0,1,5,1,3],8]]]
+
+[[10,[8,[7,7,3],7,[5,3,8]],[1,2,10,[]],6]]
+[[3,[3,[7,6,3,6,10],9,[6,9,1],[1,3,1]]],[3,[8,10,[1],[8]]],[[[1,4,4,8]],[]],[[2],[[4,8],[9]],[[5,3,5,4]],9,[2,10]]]
+
+[[4,1]]
+[[[10,[5,5,9,2,6],[],[3,2,0,4],10],[6,[8,7,7,4]],8,[]],[3,[0,[10,10,10,1]],[0,8,4],[[4,4,10,7,1],2,[],[2]],[5,2]],[[[10,6],7,[8,6,3],10,[5,8,0,6]]],[],[[]]]
+
+[[[],7],[3,[5,[5,8,8,7,4],[2,6,2,10]],2,7,8],[5,[[],[1,8,1,2,5]],0,0],[]]
+[[4,[3,7,0,9],8,0],[[[3,2,3],8,[10],[7]],9],[1,[[],[2,3,1],2]],[0]]
+
+[[[[8,2,1],8,10,10]],[[5,4,[4,9,2,6]],3],[],[10,[[3,8,7,4],8,7,[3,10,1,2,7]],[4,5],1]]
+[[4,[],4,[2]]]
+
+[[[10,4]],[0,1,[]],[],[9,10,10,2]]
+[[],[[[7,9],10,8]],[8,4,2,[[6,7]],5]]
+
+[[],[[[0],2,7,[8,5,6],[6]]],[[3,[0,9],1,[9]],2,[[6,5,2,7,9],[],[3,8,3,0,2]]],[[3,[],[10,2,9,2],[9,3,1]],[1,7,[6,2],[9],6]],[[[10,4,0,9],[8,8,0],10,2],[8],6,[4],3]]
+[[[[5,0],6]],[10,[]]]
+
+[[[7,[4,6]],4,[5,7,[8,5,3,5],[2,9,5,5,5],7]]]
+[[[[8,2],0,[0,8,10]],[],[8]],[[[1,10],10,1],[10,[5,1,4],6,6,0],6,[9]]]
+
+[[[[4,9,7,1],[8,0,10]],[[8],0],9],[4,[7,[5,10,9],8],[[],[3,4],[9,4,9],[2,9,9]]],[],[],[[3,0,[7,8,5],9,2],[[],[],[0,5,2,1,1]]]]
+[[0,[],9],[],[]]
+
+[[5,[5,[5],[]],8,0],[3,[[]]],[6,[[7],[6],8,7,2],[[]],[],4]]
+[[6,2,3],[0,[[6,1,9],[2,10,5],0],[1,0,8,[10,0,9],[]],[[0,1,5,2,2],[],1,1,6],[[4],[]]]]
+
+[[[0,[5,9,0,1],5,[3,6,4,7],[3,0]],[],[7,[],4],1,[7,4,8]]]
+[[[[2,0],0,[],6,1],[],[]],[1,5,[[],[3,0,3]],[6,3],[]],[[[9,9,0,3],5,[]],0,[[5,3],[6,9],[3,0,4,5,3]],[[7,6,2,6],[]]]]
+
+[[5,[[3,5,10,7],3,[]],4,[]],[8,4,9,0],[[2,[10,2,8],[8,6,10],[9,8,0,3],[0,5,5]]],[[[6]],[6],3,4,[]]]
+[[[],[],0,2],[0,[[9,1,4,8,5],2,7]]]
+
+[[9,6,[4,[7],[9],10,5],[8,[4,5,1,0,3],[9,6,7]]],[8]]
+[[2,[5,[6,1,3,6,8]],7],[[5,3,7,7,0],10,[8,6,6],[[1,2,3,8,5],[6,5],[9],[]],6],[[5,5,[],[0,4,5,5]]],[[5,2,2],5,[8,8,[8,9,5,1]],[],[6,7,3,8]],[8,3]]
+
+[[9,2,[[],8,7]],[[[]],4],[[],[8,[6,1],[3],8],[[8,0,0]],3],[7,4,[[3,5,8,9,0],3],[],5]]
+[[9,0,[],[2,[6,2,1,7],1],[10,2,[6,2,7],[9,2,0],[8]]],[3,9,6,[6,0]]]
+
+[[0,[4,[],[]],[]],[[8],[],5,0,[]],[10,[7,9],[3,5,5],[3,[3,3],[6,7,3],[4,0,2],[6]]],[5,[],10,8]]
+[[1],[],[[]],[7,[[],[0,1,3],[2],[],[4,0,7,7,9]]]]
+
+[[[8,[2,4,7]],0,[0],[0,[],1,0,7],7],[0,8,4,4,[6]],[[],6,[[10,2,8,8],8,[7,2,4,9],1,5],[0,4,10,9]]]
+[[[1,[7,6,1],8,[6],[5,9,8]],1,[[3,7,3,7,2]]],[],[8,[4,10,2],[8,[]],4,5],[[3,[5,10,1,6,10],2],10,0,[[10,2,2,5,5],9,[4,3,7,4],6]],[0,8]]
+
+[[[0,[],[2,5,7,8,10],[4,0,7,7]],1,2,4,7],[[7,[6,0,0]],[2,[],9,[7,0,5,7,10]],[[0,7],[],[3,10]],[1,10,8,0,[1,8,5]]]]
+[[],[8,[[1,10,3]],0,[],[[],8,5,4,7]],[[0],5,5],[[4],[5,8,[6,2,8],4,[1,4,2]],2,[[7,7,3]],[6]]]
+
+[[8,[[6],1]],[0,8],[[7,2,[6,1],3],9,[6,[2,5],[5],[6],[6,1,0,1,10]],3,[[1,9,3,7],2,[]]]]
+[[6,[]]]
+
+[[6,6,[5]]]
+[[9,[[],[4,8,1,2,10],[2,9,6,1],2],[[5,4]],3,[4,[1,1,10,5,10],4,[0,0],[7]]],[],[2,[1,[3,1,7,1],10,3]],[[[9,7,3,4]]]]
+
+[[[]],[[8,[3,5,5,7,1],0],[10],0],[5,2,[[]],[2]],[]]
+[[6,0,5,[[1],[6,8],3]]]
+
+[[10,[3,[],10]],[0],[[4,[],2,7]],[[9]],[[[0,7,5],[]],[[9,4,4],[1,5,8],[4,10,7,6]],[[8,5,4],8,[9,3,1,4,2]]]]
+[[1,[1,[5,2,7],0,[6,4,8,2,4],10],[],9,[1,3]],[[7,9,7,[7,5]]],[[[0,10,6,1]],[7,[8],6]]]
+
+[[[0]],[[9,10],[9],[2,4,9,3],[[],[],1,7],10]]
+[[[[0,7,4,7,7],[3,6],[5],[1]],[],[8,9,[2,5],[10,3,10],[10,4]]],[[[9,7,1,6,2],3,0,[7],1]],[[7,[4,3,6,6,9]]],[[],[],[[],[8,8,2],3]],[[9,[8,2,5,4],[8,9]],[]]]
+
+[[[],[4,[7,5,10],9,6,10],4,3],[]]
+[[6,4]]
+
+[[[[],0,[8,8],3,[]],4,[4,[9],1],[[5,7,6,1],4,5,7,[]]],[1,5,1,[10],[]]]
+[[[[3,8,9,2,7],[3,0],2],[2,[8,0,4],2,5],[[8,0,6,0,2],[0,4],4,[5,10]]],[2,[]],[[1,[5,9,9,1],[10,7,2,10],3]]]
+
+[[],[],[8,[[6,1]],9,[1,3,2],8],[5,2,[[7,7,8],[9,5,0],[10,4,7],2,[0]],7,5]]
+[[0,1,10],[4,3,[0,[5,4],4,5,2],[7,7,8],[[6,8,1,1,4],[6,3]]],[[[9,7,7,5,0]],6,[[5,0],[4,7,0],[5],9,8],[],[1,[8,8,9],[8]]],[[[7,8],6]],[]]
+
+[[[[9,9,7],7,1,4,[9]],[],[4,8,6,[7,4,4,4],0]],[[2,[3,6,2],[0,8,0],[9,3],2]],[[[8,10,1],[9,7,8],[0,8,4,7,7],[0,7,7],5]]]
+[[6,[[]],0,[[],[2,3],1],7],[],[0],[2,[5,0,[2,5,8,6,2],3],[10,[0,10,5],[9,7,3,7,10],[]],[9]]]
+
+[[1],[[[],[5,4,4,8,8],6,3],6,[8,0],1]]
+[[[1,9],1],[]]
+
+[[[[0,6,6],[],0,3,[4,4]],[[10]]],[[[0]],8,0,0,9],[0,10,[7,[3,1,10],5,6,[1]],2,1],[[5,6],[[10,2,9,5]],6,[]]]
+[[],[],[[]],[[[6],[2,0,7],0,10,5],1]]
+
+[[[[8,0,3,6,10],[4,8],5,9,[7]],[[8],[3,10,2,10],[4,5,4,7],5,[]],0,7],[2],[3],[[5,6,3,4],[[2,0,3],[6,0,9,0],3,[2,5,4,1,6]],[4,[3,4,10,1],1,0],[7,[5,2]],3],[8,6]]
+[[3,9],[5,[9,1,[7,1,1,8,7]],[6,[2],[4,8,4,2,10],[6,4,5,0],[]]],[[[1,2,3],[8,6,9]],7]]
+
+[[[0,7,2,4,0]],[6,2,7,10,6]]
+[[0,1],[2],[6]]
+
+[[[[5]],4,2]]
+[[[],7],[[[4,1],4,[2,0,3]],5],[[8],[1],2,[9,8,9,0,[2,3,9]],[9,[10,8,2,4,0],9,[6,0,2],6]],[[[5,5],[],1,5,[10,0,7,4,10]]],[8,7,3]]
+
+[[[[1,1,1,9,2],[1,9,7,4,4],[],[0]],[2,[5,9,4,4],[7,5]],4,7],[1,7,5,[[],2,5]]]
+[[2,[[7,6,4],[3,5,3,10,4],5,[8]],8,4,3],[1,5],[],[2,[[0],[4,5]],[8,[9,8]],[8,[]],0]]
+
+[[5,[[3,8,7],[10,9,4,3],[1,9,9,4],4],6],[[3,1,0],[[2],6]],[[1],0,[[4,3,1,2,0]],7],[]]
+[[9],[],[0,10,0],[1,5,[[8,6],[9,8,0,9],6,[0,10,1,9]],[[3],[2]],0]]
+
+[[9]]
+[[6,[[],2,3,10],7,8],[],[[3,9,0],5,[[4,0]],2],[[],2,3,[[2,6,0,5],10,6,[1,0,0,0],2],1]]
+
+[[],[3,4,[[],[],[],[]]],[3,[8],[],8,[8,[0,10,0],2,3]],[[2,[8,7,3,5],[0,10,6]],5,[[7,10,6],[3,7,9,7],5,[8,4,2],9],5],[[0,[8,0],5,[4,6,4,6]]]]
+[[5],[4,1,[[],7,[6,0,6,9]]],[[[6,3,3,9,8]],[],0,[[3,3],[8,7,8]]]]
+
+[[[[10,4],[0,7,7,9],[10,6,0],[2,7,1,5,3],4],[4,[4],[1,8,0,2],[5,8,4],7],[9,10,6],3,5],[[[1,10,3,10,9]],4,[3],[7,0,3]],[7,[],[[2,5,1,3]],[7,[2,2,4]],[[4,6,4,10],2,[6,7,8,6],[3,7,3,2,0],1]],[3,2,[[2,3,10,2,0],9,1,[]]]]
+[[9],[2,3,[[],9]],[[2,10],[]],[9,[2,[4]],7,[6,7,[10],[10,8,2],0]]]
+
+[[1],[[6],4,0,[7,4,6],5]]
+[[[[6,6,9],[1,2,2],[5],6,[8,8,8]],3],[[[],2,0],[],[],3,[[5,0,0],[2,0,1,5],0,[9]]],[[[],9,7],3,9]]
+
+[[5,9,[],9,4],[[[9,8],0,2],8,5,[7,7,10,2]]]
+[[[5]],[7,4,6,7],[],[[2,[3,5],[7,8],0],[]],[]]
+
+[[[[5,9,9,8]],[8,[8,1],8],6],[[8,[4],8,8,[8,5,6]],[8,[],2]],[0,4,6],[],[7,[2],[4,5,[10,8],[1,6,3]],4,[10,[7],3,7,3]]]
+[[0,[2],[],[5,[2,7,4,4,0],7,4]]]
+
+[[10],[[[1,3,6,10],2,1],0,[],[3,[8,5],[3],8]],[0,[2,[],4,[1,10],[6,1,6,6,8]],[3,[0,8,7,3],10,9,5],6],[7]]
+[[9,[]]]
+
+[[],[[9,[],1],[9,[0,2,0,7,8],8,10,[0,6,3,5,0]],[10]],[7,1,[[6,2,3,0],0,5,4],10,[[1],6,[9,4,7,3],[6]]],[0,10,[6,[8]],5,[2,2]],[9,1,2]]
+[[2,6,5,[2,7,[7,6,8,4,0]],[[3,0],3,[6,7],[10],4]]]
+
+[[[],7,10,[[],7],3],[8],[[[],[7,8,0,0],[2,9,5,3,2],0],6,3]]
+[[[[1,1,9,2,1],[],7,[5,8]],[4,[8,4,1],9],[[4,4,6],[5,8,2],[5],[5,7,0]],7,[0,3,[10],[],[4,2,0]]],[],[],[1]]
+
+[[],[0],[[[8,0,7],5],0,[10,6,9,10,5],10,[]]]
+[[[0,[6,1,6,10],[10,3,7,3],[1,4,9,3,8],[5,9]],0,[10],8,10],[],[7,3,[5],1]]
+
+[[2,6],[8,0,[[10,8,7],[],[],[7]]],[[8,4],[],9,[7],2],[0,6],[[5,9],[2],[6,10,[3,2,2,6,0]],7,[[2,6,0,8,5],[],[9,4,10],2]]]
+[[[2,[],0],[[1,10,7,0,5],[7,9,7,2,5]]],[[[0,5,7,2,5],4,[],2,4],9,2,[]]]
+
+[[[[],8,6],[[5,7,0,8],1,10,9,[4,4,7,7]],6,[[10]],[]],[[10,3,[5,7,9,2,7]],[[10,0],5],[7,10,9],4],[],[[0,0],6],[]]
+[[],[[[0],1,5],5],[[[6,2,4],0,[],6,5],[[7,1,8,1],[9,9,10,5,5],10,1,1],[3,10,10,10],2],[],[1]]
+
+[[[],[[5,4,1,5],0,[],6],[6]],[4,0],[]]
+[[[[],2,5,2,3]],[[[6,5]],[]],[[5,0]],[[],6,[[4],10,[0,7,9]]],[]]
+
+[[[3,7,[8,4,7,6,3],[5,1,7,6],[2]],8,3,[[0],1,[10,2,6,3,8],[9]],[5,6,1,[],[9,6,7]]],[[10,7,6,[7],[1,3,4,2,4]],[7,[5,2,5,9,0],[0,1],[5,10,6]]],[[[6,2,0],6,3,9,[3,3]],[7,8]],[0,1,[[5,9,6]],[[9,8,10,0],[6,3,7,8],8,5]]]
+[[],[[9,2,[0],[7,4,9,2],7],[[],[1,4,5,4],[2,10,8],0,5],1,3,[[7],9,9,[5,7]]],[[],4,[6,3,[3,0,1,6],5],[[],3]],[],[6,[1,[3,10,9,10,10],8,5,[4,3]],[10,4],[9]]]
+
+[[[[7,2,3]]],[6]]
+[[[2,[3],[]],4,4,8]]
+
+[[0,[10,6,[6],4,4]],[6],[[6,[8,4,6,7],7,7,0],9,[],10],[[[5,5,10]],9,[[10,6,5,6]]]]
+[[6,2,1,10]]
+
+[3,6,5,10]
+[3,6,5,10,10]
+
+[[4],[1,[10,[2,9,9,1,6],[],7,[9,3,8,9,0]],[10,[9,7,2,2,3],[0,2,3],5]],[[10,[10],[9,2]],6,7,[4,[1],[]],[[],10,[9,7,5,4],[1,4,3,3,4]]],[]]
+[[10,[9,[],0],4,[[],10],[0,0,6]],[],[5,[],8,[7,7,[4,7,0,9,6],5,1]],[],[[7,9],[[],5,5,[]]]]
+
+[[[],0,5,[3,[5,1,1]],5],[[4,[6,5,2],[0,9,7,0],1,1],[],[1,10],4,10],[9,[1,9,9],[10],[[5],[5,9,0],[2,9,5],[7,2,3],1]]]
+[[4,10],[5],[[[2,0,7],5,[0],[],[4,10,3]],1,[[9,4,4],6,[8],[7],0],[],[1,1,[8,4,5,7],[3]]],[7,7,[[],[1,1]],2,7],[9,[[2,6,9],[6,5,6,2,4],[4,8,10],[3,0,2,9,10],8],6,3,[[7,2,7],[3],[4,3,10,1,3],[5,2,10,4,5]]]]
+
+[[[7,[4,7],[8,8,2],[6,3,9]],[[1],0,[10,3,10,7],[9,2,9,4],1]]]
+[[],[[1]]]
+
+[[[[4,1,10,4],2],[],[6,[]],5],[[[5,3,4,8],10,[]],[10,4,[0,7,9]],[],7],[[],4],[3,4,[],7]]
+[[[0,[2,5,1,5],6,[]]]]
+
+[[[3]],[],[7,[[],[1,7,7,8]],[],[1,8]]]
+[[[0,[5,5,9,5],1,5]],[],[[[7,4,1,2,3],3,[],3],2,[[6,0,4],[0]],[[4,4,2,6,6]],[[9,0]]]]
+
+[[4,4,8],[0]]
+[[6,5]]
+
+[[5,9,[[5,5,3,3],[],[8,5,0,4,1],1,2]],[5,1,[3,4]],[8],[[[9],8,8,[8,0,2,3,8]],[8,[9],4,[7,1,0]],8,[]]]
+[[],[0],[],[4,4,[4,6,[10,1,1,0]],5,[3,6,[2,1,2,1],[5,8,7,10]]]]
+
+[[7],[[10,[4,3,6],[6,9,10]],8,2,10]]
+[[3,2],[[7,[10,2,5,1],[2,7,0,0],[],[0,10,1,3]],9,7]]
+
+[[[[7,7],[0,9,4,2],[7,0,2,9,6],2],2]]
+[[[[5,5,9]],[[7,4,4],[9,6]],6],[6,[8,1,6],3,7,4],[5,[6]],[],[[0,5],[8,1,3,4,9],[[],[3,4,9,10],6],[10]]]
+
+[[6,[1,[6],6]]]
+[[6,[0,5],[[5,6,4,7],7]]]
+
+[[],[[5,8],3,0],[[9],9,[5],[[],[3,2,4,4],1,[3,6,8,7,1]]],[[[],0,1],[3,5,[4,10,4]],[],[[2,2,5],[5,10],[6,6,10,0,7],[10,10,5,3,10]],[[1],9,5,[3,3,8,1,5],[5,4,5]]]]
+[[[[10,4,3,7,7],[3,6,6],[],[3]]],[5],[8,10,[7,3,5],7]]
+
+[[9,7],[7],[]]
+[[5,[[8,8,8,3,9],5],5]]
+
+[[1],[[3,[5,7],[3,4],[6,4]]],[[],[[6,7,5,8]]]]
+[[[[6,8],[],[]],0,[4,[]],1],[]]
+
+[[],[[5,[2,9,0],3],1,[[]],[4,10,[]]],[[0,3,[4,1],[5,9,0],2],1,[]],[0],[[[4],5,6,4,3],3]]
+[[7,[4,[9,6,1,3]],[[9]]],[[6,[2,1,10,2],[9],8],[8,6],[[5,2,8,10,9],[8,8,3,0,5],[5,10,8,3]],[],8]]
+
+[[],[3,[],5]]
+[[2,[],[[3,10,6,10],4]],[],[0,[10,8,[4,8]],[8,3,[9,8,3],[3,6],[10,9,9,6]]],[[[4],2,2,4],9],[[],[[],5,[],6]]]
+
+[]
+[[],[[4],4],[[8],6],[0,1,3]]
+
+[[[3,10,3,[9,3,9,9,4],8],[3,[]],[[7,8,6,0]],[[],[10,1]]]]
+[[0,3,10,2],[[[1],10],[3,0,4],9,[[4,8,6,7],[0,8,5],[],[9,5,3,1,4]]],[0,5,8,2],[2,[]],[]]
+
+[[[1,[]]]]
+[[[],5,2],[],[[[8],[3,4,1,7],[0,7,10],7,[]],1,1]]
+
+[[[[4],[0,9,7,6,0]],[[1,7,7,1,10],[],5]],[[0,[7,9,0,9,9],[3,10,6]],10,[[1,6],[10],[10],[6,2,2,2,4]]],[[]]]
+[[[4,[],0,[2,7,8,2,3]],8,[9,0,[1,9,1,2]]],[],[8,[3,2,0,[1,1,7,0]],[8,9,3,[10,5,1,5,4],[9,3]],[6,8,4,[3,3,4],[5,2,3]],1],[[3],5,[],[6,[2,4,9],[2,3],2,[]]]]
+
+[[0,7,[10,3],10]]
+[[],[]]
+
+[[[6,[6,6,5,6],[3],[9]]],[4],[3,[]],[[6,8,[3,0,6,7]],[5,[7,4,5,6],3,[0,7,2,8,3]]],[[10,7,10,2,3],[2,1,[7,2,10,1,3]]]]
+[[9],[[],3,0],[8,[10,[9],10]]]
+
+[[10,[[5,9],10,[10],[10,7],4]],[0],[0,[9,[5],[5,6]]],[3]]
+[[4],[[[7,4]],0,6,2],[9,[4,2,5,[4,10,3,10]],[4,10,[4,0,5,1,4],1,1],10],[]]
+
+[[[4,[9],8],[7,5],[],[[8],[],[6,9,10,4]],2],[],[],[],[[[3,10,0,3,0],[8],5,8],10]]
+[[[[1,2,1],10,[2,9]]],[4,[[6,0,4,3],[10,2],[],2,1],[[3,3,10,0,9],[3,7,2,5],[5,9]],10]]
+
+[[[[8],[3,2,9,8,6]],[10,[3],5]]]
+[[],[[[8,3,10]]],[[4,[1,5,3,6,2],[3,6,5,8,7],7],0,[6,[10,4,9,8,9]],[]]]
+
+[[9,[6],0,[9,[8,4,5,7]],[9]],[7,[[9,9,10],[9,4,0]]],[[4,[6,1,5,6]],[[6,7,0],[]],0,[[3,1,10,9,10],[0,6,6,10],6,[6,1,3,9,9],[9,0,10]]]]
+[[0,[10],8],[]]
+
+[[0],[7,[[7,7,9],6],2,[],3]]
+[[[7,6,5,[9],[8,1,0,3]]],[4,[],[6,4,[7,6]],6],[],[[],0,9,8,[[8,5],6,1,[1,2]]],[[],4]]
+
+[[4,[8,[5,1,7,6,2],6,[7]]],[[8,8,4],[9,5,8]]]
+[[5,[[10],2,[8,7,7,0],[9,0,7,5],3],6],[],[4,3,[]]]
+
+[[2,3,7,1],[9,4,[],[[8,2,9,0,3],[]],[[6]]],[]]
+[[2,[[5,2,10,8],4]]]
+
+[[[[3,7,0,8,3],4,10,[4],4]],[[[2,4],6,6,3],[[5,2,8],[6,3,6,6],9,10],4,[1,9,[],[1,2,4,8],2],9],[6,[[6],[2,9,8,7],1,[10,10,5,0]],[10,7,[8,0,2,6],10,3],1,3]]
+[[8,[7,[4,10,6,5],1,[]]],[[[0,0,2,9]],[10,2,0,[10,9,7,9,1],4],[5]],[[3,[10,5,1],1]]]
+
+[[]]
+[[],[5],[0,9],[8,[[5],10,2],7,[[9,6,5],[9,6,4,1]]],[[[],[8,10,0,2],[0,9,3,7,2],3,[2,7,1,6]],2,[],[],3]]
+
+[[[3,4,[7,2,4]],7,[1,6,[7]],6],[1,[[1],8,8],[1,1]],[[[5,3],[]],[1],[[4,2,1],3,0],6,0],[[[],[2,0,8,0]],5,[]]]
+[[],[[4,9],[8,3,[]]],[7,1,8,0]]
+
+[[[[],9]],[],[7,2,10,1,[[6],6,[],3,[]]],[]]
+[[[[1,10]],6,[],5],[4],[1,[[1],2,[5,4,4,4,4],2],[4,4,[2,2,8],8]],[1,[],6,2,1],[[[2],[10,8,6],[6,3]],3,1,[9,3,10,9,3]]]
+
+[[5,6,8,3],[9]]
+[[[],4],[[[],2,10],[5,[9,9,3],0,[]],4,3,[0,9]]]
+
+[[10,3,0,[[7],8,3,7,5]],[[[6,9],[3,5],2],2,[[7,7,10],[5]],0],[[8,6,4,10,[7,10,5]]],[[4,[],[10,2,7,10,3],[10,3,7]],3,7,7],[[[2,0,2,0],[5,8,10,6,4],[3,10,10,0],[4,2,6,1]],10,3,[6]]]
+[[[[1],[],5,[]]],[4,8,3]]
+
+[[10,[8,5]],[1,[0,4,[0]],1,3,[[0]]],[1,4,[[3,4,0,1,3],9],[10]],[],[10,[],[1,8,1,[5,2,10],1],[8,3,[1,4,7,1],1,[8]],[0,3,[8,5,0,3,0],[]]]]
+[[10,0,[7,[5,2,5,7],2,3,8]],[9,[[4,9,10,3],10,[],[1,1,5,2,2],[1,2]],3,[[9,1,9]],[[8,8],8]],[[5,8,[0,1,1],[7,7]],1,[3,[2,1],[10]],[]],[[10],3,[3,1,5],[4,[7],[2],2,[7,10,10]]]]
+
+[[],[5,10,[[1,2,6,0],[2,9]],[2,[9,10,6],[2,7,4]]]]
+[[7,[[2,9,4,10,5],6],[[4],9,[0,4,3,5],0,0],4]]
+
+[[[],[4,[1,6,7,7,3],[7,5,2,4],[5,10,1,2,7],[]]]]
+[[[8],[3],8,4]]
+
+[[2,8,0],[[]],[],[[]],[1,[2]]]
+[[[4,0,[9,3,2,5,3],[1,4],[2,0]],0,0,[[7,9],[3,9,1,5,9]]],[[[6,0,9],[10,5,0,5],0,[1],[5]],8,10],[],[6,[10,1,[9,9,6,4],[8,8,7,6,0]],[[6,1,9,0]]]]
+
+[[2,5,[[],2],[]],[6,[],1,1],[[7,8,3,8,5]],[[2,3],1,8,7],[]]
+[[[[],[],6,6]],[[7,1]]]
+
+[[9,6,[9],4],[],[],[[[],3,6],[10],[1,[9,9,1,6,6],[],9,6]]]
+[[7,5]]
+
+[[[2,[0,0],8,7,[7,6]],5,[[9,7,7,0,3]]],[[0,7,4]],[7],[]]
+[[[4,2,4,9]]]
+
+[[5,2,[[10,8,8,1],1,8,4],0,[[9,8,4,4],[4,1],4]],[],[1]]
+[[4,7,[[7],0,8,0,1],[6],0],[4,4,9,[[1,3,0,5],[],[3,5,0,3,3]],[6,[9,2,7,9]]],[9],[8,6,7],[[10,[3,2,9]]]]
+
+[[[[8,7,7,9,4]]]]
+[[2,[3,[9,8,5,6,2],[3,3,6,2]],8],[],[3,8],[[[0,0,2],6,3,7],9,[[3,8,8,0],[6,8],[5,9,6],0,7]]]
+
+[[10],[[[8],2,[8]],[],7],[[2,2,[4,6]],5,6],[[],[[],3],[[9],3]],[3]]
+[[[[3,6,7,0],[9,8,8,3,0],5],[10],6]]
+
+[[[4,[6,3,10,5],5,9,4]]]
+[[[[7,0,8,3],10],[[1,4]]],[4,4,[[5,2,6],[3,1,6],[10],[]],[7,3,[],[5],[7,1]],[7,[],1,9,[7]]],[7,[]]]
+
+[[0,[6,[3,3,6,7,5],[6,5]]],[[9],[]],[[4,[7,10,7],[7,5],8,[0,2,2,3,6]],0,1,5,2],[[8,8,[9,8,4],8,6],0,[[9,6,7,7,5],7]],[]]
+[[4,5,4,[[3,2]],[7,5,[9],0]],[[],[],3],[[3,9,[7,3,8,6],[7,10,10]],0,[[0,5],[2],[]]],[]]
+
+[[],[[[4],9,7],9,[[6,9,10],[8]]],[[1,[1,10,6,4],[4,9,6],[5,8,6,5,6],5],[0,[2],9],5,4,[7,2,10]],[9,4,2]]
+[[2,[[1,0,0],4,2,[10,0,9,5,3]],[8,1,2,[6,4],1]]]
+
+[[2,2],[[4,[1,7,7],[4,2]],[4,9,[10,5,10,1],[3]],[5,[],9,[7],3]],[[],[9]]]
+[[[[7]],[2],[2,[3,2],[0],9],10,5],[4,3,2,[[7]],3],[[[7,2,4],0,0,[3,8]],[]],[[],0,[],[[],[5,0,0],[0,4,6],3,2]]]
+
+[[],[[2,[0,1,1],10],[2,6,4,[0]]],[6,9,[[0,0,10,7,5],[],[10],[8,7,10,10]],7],[[2]]]
+[[10,[[4,6,0,5]],9,[[3,1,0,9],5,[6,7],7],[[8,9,2,7],[4,6]]],[[8],1]]
+
+[[[],[[10,3],5,[6,10,2,8]]]]
+[[0,9,6]]
+
+[[9,6,0],[[],5,10,10],[],[3,1,[[4,9,7,6,10],10],[[9,6,4,5,2]],6],[10,8,5]]
+[[2,8],[[],[]]]
+
+[[6],[0,[4,[9,9,0,0,7],[9,10],[7]],6,1],[[6],9,[0,8,[3,5]]],[4],[[[0,9,2,4,1],3,5],3,[3],[7],[[6,0,1],[2],[7,1,7,5,5]]]]
+[[9,7],[7,5,[[],[2,0,9,0,0],9,[8,1,3,10]],2]]
+
+[[],[[5],[1,[1,2,6,10,1]],[]],[[],1,8,[[8,7],[7],[4,4,7],[4,9,8]],[[2,6,4],4]]]
+[[6,[10],1],[[9,8,[]],[1,[7,7,1,1,2]],5,[[5,8,9],[10,6,10,6],0,3,9],[7,2,[1,5]]],[4],[3,[2,[8,6,7,2],7]]]
+
+[[9],[8,[[3,0,1,5,5],9],0,6],[1,[],1],[8,3,6,[[8,9],[10,9,6,8,4],[]]],[[],[3,5,1],2,6]]
+[[4,[]],[5],[[],[]]]
+
+[[5],[[[],[2,2]],4],[5,[[],[9,3,0,1,4],[0,2,1]],[[3],[8,4,10],[]]],[]]
+[[10,[6,10,3,7],[0],3,4]]
+
+[[1,[[5]],[4,1,[]],10,[4,[2,6,5,4,2]]]]
+[[[],5,[],5],[8,3,4,6,7],[1,[]]]

2022/inputs/day14.txt

@@ -0,0 +1,146 @@
+477,140 -> 481,140
+468,149 -> 472,149
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+465,152 -> 469,152
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+501,140 -> 505,140
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+498,17 -> 503,17
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+492,131 -> 496,131
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+501,116 -> 505,116
+495,122 -> 499,122
+486,131 -> 490,131
+462,155 -> 462,157 -> 457,157 -> 457,162 -> 471,162 -> 471,157 -> 465,157 -> 465,155
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+504,104 -> 504,105 -> 521,105 -> 521,104
+503,70 -> 503,71 -> 518,71
+501,15 -> 506,15
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+504,119 -> 508,119
+529,93 -> 529,95 -> 526,95 -> 526,100 -> 541,100 -> 541,95 -> 533,95 -> 533,93
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+462,155 -> 462,157 -> 457,157 -> 457,162 -> 471,162 -> 471,157 -> 465,157 -> 465,155
+471,146 -> 475,146
+502,46 -> 502,48 -> 494,48 -> 494,55 -> 507,55 -> 507,48 -> 506,48 -> 506,46
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+502,46 -> 502,48 -> 494,48 -> 494,55 -> 507,55 -> 507,48 -> 506,48 -> 506,46
+495,134 -> 499,134
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+498,125 -> 502,125
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+501,122 -> 505,122
+495,140 -> 499,140
+520,108 -> 520,110 -> 516,110 -> 516,113 -> 529,113 -> 529,110 -> 525,110 -> 525,108
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+502,46 -> 502,48 -> 494,48 -> 494,55 -> 507,55 -> 507,48 -> 506,48 -> 506,46
+498,119 -> 502,119
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+498,137 -> 502,137
+474,149 -> 478,149
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+517,90 -> 531,90
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+483,152 -> 487,152
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+483,134 -> 487,134
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+489,134 -> 493,134
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+477,146 -> 481,146
+462,155 -> 462,157 -> 457,157 -> 457,162 -> 471,162 -> 471,157 -> 465,157 -> 465,155
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+462,167 -> 462,168 -> 474,168 -> 474,167
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+520,108 -> 520,110 -> 516,110 -> 516,113 -> 529,113 -> 529,110 -> 525,110 -> 525,108
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+520,108 -> 520,110 -> 516,110 -> 516,113 -> 529,113 -> 529,110 -> 525,110 -> 525,108
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+529,93 -> 529,95 -> 526,95 -> 526,100 -> 541,100 -> 541,95 -> 533,95 -> 533,93
+474,143 -> 478,143
+497,13 -> 502,13
+529,93 -> 529,95 -> 526,95 -> 526,100 -> 541,100 -> 541,95 -> 533,95 -> 533,93
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+505,17 -> 510,17
+529,93 -> 529,95 -> 526,95 -> 526,100 -> 541,100 -> 541,95 -> 533,95 -> 533,93
+462,155 -> 462,157 -> 457,157 -> 457,162 -> 471,162 -> 471,157 -> 465,157 -> 465,155
+477,152 -> 481,152
+462,167 -> 462,168 -> 474,168 -> 474,167
+504,104 -> 504,105 -> 521,105 -> 521,104
+489,128 -> 493,128
+520,108 -> 520,110 -> 516,110 -> 516,113 -> 529,113 -> 529,110 -> 525,110 -> 525,108
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+502,46 -> 502,48 -> 494,48 -> 494,55 -> 507,55 -> 507,48 -> 506,48 -> 506,46
+529,93 -> 529,95 -> 526,95 -> 526,100 -> 541,100 -> 541,95 -> 533,95 -> 533,93
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+483,140 -> 487,140
+529,93 -> 529,95 -> 526,95 -> 526,100 -> 541,100 -> 541,95 -> 533,95 -> 533,93
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+507,122 -> 511,122
+489,140 -> 493,140
+510,125 -> 514,125
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+480,149 -> 484,149
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+492,125 -> 496,125
+503,70 -> 503,71 -> 518,71
+520,108 -> 520,110 -> 516,110 -> 516,113 -> 529,113 -> 529,110 -> 525,110 -> 525,108
+462,155 -> 462,157 -> 457,157 -> 457,162 -> 471,162 -> 471,157 -> 465,157 -> 465,155
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+462,167 -> 462,168 -> 474,168 -> 474,167
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+491,17 -> 496,17
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+502,46 -> 502,48 -> 494,48 -> 494,55 -> 507,55 -> 507,48 -> 506,48 -> 506,46
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+504,125 -> 508,125
+462,155 -> 462,157 -> 457,157 -> 457,162 -> 471,162 -> 471,157 -> 465,157 -> 465,155
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+502,46 -> 502,48 -> 494,48 -> 494,55 -> 507,55 -> 507,48 -> 506,48 -> 506,46
+504,68 -> 504,59 -> 504,68 -> 506,68 -> 506,60 -> 506,68 -> 508,68 -> 508,63 -> 508,68 -> 510,68 -> 510,67 -> 510,68
+486,137 -> 490,137
+502,46 -> 502,48 -> 494,48 -> 494,55 -> 507,55 -> 507,48 -> 506,48 -> 506,46
+462,155 -> 462,157 -> 457,157 -> 457,162 -> 471,162 -> 471,157 -> 465,157 -> 465,155
+529,93 -> 529,95 -> 526,95 -> 526,100 -> 541,100 -> 541,95 -> 533,95 -> 533,93
+504,104 -> 504,105 -> 521,105 -> 521,104
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+471,152 -> 475,152
+520,108 -> 520,110 -> 516,110 -> 516,113 -> 529,113 -> 529,110 -> 525,110 -> 525,108
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+494,15 -> 499,15
+490,43 -> 490,42 -> 490,43 -> 492,43 -> 492,35 -> 492,43 -> 494,43 -> 494,38 -> 494,43 -> 496,43 -> 496,36 -> 496,43 -> 498,43 -> 498,39 -> 498,43 -> 500,43 -> 500,35 -> 500,43 -> 502,43 -> 502,36 -> 502,43
+514,84 -> 514,79 -> 514,84 -> 516,84 -> 516,78 -> 516,84 -> 518,84 -> 518,77 -> 518,84 -> 520,84 -> 520,82 -> 520,84 -> 522,84 -> 522,79 -> 522,84
+492,137 -> 496,137
+480,137 -> 484,137
+520,108 -> 520,110 -> 516,110 -> 516,113 -> 529,113 -> 529,110 -> 525,110 -> 525,108
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30
+482,30 -> 482,23 -> 482,30 -> 484,30 -> 484,20 -> 484,30 -> 486,30 -> 486,26 -> 486,30 -> 488,30 -> 488,23 -> 488,30 -> 490,30 -> 490,20 -> 490,30 -> 492,30 -> 492,25 -> 492,30 -> 494,30 -> 494,29 -> 494,30 -> 496,30 -> 496,24 -> 496,30

2022/inputs/day15.txt

@@ -0,0 +1,30 @@
+Sensor at x=2332081, y=2640840: closest beacon is at x=2094728, y=2887414
+Sensor at x=3048293, y=3598671: closest beacon is at x=3872908, y=3598272
+Sensor at x=2574256, y=3973583: closest beacon is at x=2520711, y=4005929
+Sensor at x=3011471, y=2514567: closest beacon is at x=2999559, y=2558817
+Sensor at x=3718881, y=2593817: closest beacon is at x=2999559, y=2558817
+Sensor at x=2388052, y=2201955: closest beacon is at x=2163809, y=1961540
+Sensor at x=3783125, y=3897169: closest beacon is at x=3872908, y=3598272
+Sensor at x=1864613, y=3918152: closest beacon is at x=2520711, y=4005929
+Sensor at x=2850099, y=689863: closest beacon is at x=3231146, y=2000000
+Sensor at x=3431652, y=2328669: closest beacon is at x=3231146, y=2000000
+Sensor at x=3480248, y=3999492: closest beacon is at x=3872908, y=3598272
+Sensor at x=455409, y=3347614: closest beacon is at x=-399822, y=4026621
+Sensor at x=2451938, y=2950107: closest beacon is at x=2094728, y=2887414
+Sensor at x=1917790, y=3194437: closest beacon is at x=2094728, y=2887414
+Sensor at x=3947393, y=3625984: closest beacon is at x=3872908, y=3598272
+Sensor at x=1615064, y=2655330: closest beacon is at x=2094728, y=2887414
+Sensor at x=3630338, y=1977851: closest beacon is at x=3231146, y=2000000
+Sensor at x=3878266, y=3019867: closest beacon is at x=3872908, y=3598272
+Sensor at x=2837803, y=2395749: closest beacon is at x=2999559, y=2558817
+Sensor at x=3979396, y=3697962: closest beacon is at x=3872908, y=3598272
+Sensor at x=109399, y=250528: closest beacon is at x=929496, y=-688981
+Sensor at x=2401381, y=3518884: closest beacon is at x=2520711, y=4005929
+Sensor at x=3962391, y=71053: closest beacon is at x=5368730, y=-488735
+Sensor at x=1751119, y=97658: closest beacon is at x=929496, y=-688981
+Sensor at x=2932155, y=2967347: closest beacon is at x=2999559, y=2558817
+Sensor at x=3326630, y=2845463: closest beacon is at x=2999559, y=2558817
+Sensor at x=3959042, y=1734156: closest beacon is at x=3231146, y=2000000
+Sensor at x=675279, y=1463916: closest beacon is at x=2163809, y=1961540
+Sensor at x=3989603, y=3500749: closest beacon is at x=3872908, y=3598272
+Sensor at x=1963470, y=2288355: closest beacon is at x=2163809, y=1961540

2022/inputs/day16.txt

@@ -0,0 +1,64 @@
+Valve AA has flow rate=0; tunnels lead to valves AM, AN, BN, LA, RJ
+Valve AM has flow rate=0; tunnels lead to valves OJ, AA
+Valve AN has flow rate=0; tunnels lead to valves AA, IX
+Valve BB has flow rate=0; tunnels lead to valves NS, HR
+Valve BN has flow rate=0; tunnels lead to valves AA, YH
+Valve CN has flow rate=7; tunnels lead to valves YH, EO, WX, NR, OM
+Valve CV has flow rate=0; tunnels lead to valves KV, NS
+Valve DT has flow rate=16; tunnels lead to valves UU, HU, KA, VH
+Valve EE has flow rate=0; tunnels lead to valves LY, RI
+Valve EO has flow rate=0; tunnels lead to valves IK, CN
+Valve FM has flow rate=0; tunnels lead to valves VT, RP
+Valve GG has flow rate=12; tunnels lead to valves ML, IL, MH, OL, KA
+Valve GQ has flow rate=0; tunnels lead to valves YA, KO
+Valve HF has flow rate=0; tunnels lead to valves NR, SU
+Valve HG has flow rate=0; tunnels lead to valves MH, RP
+Valve HN has flow rate=0; tunnels lead to valves KV, LR
+Valve HR has flow rate=11; tunnels lead to valves BB, KO, LR
+Valve HU has flow rate=0; tunnels lead to valves TQ, DT
+Valve IK has flow rate=0; tunnels lead to valves EO, RP
+Valve IL has flow rate=0; tunnels lead to valves GG, XD
+Valve IP has flow rate=0; tunnels lead to valves WX, VT
+Valve IX has flow rate=0; tunnels lead to valves AN, JQ
+Valve JC has flow rate=0; tunnels lead to valves JQ, NJ
+Valve JQ has flow rate=6; tunnels lead to valves IX, JC, PX, YN, OM
+Valve KA has flow rate=0; tunnels lead to valves GG, DT
+Valve KO has flow rate=0; tunnels lead to valves GQ, HR
+Valve KV has flow rate=13; tunnels lead to valves HN, CV, PE, XD, TA
+Valve LA has flow rate=0; tunnels lead to valves AA, MU
+Valve LI has flow rate=15; tunnel leads to valve XG
+Valve LR has flow rate=0; tunnels lead to valves HR, HN
+Valve LY has flow rate=0; tunnels lead to valves EE, RP
+Valve MH has flow rate=0; tunnels lead to valves GG, HG
+Valve ML has flow rate=0; tunnels lead to valves RI, GG
+Valve MU has flow rate=0; tunnels lead to valves VT, LA
+Valve NJ has flow rate=0; tunnels lead to valves QF, JC
+Valve NR has flow rate=0; tunnels lead to valves HF, CN
+Valve NS has flow rate=23; tunnels lead to valves CV, BB, UJ
+Valve OJ has flow rate=0; tunnels lead to valves RP, AM
+Valve OL has flow rate=0; tunnels lead to valves GG, SU
+Valve OM has flow rate=0; tunnels lead to valves CN, JQ
+Valve PE has flow rate=0; tunnels lead to valves KV, RI
+Valve PX has flow rate=0; tunnels lead to valves XZ, JQ
+Valve QF has flow rate=17; tunnels lead to valves YI, NJ
+Valve RI has flow rate=4; tunnels lead to valves ML, EE, TZ, RJ, PE
+Valve RJ has flow rate=0; tunnels lead to valves AA, RI
+Valve RP has flow rate=3; tunnels lead to valves HG, FM, OJ, IK, LY
+Valve SF has flow rate=0; tunnels lead to valves YN, SU
+Valve SU has flow rate=19; tunnels lead to valves TQ, HF, OL, SF
+Valve TA has flow rate=0; tunnels lead to valves KV, VH
+Valve TQ has flow rate=0; tunnels lead to valves HU, SU
+Valve TZ has flow rate=0; tunnels lead to valves VT, RI
+Valve UH has flow rate=25; tunnel leads to valve YI
+Valve UJ has flow rate=0; tunnels lead to valves YA, NS
+Valve UU has flow rate=0; tunnels lead to valves DT, XG
+Valve VH has flow rate=0; tunnels lead to valves DT, TA
+Valve VT has flow rate=5; tunnels lead to valves IP, XZ, TZ, FM, MU
+Valve WX has flow rate=0; tunnels lead to valves CN, IP
+Valve XD has flow rate=0; tunnels lead to valves IL, KV
+Valve XG has flow rate=0; tunnels lead to valves LI, UU
+Valve XZ has flow rate=0; tunnels lead to valves PX, VT
+Valve YA has flow rate=21; tunnels lead to valves UJ, GQ
+Valve YH has flow rate=0; tunnels lead to valves CN, BN
+Valve YI has flow rate=0; tunnels lead to valves QF, UH
+Valve YN has flow rate=0; tunnels lead to valves SF, JQ

2022/inputs/day19.txt

@@ -0,0 +1,30 @@
+Blueprint 1: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 12 clay. Each geode robot costs 4 ore and 19 obsidian.
+Blueprint 2: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 11 clay. Each geode robot costs 2 ore and 7 obsidian.
+Blueprint 3: Each ore robot costs 3 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 13 clay. Each geode robot costs 3 ore and 12 obsidian.
+Blueprint 4: Each ore robot costs 2 ore. Each clay robot costs 3 ore. Each obsidian robot costs 3 ore and 18 clay. Each geode robot costs 2 ore and 19 obsidian.
+Blueprint 5: Each ore robot costs 2 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 19 clay. Each geode robot costs 4 ore and 13 obsidian.
+Blueprint 6: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 7 clay. Each geode robot costs 4 ore and 11 obsidian.
+Blueprint 7: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 15 clay. Each geode robot costs 4 ore and 17 obsidian.
+Blueprint 8: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 13 clay. Each geode robot costs 3 ore and 7 obsidian.
+Blueprint 9: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 12 clay. Each geode robot costs 3 ore and 15 obsidian.
+Blueprint 10: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 4 ore and 18 clay. Each geode robot costs 4 ore and 11 obsidian.
+Blueprint 11: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 8 clay. Each geode robot costs 2 ore and 15 obsidian.
+Blueprint 12: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 4 ore and 8 clay. Each geode robot costs 3 ore and 7 obsidian.
+Blueprint 13: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 3 ore and 10 clay. Each geode robot costs 2 ore and 10 obsidian.
+Blueprint 14: Each ore robot costs 2 ore. Each clay robot costs 3 ore. Each obsidian robot costs 3 ore and 13 clay. Each geode robot costs 2 ore and 20 obsidian.
+Blueprint 15: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 19 clay. Each geode robot costs 3 ore and 8 obsidian.
+Blueprint 16: Each ore robot costs 3 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 16 clay. Each geode robot costs 2 ore and 18 obsidian.
+Blueprint 17: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 9 clay. Each geode robot costs 3 ore and 19 obsidian.
+Blueprint 18: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 11 clay. Each geode robot costs 4 ore and 8 obsidian.
+Blueprint 19: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 12 clay. Each geode robot costs 3 ore and 17 obsidian.
+Blueprint 20: Each ore robot costs 3 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 14 clay. Each geode robot costs 3 ore and 17 obsidian.
+Blueprint 21: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 15 clay. Each geode robot costs 3 ore and 16 obsidian.
+Blueprint 22: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 16 clay. Each geode robot costs 4 ore and 16 obsidian.
+Blueprint 23: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 19 clay. Each geode robot costs 4 ore and 11 obsidian.
+Blueprint 24: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 18 clay. Each geode robot costs 4 ore and 9 obsidian.
+Blueprint 25: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 17 clay. Each geode robot costs 3 ore and 16 obsidian.
+Blueprint 26: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 20 clay. Each geode robot costs 4 ore and 7 obsidian.
+Blueprint 27: Each ore robot costs 2 ore. Each clay robot costs 2 ore. Each obsidian robot costs 2 ore and 8 clay. Each geode robot costs 2 ore and 14 obsidian.
+Blueprint 28: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 20 clay. Each geode robot costs 3 ore and 14 obsidian.
+Blueprint 29: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 4 ore and 20 clay. Each geode robot costs 4 ore and 8 obsidian.
+Blueprint 30: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 18 clay. Each geode robot costs 3 ore and 13 obsidian.

2022/inputs/day23.txt

@@ -0,0 +1,70 @@
+#...#.####.......###.#..##.#####.#...##.##.##.#.#.#...#.#...##...#..#.
+#.#.####.#.#.###...#####.##..####..#.###...#.#...........#..#.#..##...
+#.#####....#..###.#.###..##.#.#.#..#...###...####.#.##.#.#..#.###.#..#
+.#..##.....##.##.#.#...##.#.##..#..##.#.#...#####...####..###...##..#.
+##...###..##....##.#.#...#...#...##...#..#.#..##..###..##......####.#.
+#..##.#.#...####.....###.#...#####.....##.##.#....#.#.......####..#.#.
+..#.###....###..##.....#...#...#####....#.###.....###..###.#####..#...
+#..###..##...##.#.#...##.#.#.#.###.#######.#.###...#..#.######....##.#
+#.....###.....####.#..#...##..#.#.#...##....##.###.#.#...#.#.#..#.###.
+.#...#......#......##..##.#....#.......##....##...#####...###..#.#.###
+.#.####...#.###.##..##.#.#.##.##.####..####.###.#######..##...#..###..
+.....##......#.#.##.######....#.#.#.#####.##.#.##...#.#..###.#.#.###..
+.#.##.#.#.##..###.#..#...#####..##..#.#####...#....#..#.#...#.##.#....
+.####...#....#.#.##.#.##.####......#......###....####.....#######....#
+.###...########.##.#..#.#...#.##..####.##.#####.#..#.#....##...#...##.
+#..###..####.#....#.#..#####.##.#.##...#.#.###.###.#.#....###...#.##.#
+###..#.###.#.#####.###....###..#...##.###.#..##.####.#.#.#.###...##.#.
+.#####.#..##..#...#.##.#..##.#.#.#...##.##..####..#.##.........#..##.#
+.#.###...#....#.##.######..#...##.#...###.##...###...########..#.#.###
+.######.#...##.####.##..#..#...#.#..##.##.#.##.#.#.#.##.#.###..##.##.#
+#...####.#.#..##.#...##.#.#...##.#......####...#..#....##.##..#.###.#.
+#....##..#.##....#######.#...#..#.####.##.....###.####.#.###..#..####.
+..##..##.#....########..#.##.......#...#.#.........##.#.#..#....####..
+.#..##.#.#.##...#.....##...##.#.#...#....#..#####.#..#..#.###..#.#.###
+#.##.##............##.##.....##.#...#.#..##..#.#..###.....#..#..#..#.#
+..#.....#..#..#.#.....#...###.#.#..#....##.##...#...##.##....#..##...#
+..##...##.##......#...#..#####....#..#......###.#..#####...####.#....#
+#..###.##..####.#....#..##.#..##.##.#.#..######.........#.##....######
+..#.######.#.##...#..####..##....##..###.#.###.#.#..#.##.##.###.#..#.#
+..#.####.###.#.#..###..#######.#..##.#....#.#####.###....#.#..###...##
+....#....#..###.#...#......#..##...##..##.#.###...###.#.#.#.#..#...#.#
+#....#..##..##.###.####.#######.###.###...#...#..###...#...#.#..#.##.#
+#...###.##..#.#..#.#..#.#.#..###..####.##.##.#...###.#.###########...#
+##...#...#...#..##....#...#...#....###.#######.....#.#.##...##..#.#..#
+.....##.##.#.#.#..#..###....##.#....####.#.##.####..#.##.#..##.##.###.
+....##.#....#####.#.##.........##.######.#..###..###..#.#.##.###.....#
+...##..#####....##..####....##..###.##.##..##...#.#.###.#.#.##.#.##...
+..#..####.#..#.##.##.#..####..#.#...##.....#...#....###..#.#.##..#.##.
+#####.#..#.#.###..#.#.###.#######.#.#...#........##..#...#.##..#.##.#.
+.#..###.###.#..##.####.##.###...#..#.#.....#.#.#...#....#.###..##.#.#.
+.#.#.....##.##.#.####..##.#.#...#.#..#.....#..#....#......#.######.##.
+...##.##..#....###...#..#.#..#.#.#.##..##.#..#.####..####.#.#.........
+#.###.#...#....#...#.###.....#..#...##.#.#.####..#...#.#.#..####......
+##.###.#.#####.#.##....#..#..##..##..#..##..##...#.#.##.##....#...##..
+.###..###....#...##..###..#....###.....#..##...###.###.###..##.#..####
+#.###........#..##.#.....#.....#...##.#####.#.##..##....####.#...##.#.
+#.#.#..###.##.###..###..##..######..##.#####......#.##....##.#..###.#.
+###...##.#.#.#.#.#.######...#..##.....#.#######.#..#..###.#.###.#...#.
+###..######......#.###..#.....#########....#####.##..#...#.#...###..##
+##.#..######..#.###..#.###.###.#.#####.####.....#...#.#...#####.#..##.
+...####.#.#####.##...##..#.######.###....#.###.#.##.#####...#.#.#.####
+#..###.########.#.###.#.####.###.###.#..#.##.#.#####..####.#.###...###
+#..#.....#.###.#.##.###.#.....#..#....#####.#.#...##.###.######.###.##
+##.#.#...###.#.#..#.#.###....###..#.##.#..#..###.#..#######.##.###.###
+.##..##.#..#.#####.###.#.#.#......#.#.##.#...#.######.##...#.###.#####
+#####....#.##....##.###..#.###..###.##...####.###.###..##.####.#.##.##
+#......#.##.##.##.#....#.##.##..########.#....#..#..###.#####.#.#..##.
+.#..#...#..##.#..###...#......##.##.###.....#.#.#.#..#.#####.##..#.###
+.##.##.#.##.###..#..##.####.#.#..####.#.#.......##.......##.....#####.
+####...##...#.#.#..###.#####.#.#.#.##.#..##......#.###.##..#...#...#.#
+...........##.#.####.#.#########..###....#...#.......#..####..#####.#.
+.#.###.##.#..####..#.###.#.#####..##.#......#.#..#####.##.#.###.#.##.#
+###..#...#.##.####.#.##...#..#.......######...#....##....#.....#...#..
+####.#.#...#.#.#######.##...#..#.#..#####...#..#.#..##.##.....##.##.#.
+###..##..#..#.#.##.##..#..##..##..#####.#.##..##.####.##.##...#.####.#
+#.##.#.#..##..####.....#.###..#....###.#.##.###.#.#.#.######.##....#..
+.#.#..##..#.###.#.....##.##..##....####..#.#..#..##########.#...#...#.
+###.####.#.#.##.#......#.###......##.###..##.##.#..#....#.##.#..#.....
+.....##.......###.#..####.#.#.#.###..##...##...####.#.##.#.#.#..#.#.##
+..##.##.#..#.##.....#...##.#...#.###..##.#.##...#..#.....###.#.#####..

2022/inputs/day24.txt

@@ -0,0 +1,22 @@
+#.######################################################################################################################################################
+#.v><><<>^^^<><<>.^v<>v^>v^v^^<..^v>^>^vv.>v^<<>^.v<vvv<.>><v>><^>><>^<><v<>>>><v>v<^<>^.v..v^vv<v<<vv.v>>v<>v.<..^<vv<^v^v.v>>v>><^v>^<.vv^^<<><<>v>><#
+#.vv<vv<>.v<<<<<>>vv<>^v^^<^<>><.<^>^<^>^<v<<<<v>v>><.><.^><>vv<^^><<<<>^<.<v^.vv^vv>v>^.<<<><v<.v.<><<v^^v>^^<^>>^.<v^v.v><<v^vv<<v>^v>><^^<^<v>^>><v<#
+#<v^>v^vv<><v><<^<>^<^vv>v>>^^><<<vv><v.v.^><<^><>v>^<^v<<^>v<vv><v<<^.vv^>>>.^v>v.><v>v<^<^^<><<>><<^^^>v<^>>^v>>vv.<>^<><<^v>><^.>v^v><<^^^^<v<>^v<v.#
+#<<^<vv^<^><>^><>^vv.v^v>><^^<>^<>>^><^.^^<.v...>^^.^<<v<vvv>>>v^..^v.v<^><>.>v^.vv<^^vv>vv^.^.vv<v>>^>v.^^^<v<>><vv^>>^^.v>.v^^<^>vvv^<<v^<v<^><^>v<>>#
+#<.<^>>^<v><^>^^.>>v^<v^vvv>>vv.v^<>^^>v<<vv^<>^v.<<<^>>>.^>vvv.^^^<^><<^><v>><^.^>vv^^vv.><<v<^<v^^^.>v>^>v.^^<<^^^>^><><<vv<.<>v>vv>><^^v>>vvv^<...<<#
+#><v.v>vv>^^^>>><v>^^v>^>>><vv^<^<^<<<>.<<.<.<..><><v.v^^.v..v^>>>^v><.^^><<>v^<^<>^>>.v^v.v.>v>^>>>v>>^>><^<.v.v<^<<<<<^^>^^^^>^^<v^>>v><>.<>v><>.>><>#
+#<><<.>^<>^^v<v>^><^>v^.>><vv^vv^<v<<>.>.>>.vv.v<.^<^<>>^><><^.v>>v^^v><>><<<vv<<>v><>^.>>^>v^^><^<v<<><vv^>>.<^<.^<^>vvv>^<.v<^<>.><.>>v<^>^v<<.^<v>^<#
+#<>.<v^>.^<<^v^.<<^>v^^vv<^><^<^>><v^^vvv<<vvvv>>^v><<>^>vvvvv^<<v^.>^<.<^>.^>^><v^<>>.<<^^vv>>>^>vv><vvv^v.>^vv><<<<>^v^^^.>.^>>^^v^v>v>vv^<<^vv^<>v<>#
+#<<>v>v>>v^^v><^<.vv<^>^^>.v^<.^^vv>.<>^<>v>^>vvv<vv^>v^><<<v>vv<..^v^v>v.v><^.<^>.v<v><v>v^>^<<<<<>^.v<^.<v.<<^>v^^^<^<<>v.<<^<<<<.<^><<<^<v<v>>v>.><>#
+#>>.>vvv<<..>^^vv^>.<.v..v^^>^v<<>>>vv.<v>vv^<vv^v><v^^.<<.><..><^><<>^<<><v<.<v.<^<^.^<^<<><><<^v^>.<<v^^>.^<...v.^<^^<><><>v^<><^>^>^v^.>^^>^.vv.<v^>#
+#>.<><v>v<v>v>^v^^v>.v^.v>v>.<>>>^vv<<v>>^>^.^<^vv.vvvv<<>v<^^.>v<^v<<^><^.^^v<>.v<vv><v<v>vvv>^^>v>..<<<v..>v..<^^^<v>^^<<vv<>>^^v^.vv<><^>>.^<<^>>v.>#
+#><v..vv^<v^<>>v<>..<^>v^^><.>vv^vv^<^^v<>vv<.vv^^<>^>>^v<^^<<>^vv>v><>v<^vvv^<>><>^^^v^<v.v^<<^^>>>>><^^>><^v>>vv^v><^>^<<^.v>vv>^.v^<vv^v>>>vv>v^v<^>#
+#...>><v.<v<>^.v.v..^>^<><vv^><<<vv^<vv.><^.vv>>><v^v^>^v>>v<.^<^^<v^<>v<^<><<<.^<<vv.<>>^v^^.v>.<v>^.^>v^.v><^<<>>>^.<<<^v<<<><^>.^.^v><>^>><vv<v.<.^>#
+#<^vv>>v>v<^><^^^<^>vv<>vv>^^^.><><^>v>><v.<>vv^^<^<<<v^<><v>v^v>^<><><><><>^^>><>..^^>v<...vv<^>><.vv<^<v><v<vv^.><>v^<>v.^>>>v<<^<<^vv.>^<.^<>^<v^^^>#
+#>>^vv^.<<.<.<>>vvv<<<..<v><^<>^><<>^.<<^^^<v^<<v.<vv<^<>>vv^>.v^v<^<>>vv<<^>>.v>.v>^^^vvv^v<^><v^><>><^<.>v^^^<vv^>^v<v^<vv><>..^><.>^^<^>>..^.v^<^<v>#
+#<<><^^><v^v<^^<vv>><v..>>>^><>>>v>v>v>v><>>^vv><>>v>>vvvv<<^><>v^>vv>^.>>v.^<v<^.>>>^^v>>><vvv>><.<v<^<v<^v<v<<vvv..^^<<^<.<><<<<^<>v<<<^^>.^v>^^v<^^<#
+#>v^^^<v>^^<v<<<vv><^v.v<v^^^vvv<<><><^^><^^>>>>>><^>^^.>vv>^><<<v<<<^vv.^^^<v>v<^^^^>.^^vv<^<.<v^<vv^^^>><..><^>v><<v>v>^v^>>^^>vv.v^^^>^^vv.<<v.^><<.#
+#<^v<<^^vvv.>v>v>.v><v<^^>^>^>^^v>v^vv^<.^.>>>>>v<>.<<.<^<<vvv..<^>^><^>^<^<<>><^>v<v^v>^v^^^>>>>v>^>>^<v..><.>>^^><^<^.<v^>^.v>^^vv^v.<>>>>.v.<<>^^vv>#
+#<v^v.>.>^v>^<v.<^<^>v^>^^.>.>v<>>>^>vv<>v<>^>v^<<^<.<<^>v^<><>><^^<^^v<>>vv<<.<>v>.>^^^>><^^<^vv.><v<.<<^^>^>><>v><^vv.>v^v^v..<vvv..<<v<v^<<v>^<^>><<#
+#<^v<v^^v^>^<>v^<^<>>..>><>v<.^<.>v.>^v.>>^^<^v>>v^.v>^><>>vv.<<<>v>^.>v>..<<<v.<v^<>^>^<>v<^<v<><^>^v><.<<^^^<^.<<<^.^v^^.>^.<<vv>^v><<>^<^v^^>^v><<^>#
+######################################################################################################################################################.#

2022/inputs/day25.txt

@@ -0,0 +1,124 @@
+21-0==1=-0
+102211-220011-----
+1=2=111=10=-
+12-2=022=2
+1=--=11
+12-2211000=0011-0-
+1=1-
+2=0-10-=21-2
+1210-
+2=1-=
+1=0=12=2112--11=
+2--211=200
+20-02-20
+12=12=0=0=1
+22===21=-0102-012=
+1--=-121
+1=02=2-=
+12-0-20
+2=---=0102--00=22
+1=2==0=2=
+11-1112
+2--012
+12=12=--212-0-==-02
+1=220
+20===1
+2210-02=12-022-=1-
+22--1-==1
+211-1=1=0-==1
+10
+1-1-02
+1=-2==-0=21
+1=102
+20121021
+1=2=22=001200-==1020
+10211-1-20--10-1=
+1222==1--=1--11-=
+11211211
+1=101-20=
+1=1-11=0=000
+1=-=101
+2
+1000-2
+1==0=210=1=21222-=2
+1=1==2-
+2--020=2=2===-
+2-
+2=0
+222101=22=-21=11
+2=
+121201-0-20-2-=11=
+10=
+1212=20=2=-=-1--1
+2-20-=212=01
+1=1--00--0=12=-00
+22--
+22
+22===1=-0-22-
+111-=
+2-111=0021=2
+200=22-=12-2=
+1==-=1=0
+1--=02-0002=
+1=-=2-2=2-
+2=2222220=2==001
+1=00==11=-20-=2-2
+1---0=-=
+1-0==10-=22001
+1=02=02-1=0111
+1-=010-21-=21==02
+10200-2=-=20120-2
+1=-
+10=122-
+210-1=-=2011-0--1
+2==-1=20
+1=-=101-20=221-1
+210
+1-=-==-0-=02=---
+1-=1=-=12=0
+1-=0---12-0=
+210-==1021=010=1
+1=-212
+11=1=-=2211=101222-
+2=-==--=2
+1=11-200--=
+1120-
+11=-0=221=0101=
+11-1=-
+1-12-2=0
+1012-22=1-
+20-122=-1=
+1-100=0=101-0
+20-1=1=0
+1102=
+21
+10=20=11
+1-=2001
+1-20=12-0221102-==
+1-1--010100=-1=
+221002==2102-2=1
+2012=121-22
+110222002=01
+212102-1=1=-211
+210-=12
+1=-1-0101=1-12
+12--21=1
+10=-12
+100-122211=--2=
+101102001
+11011=-
+211-0=-=0
+1-2=01-1=
+1-022-=00000
+2==-0==2=--00=
+10=--2000==
+1---=--1-110-02
+11-012
+2==-2210-0
+212
+22-=-12111
+2--=
+2=2=12-100
+10-12===0-
+1==0=0=22012201
+211-1--22

2022/inputs/day3.txt

@@ -0,0 +1,300 @@
+LLBPGtltrGPBMMsLcLMMVMpVRhhfCDTwRwRdTfwDllRRRDhC
+gNFJHJFgtZFJjZJHNNFWZWZwwDjCwSDhfCDbdwjfwDTTDT
+gmQNZnZNHWnqmQpLtVLMBsPpBqrL
+HlHldQtHlctzppdQtjdczHhJRnnhGNVmVRJmVjCVFCNh
+LgWNgggZJZGFhCZr
+DbqPswwMvDPqzlBNHtzfHdwd
+tJgtJwwCtNvPHHPtHzDsdRTsBRDDWgWTgT
+QhLQjLGjZQFlFZmnmGLDrzWfRldrTrzTBRWTzs
+bFFmFZjhSFHvBCvCvJpb
+MSGcvnvMGMJgWJDpdndZwBnppfCp
+VPVfQQVbshZNZwdNDwNs
+LtLbjmQRLmVhQtTbfgWjJgFFcrqqrGSqWg
+fHfCNCwwHfGhcntntrrgHrQnrn
+FVqpSpbPpjSVMjqvVmVvMzlzwJnbtnnlzQQlrWzJgt
+PTqqRRPSRSmqSpPpSpRZwGCLGscCNLZZZTNdNZ
+pQQQslVSVzzCQnZSlplzbLcHZHcrrrbZqFbZjbFm
+gWtvPgdMDDtFDHHjJJbbccbrLW
+MhNvwwDfDfdtvRQnpFNNTlSRSn
+ZTnSnTTzqvFmVzvWWm
+ClpCgltHNrtgsHdpLCHtDCNLVvQvVwVmwcsWQGMMQvcGcFcv
+JmrgCHCNJtlmHmNhnJjnnnjJhPfhSJ
+BgRRZTgHHvRTRmRNLNNhQWlmGFfJlWlhsQshpF
+qPqSSttwnnzqqqwtVrPwMthFsJllJJlGhpJhWJQlhVQd
+MjMwScnDPzcwjtqDtztnctrvgNZTTvCvLgvQbLbvjTBvBg
+SWQSbbqTTbPcfMZSwZZwwn
+dghjghmNDmGsGgdnfmtMRCLCCRncfc
+pJDJNdsNMMhpssgdprBTBzWlpBWlllWb
+TwNLNZTwWCWLwWCSTZSLzWHGrDHHPmGdDHvndGdNfvMm
+BgpjtpgjBjVbRjQRhVsDnvgGgPnGdrmvnMDfrf
+rhRjRssQJplRtVbpthblbbLSLzFCJZFqLLFWCzqcqzLL
+PBrdPMtBPvCQBVBjCfWPqSHbszhGGnsfSG
+JpmDwJgWJgNzmShhmfSGzh
+pRwNcNpFZNZRWgcNplpjVCMVjdvdMQtCMLZjMZ
+lDrcnnlLqLRcDDZRLjFVTHzGCLGVPzGPVWGB
+pNwHpdmsNJsbpwsbzJTCPWTVFzzQTWCQ
+vbhswdtdwfdsmtNSssHwvllvMcZjnjcnZqlgMDZglM
+GVVtJGtzVFsVsDTH
+mQRgcBRmRLnBjrtFjCCrHmFF
+gqpBnlRpgZcvdSdlMdSvMt
+tMSCNGSflffNhnnGqlPPsrzWPrTrVpWr
+bZHbmDBQmbDZQdbDcRFZZBTTWWWwqVzszWjrFPVwrzqq
+HQBLHmQVQLDdCggMfgMNLvNG
+HHNDzNJPJPmdPcNGGGhnhwnVhCQBwBjQ
+bsSbLfrLtRSLRSRRRsBwhCpfpCzlwCBVjlCV
+zvvsvqLtZqLtzRsqTrggRMHJNWJgHHHNJcgWNPdHcH
+qgbNvqbgmmZgZLvZqgnZzlpzpzHtVPzttGPrrnnl
+jwswGjQDMsQMjdBwdcjCHVtcPVpCVCrPlVSrpc
+GsFWBfhGBfDFDFWqNbLNqbgvqbbvfN
+HgwWqtcqHNWgnHcNNCfvJCCJJfJGvnPfrR
+sbDhZSmdBbsSdmSDdrjjffRvdjPrprCd
+vvZbSFFlFHtqFqqWNc
+ZRjnbRsHlncZGjTRTfFVSQBQppQvvFBHpF
+zrLwMdhDhqJJttDQSldQVPQSlSfPlV
+hCWWCzqWnmcZlRRW
+HfgfQflHjWgRQRdRBWVsnbvvscbbbwvmbHncSc
+tJGLtPPGZPwVvSSPhw
+CLGTLZqJtMGqLDFFDZZJFZJpWjRpVNRWpllDpjlBfgVjlp
+rhhGZZhLNhPmfJqvfLlq
+dHRTHRHQQWcTCRTHmmjJgfqqlGmgWgql
+CCwRzTRRdCCRSQwzRcppprZtrMhGBMZMnDSt
+WfffvnSnfSBshwsjhlvGlh
+ZHpFNTmppVmNzVVmmFMZzbwwjHGrGlPhCGrljbgHsg
+pLZMmqVsZVMMVVscDfdtSSStqcRRdn
+RhRbLzRLHLCPmzznHLbzCRTJhdTVSJJVSjdFFNFFNTJv
+MGgMfpMsBgpnMtGfnfwBtDBjFVdNSSSFdvJSQSpTJdJjNv
+lMsBgDMsblmRblnz
+ClNcJZttLfLvvRQzQWwRQN
+hrpMdqMspsrGDdMphhdMMMMHBmRWmSVrRVzVTzQBQvSmzVWV
+ppHDMGhMMDbGMdDMGbgFbgbMlJJnjjZtZfLPcfcngZfPPfCR
+ZRslLRgCclZLZzQghQhfrbfGbJ
+pVSHpBBBBDVDqDBldVzfrMzQbfSTSJrzzJrJ
+DqqHnBDlpNDVVnpnjtDtNjCvFLcsFFPZRcPsNNmPcFcP
+LmLWSmSRNdcpcRHFHrWzWHbMbwZlZlPSbTjlwPbTPJTf
+DttBsvhnhqvGGBhGtBVNBVqJlPwslMMPJwTjZbbZPTfbPs
+CDthQvVNVFCHHWCFdr
+RRtCWSzQZdRMrtRWrSztMggcGDfQTcfFTGqTLgGDLc
+bnVhnvPHhhdJJBTLDGcDTcBvvD
+pmbnhmPPmHwdCjmdrRtCdj
+lTPzwhzmHpTvrDCDHJnsNN
+tdgtbMMBbWdFbtqJCnsrqnMMDsrq
+FjWdtgLSWttWtLSWtDWBjGGmwGlzTRwPTQGhlQQm
+wcbnTtTppNLrntznTBBccCGrVldRrZqdqRCZdFZCVZ
+JfHDgjgPPfRRgRlLRddR
+jhDhhLMfmJjMjDbNSTzbbbtmttmN
+CfGlvzpvpTjzzCWjvDlfvbbJbCRSdSRhsSQCMhdbhR
+wqrSmrLHHNcLqrrLBNsndssnnhPshnsQwbnJ
+NtcmBLcNVDWzjSvWtv
+vZPCSCvCJffvVvmCmPqCSlDSscczHDRcwcHzRlRHHs
+LFGFNnGrdQttNMFpzpMRRDslsJwsJH
+gjtLnFBJrLvhZvCbZhqB
+DBcjVFjDhQMSJVZbHZbl
+nfmsqppnLfTnfmMmzppwgllSrbSHHtllqbtSwZ
+TRzTnfRWnfdzWssfnRfRpncQPBhdDjjDCPcMQcCBGPPj
+NSjWCHjNHjpPWPpSFWdtqBMBBFVBvqvJGJwqBt
+gQllgDrnhQQDGRshRsZfVtVMRqwMtccVJcBtvRqw
+DQrzrDzhQgrsZLrZjWSSHNTWCjjNGTLH
+CgdcCFcbTbBzPgmNRmpptP
+rsZtsvVvHZZzPmqVNPzNmV
+HZjrwrjnjtHSHwDGdFhCdhWWJnWchCFJ
+RMTqQMRJqPtBtGBPtWjN
+ssHfSfShCwwbhsbHhhsmSfhSGNpCpNCjBBBLptcGtpzBBBWW
+HnwrSFwffHsFwrSSjfHglJJlTgZdFdgZRZTDDM
+pDLDWlDSlJDmzSJnDScRPLGGvqFqLPccGLgv
+CZHfwNMVNjsHNNqPgcbcBbRQGQ
+dCffZCjVCdCHHTmnlSgTlTSrlStp
+bFtlLCvLlVjpCGPJndrrMMCDDCnrMg
+hRsTwcZcBjZRJrfMDnsHrJnH
+mNZqcTSSBTScNzVQFtGtjpFtjmGG
+bjHdLrHjRWpDCtLzhzps
+lZcGfTvQcQfvlqqcNCcBvVwtGzmzthmwmpthMDmswgMt
+NcqflNQTBTTvvQSvqSVvQJbHPHbHCRJdndJPSHjWHb
+CVmRncrRVrhcmsBgfmtfdJsJmt
+bZHvZZDJwpWtdZgtGNGd
+vSbwHDMFMJqPQqQvvSPQqpSwjRcTVTLjLRhVCLFLjLFnFzCC
+mtffsmBwfwBDBmmsLsHqtpftGrMVMPSMPsVvhNvFrGPMvjNV
+TQTQCRWjJcdcQQSPrhhPSvVGPF
+cTRJCnldWJZlTgbWgbdbpqfqmppjmtljpqzmjpLw
+NNPmrmPWmrSSNNPmnglghmCvLCCflh
+LFbsDQMQFtQFHbQHqhvnngCftpcllptJgJ
+bDjsGqLLdRVjPZPP
+tgrbBQlbtRblwtRGrbCNswDDCsvFszpssCss
+SJVMhSZfHvpdhphN
+SMLpWZSSZMjfgGBgRtbQgljQ
+HsHHNDDHzHDDjsVBBZqtWBrSNcPwQvccvvdhPclSrQSc
+fGCFCgpgTfnTmgTFLFgccclhwQhwrzSwSwrCrr
+pmLJGfMRpFmfFMzmgGmRpgmVqWJDqZqqHtjBBVDBBqqssJ
+mBTfcfCCmpBCCSzNQScQSTfddhdtwgttjghNwGtGdgwGtd
+HvvqbvMLnFZVVPjJGRGzGRjZtwgw
+VFHFbsFHHSmzQBmsmT
+ZNmZCmNHHzzmPPzlbplvhbQh
+GDSwldfdvggPfLvQ
+ddqrtlnJDJlnjScRmMRCFHTHtFZF
+FPvglHSPcpNcFNSHFHNvZjdmbwdbzZtzsHDzbsbj
+MMnBLCCWBJCnrCVWCBstTZdZmdTtbDLswTtZ
+BMDnRCrnGhPPSgcgpG
+nsbgpbdrjMdGqnNRRWWRww
+tZZhPzCJhsJBtJPllJBCtCvwwcwwWLvWvwWRThcGcqLq
+mlBmZQPZmlppbgMmfssg
+RFdZTHFCdvjhgGnFqj
+zQLtNQpzNNtNpDtDPWLNMmGfBcjgjlgjhBnvcfnBvfjp
+PtmLsPzQVWzWDswCSwHbRZsGZw
+nPsfnPsFhTGjqGnmQppG
+RZhBbNwbBRZHZSCCHQqSpCpqqm
+VMbgNWRWMDfhtFJT
+RWhRPDhBHZWgZghRZwZgGJPGdncFdLcdLCjscFcjCjNLLj
+mQfSrlfTVqmSVTTTrprfFLqcdLHsLHFnvsFFqnNd
+TtQmVHmMrbMWRggRPJZP
+TTlCTVTdcpBlcchF
+ZLhwSMZhqhtqwqLjFcBvFmvvssGBmmjj
+LwSMRtqMHnqhhRZRRtJSVTgggVPdTdrVbQDJgTPW
+CGFFWFFVgjfzgVfcJCcgTCcBBWqSqMMBMBShhwMLMwSSMq
+fmQnflldltBZqlwqNZpB
+dvtnvmtRtsPbzCfTHjHcPzGf
+hzshzfshVhthgMmRsFRvFqmm
+PDDcZWlWBbplvmRRGtlvqQ
+ncjnDjbScnBWZjDVfwjfrrVtwLjzhr
+QRWvffVVGfDhNNjzGZLLcGGZ
+rgtpSSHpPrHSspvNLFlzTgNLlFglcc
+SSpbMHpvmwMQhMBR
+dHLtBqPCtPBHNsbRNdNNsZVN
+nQwntMwJWhwWjvcjDMlntRsNpgSbNNpglFpVggbSVF
+QDhJWwhzJtTqLzCmtT
+PSLqTqrCrRvCSJWLdLwdVWdQWL
+zNjHQnnHjHznnbDMnMMMdVZcpZZJpZWcdJFZ
+BntfgNbzfBtHzgnbbbPPSstlQSSGGrlGsrTT
+QpBNsBzztgqVtdmp
+jvrhGljRhSTlGGvjwjSwGjRvHVdqLttrMgMbtMMMVmdqqHfV
+ChTvTvljmCsQQQnNsQ
+CQCNSQHHgCtNHCNHHNDJcBJwLPtJBGhMPPPJwM
+zRTqmsdRRzrmdzVRpzPwcjdwwhLjMBMGBBLw
+hprmzRmblTzTVTVrlbrmVHNWNnCZFWNNFZlnDFSWgQ
+hGGqwwdwMqsRDGRBzlvDzB
+LTNTfcCFFFCcNHFFBzRSZRBlzHPSZdvD
+nLVTFNfVVLLWnwnwdrdbhnrhrr
+hlTpcDTpHmHwDmMbbdMMMGTPdGPR
+ZzFqNSQqHvBvzzqjFHtvSGRRMPQsJGJWRGWPMRdRsM
+BZjLNqNqzVVHgLVgll
+ZHHBzSZPVqghJgSnBhqJRQLRRMvQpwZvfNQRMMMp
+ctFCDmdDWmDGNRFMpRlwwQPP
+PrsmDmCGjtcmdjGtVqBSjJhnSbHnnghH
+QmZHTjmmHRmmdPRvHdVlPdrNNLqWzffbRtqpzfWtWsWNNW
+gwMcgnMGFGCjJLqfbtNtzzssCW
+DwMFGBwcBFjhBBhcDSJQQVQTPldTvPlVVZQSdQ
+NRTGfNffLghStLRR
+QlnWsdJWmnbWnVqWbWqHPSpmjgCjtSwhPjgtptLS
+JWchnllHqQJzGTZfTcFNDN
+VtdtcTVVCRctVdJclCVtpphpPhNGDwNPmThwWmgG
+ZjZMFnfBqqMjHZHMzBnzgPGwDmhmhDPfQNGPQGfD
+BbgsnFgMgMlVdJtlcVSs
+tlBMdBnClhLJnTbgph
+PhDDczqDGPqsHGrRGPWHGPzcFJNLTTJZLNbNLfFZgTbffL
+sHsmzzrGmPrRDRHqhHwmjBVtllwtdMdBSBtl
+QscfZsGsVjVtqGmlzvRMvl
+ThJNCHPTDDhHHJTJPHmlSMTtTTlBvlnMSzqn
+HhCdrHrCcpmmdVmb
+WPPBPvRWzvhWhWzGWtBqBSTLDZhgFSTCDgSgZZDCZs
+flbJmMJnjdMqNdfZZrFZZNFZgrrsTZ
+nQnqJlJdlQMMbVnVmdMplVnnBwcBPGttzQcvtHcWwWtHRHvB
+LLsmpJTWCJmJppCmgHCCLjbFtRFghzjfjcjcZttbRg
+SZlMPBdBtQfFSbSF
+nPqldlDwlBVnvdLWJVsmVNZCCVmJ
+HWvNVtHWJjHJsSgHsHzsDsmf
+RwZGPFGMQgzpTGSD
+PZMlwwqhFPPZqwFhPwnFbMjWJNNBtWNVJlCJJWJjWWzj
+frBSzJDtztfNVGwRzVgGhqsV
+MPMmjPWGMMmPCQCcbmRwVhTgVwTTqjvRTLww
+cFpcMGFplDHfBHFS
+gtjhjLffmgjgmbgVfbNdqFJMJMNbbwrwqq
+sWHHPSJsHzTZzTGsCdrqCNNddGdGFGRC
+ZpzHHTZWzsSSnBBPsTBnLVcpQfcJcQVQDQfcDfQt
+qMPqChqjQPRCMqlBrmGmLbPSsTbSvz
+nWNHZFVZZttWpfHsGSbBGTbWBSGmSm
+nZfpVfdZdtFHnwVHZtNwZhCJRJhcCdDcQhCqDSSCQc
+LlwSlZrftFSMpfLCdltTmmmSDmJqmssDVJBmJB
+cRcGGhpvDTmTDgsG
+nNPcjpWbNzjRRcWhbzWjvnLMddMLCwtdtMttddtrCdMz
+NszSsDCMSDzdZpCMCSMpNszfTvJhlvmlmrTfrhlhHPrmhD
+FRWBgRjWwqFWQFBBWjVncjRTvJfvvJvVrHhmVrHhmrdJTh
+wnwnqwRGFqdbNNtCGpCp
+zgsBvPVVDDrDtDgt
+nTHldmJQNTTfflcJNrQlHWpmDDFDFhWpWCLtFbphCm
+nTTNMlNfHQZTQPGSzVVZSVPSwr
+bPLbtPpwsJhlpnhnnLNNZDWhRNzWQrWWffNr
+SczqFdFHSTFjmMSMFVqFGCWWNRrWQQQRZCVWgQQgrZ
+dFdzFGHvjmqGMFwwLLsPnvBspnsn
+lwJwwmblVdvjbbbJvVnlmjGTTNTLqffpqDJffqGLqDLD
+ZtWgPtRMtQRQnTGDQNTTqL
+gCztMgWgchHhvwlllbnl
+cCwSSCVbqwCCWSbZMmGdtBllWBfdlvdt
+jzRsJjhPjnLthJNNpmpvmvvMfGvjQpGv
+nPHPFgRHLtCHZrqTcq
+dVJwCJGCVrQQGTNtLtGm
+hWWgDHBzWWWpZlhWBssLDTDsQTLLtswswL
+gPhBHpjwHcljpggwwWqvbFvdCVRqPPnnqVRb
+zRRRRNqzpQZNNRRmRcZscQcCDmCTTTDGfTbfGhrTCTrbFF
+HMvMtjgtLHVlLVfhCGfrfhJhhrvh
+LBgStjnHBjLVgggBgHndnSNNQdNWcQQNGZccwsccdQpw
+jLRqmZNGtZtvZvHzPfCvSSzhCP
+QbwDVHFrVbDVrDFbzPwSThSfddhWPWzS
+rpnFDccHFHtZNmMmRntj
+RFVdzzlNtrwSTltb
+hHGcqqBcGLQZffHhMwSswSWGrnnbMStC
+cgqLBgQgpgbbPbPz
+lfcgglhfTvmlBvclbgztnSRtSmttwRJwptWR
+FMjDjsdNDjNMQLFFLCMQdtwGGzRwzpGwzdWzzJpGhn
+ZQVNsVZMPsVhCQsFCFsHHlqlcBZrHHfBflbHBB
+vGGQQdwNCTJfQJHJbM
+FFqmzghlzhgqjlFqzZhmhPlRgBDLLRTTcHMbRcJHBLcgRH
+qFrPjnhZmqnhZZjhhmpPzZmtvbpwtdvsSCCsGwdNwvwNCp
+nrFdSHScdRwvdvRm
+NNpPLJJbNbppCvmzbHTbmsTw
+fWLHPlPtpMNBgGQgqggQSMGc
+BcHtrBcnjflfHslsrnltbTgvMwpWnnWpwwwCwCCRRW
+dzGhLSSGDdPNgLLdPWTqWWRMqwRWpvzMMv
+VPZZNhhNSSDhLNSLdFZBVgBbjHcgsgfrbBJbfs
+VMnWjjWTnNNCzzhblbbjlj
+FmHwfFHqpDrJzPQLPLbCDs
+GrdFfHqqSmmwHSqHfpdMNTtTtZCMMZtTRggGZR
+QRlnlTphqNfqdjZNmd
+rDtPmGctFrcgDjJcNjvNJNCcNw
+bgGDtgDbBWBSBVlblmVmsRMmLM
+CcQTQTrrmfQQhZZBpZpSSZ
+JFqSvLlLbWggDvDDFHjsdnshBZpjHBBhBW
+FgJqNvLRMlMMDDblrtfrTCStmCVtNttz
+MRRbbddqtHbMZbqMHHTFTFgwZglWPfgsZWgW
+LCcLjzCNGNcvpvLTFPmzlFsfTgFlgs
+NhNGcrCGrsrvcDpvVcSbtHQJQbnQbSdHMtJV
+bfMfBFcWFsWZHBWRPQpRqdwmMpmddm
+rSShvvVTNVhvVCCvThDlSvCwpGCmRmGQmPwmpLRLRdpq
+DhRzzVNVVgSzTFcgtnbHnHbfBB
+HsTGHHvlvvGTGlHBvlbZstrVrwNjrjVStwVVZR
+PPmgcFJPFcFWmWMgdNtVtQZtDVDVdZZjjR
+LLqWnMnmNvlBLCTzCT
+qTttLqLvGCQqCDlhml
+FJjzrRBrpjRWrCwrBrrwpRbbDzgghSmmNhPQhgNshmDSzSNm
+bJBrbFRjBVnWBrRBnHLfHGfdVtvHttcCdT
+mTzjGPmPPmPNjNBTvlJRlNJzZqrzrSZZSpcZqpgcgcggFr
+QWCwwMwWWhVZFbpQDSpSJS
+stMMsWwMwVWtwJTNNPvvRmTsNPsl
+gGFFNWMMNFTBlLpGpSll
+qvccssdDwDbhMhzwHLppTSHLrdBpBVLV
+PhJhzhMJzwDJwhZZtZQJCjgWtFjZ
+pGqWfqqGcspGqWqppHprpTrzhCzttMBCtbtJmtJbSBvWBt
+QDnVPgVPgDCJBMhmBJgv
+NlZwFlnnPLLlFwDlDlnPPFFHTMTdMZjTTcjsqqcsdfGdcp
+HLzZfHWWQwpgVHjVHr
+JlMlMGGDMtJGdtJhqtlccDgVCSTFFSCSDTggpvFTjSgS
+JcGRMlthtlVNMJRfzWsPnQsnnZNZns
+zVfvMpsbtQmtBlFWBZ
+lLSrlNTNRSFRFhhHRmPR
+dnSJjjwJJGwwnzVlvpszvccM
+SmlcCrpnrnznGzSBBSfzNbtsQsWZQcFbWctcbbZb
+JHgwJPjvdghbbWdDZGNLZb
+JjghvvhRwhwJVhHTzmfRfzGSMrzBfnGC
+JbCmrbnzmntnVJjbCHJJFQFvqgJgQgqLDQ
+NGhhhhPMGhWsSSchWlNsCLBBlLFQCgqvgCFFgQBg
+PdcNWWcdGdPssPPNTSNNtzbTwjntzbbVwtZpCVnb
+tGNgtsNQHsJmwwzddmQw
+hMhhDBwMhDDfCRRBjFDDTTWjdWmrmdWqjlmmmjJz
+RSpSSBhppDhRncRLswZLGvtGvNcNtL

2022/inputs/day5.txt

@@ -0,0 +1,512 @@
+        [Q] [B]         [H]
+    [F] [W] [D] [Q]     [S]
+    [D] [C] [N] [S] [G] [F]
+    [R] [D] [L] [C] [N] [Q]     [R]
+[V] [W] [L] [M] [P] [S] [M]     [M]
+[J] [B] [F] [P] [B] [B] [P] [F] [F]
+[B] [V] [G] [J] [N] [D] [B] [L] [V]
+[D] [P] [R] [W] [H] [R] [Z] [W] [S]
+ 1   2   3   4   5   6   7   8   9
+
+move 1 from 4 to 1
+move 2 from 4 to 8
+move 5 from 9 to 6
+move 1 from 1 to 3
+move 5 from 8 to 3
+move 1 from 1 to 5
+move 4 from 3 to 6
+move 14 from 6 to 2
+move 5 from 4 to 5
+move 7 from 7 to 2
+move 24 from 2 to 3
+move 13 from 3 to 2
+move 1 from 7 to 9
+move 1 from 9 to 5
+move 7 from 2 to 6
+move 3 from 1 to 7
+move 3 from 6 to 3
+move 2 from 7 to 1
+move 1 from 7 to 5
+move 2 from 2 to 6
+move 2 from 1 to 4
+move 9 from 5 to 1
+move 1 from 6 to 3
+move 4 from 5 to 4
+move 1 from 2 to 7
+move 4 from 6 to 2
+move 7 from 2 to 3
+move 2 from 2 to 6
+move 2 from 2 to 3
+move 2 from 5 to 4
+move 1 from 7 to 3
+move 4 from 6 to 7
+move 19 from 3 to 6
+move 3 from 7 to 4
+move 1 from 7 to 8
+move 1 from 8 to 1
+move 2 from 1 to 3
+move 10 from 3 to 2
+move 3 from 3 to 8
+move 1 from 3 to 9
+move 1 from 9 to 6
+move 11 from 6 to 8
+move 2 from 3 to 8
+move 6 from 4 to 3
+move 3 from 4 to 1
+move 7 from 2 to 8
+move 1 from 3 to 6
+move 6 from 8 to 5
+move 1 from 4 to 6
+move 9 from 6 to 9
+move 6 from 3 to 8
+move 1 from 3 to 5
+move 10 from 1 to 3
+move 11 from 8 to 7
+move 1 from 3 to 5
+move 1 from 1 to 8
+move 5 from 9 to 2
+move 1 from 6 to 3
+move 5 from 3 to 6
+move 1 from 3 to 5
+move 4 from 6 to 4
+move 1 from 5 to 9
+move 6 from 2 to 4
+move 2 from 2 to 9
+move 5 from 5 to 1
+move 2 from 1 to 7
+move 10 from 8 to 3
+move 1 from 8 to 6
+move 3 from 6 to 3
+move 6 from 4 to 2
+move 8 from 3 to 8
+move 3 from 4 to 8
+move 4 from 2 to 1
+move 3 from 5 to 3
+move 4 from 7 to 6
+move 2 from 9 to 3
+move 1 from 2 to 9
+move 1 from 2 to 3
+move 2 from 4 to 8
+move 1 from 7 to 9
+move 5 from 7 to 8
+move 2 from 7 to 3
+move 14 from 3 to 2
+move 3 from 9 to 5
+move 1 from 3 to 1
+move 1 from 7 to 4
+move 3 from 9 to 8
+move 7 from 8 to 9
+move 7 from 2 to 5
+move 2 from 3 to 7
+move 2 from 7 to 6
+move 16 from 8 to 9
+move 4 from 6 to 5
+move 1 from 2 to 5
+move 21 from 9 to 5
+move 3 from 9 to 3
+move 6 from 1 to 4
+move 1 from 1 to 9
+move 1 from 1 to 4
+move 2 from 6 to 3
+move 3 from 4 to 6
+move 3 from 4 to 8
+move 1 from 9 to 4
+move 2 from 4 to 6
+move 4 from 3 to 6
+move 1 from 3 to 4
+move 1 from 4 to 9
+move 1 from 9 to 8
+move 1 from 8 to 6
+move 6 from 2 to 1
+move 2 from 8 to 4
+move 6 from 1 to 8
+move 23 from 5 to 9
+move 1 from 4 to 7
+move 1 from 7 to 1
+move 22 from 9 to 7
+move 4 from 8 to 7
+move 1 from 5 to 2
+move 1 from 1 to 9
+move 2 from 8 to 4
+move 6 from 6 to 3
+move 2 from 9 to 5
+move 18 from 7 to 4
+move 18 from 4 to 5
+move 1 from 2 to 7
+move 1 from 8 to 4
+move 6 from 7 to 2
+move 5 from 4 to 5
+move 1 from 3 to 1
+move 1 from 7 to 2
+move 4 from 3 to 4
+move 1 from 3 to 4
+move 1 from 1 to 7
+move 1 from 5 to 8
+move 3 from 4 to 3
+move 3 from 3 to 8
+move 2 from 8 to 3
+move 2 from 4 to 8
+move 2 from 7 to 5
+move 1 from 7 to 9
+move 2 from 3 to 1
+move 1 from 9 to 7
+move 4 from 2 to 3
+move 1 from 8 to 9
+move 2 from 1 to 8
+move 2 from 2 to 4
+move 1 from 9 to 1
+move 4 from 6 to 8
+move 1 from 2 to 7
+move 1 from 4 to 7
+move 4 from 8 to 2
+move 1 from 4 to 3
+move 1 from 1 to 9
+move 4 from 8 to 1
+move 2 from 2 to 1
+move 3 from 3 to 9
+move 2 from 7 to 1
+move 32 from 5 to 1
+move 1 from 8 to 7
+move 6 from 5 to 1
+move 2 from 7 to 6
+move 1 from 9 to 5
+move 1 from 3 to 2
+move 1 from 5 to 9
+move 2 from 6 to 1
+move 1 from 3 to 7
+move 1 from 9 to 8
+move 36 from 1 to 4
+move 1 from 8 to 9
+move 5 from 4 to 9
+move 6 from 9 to 3
+move 2 from 2 to 9
+move 3 from 1 to 9
+move 1 from 3 to 2
+move 30 from 4 to 8
+move 1 from 7 to 5
+move 1 from 3 to 5
+move 3 from 3 to 4
+move 2 from 8 to 5
+move 3 from 9 to 8
+move 3 from 9 to 3
+move 19 from 8 to 6
+move 2 from 3 to 5
+move 3 from 4 to 3
+move 1 from 4 to 7
+move 8 from 1 to 8
+move 1 from 3 to 2
+move 1 from 7 to 6
+move 4 from 5 to 3
+move 1 from 1 to 7
+move 2 from 5 to 4
+move 1 from 9 to 4
+move 12 from 6 to 2
+move 1 from 7 to 8
+move 6 from 2 to 9
+move 3 from 6 to 7
+move 2 from 7 to 5
+move 6 from 2 to 3
+move 8 from 3 to 5
+move 5 from 6 to 8
+move 5 from 3 to 6
+move 1 from 9 to 4
+move 1 from 9 to 8
+move 5 from 5 to 9
+move 3 from 4 to 6
+move 1 from 4 to 9
+move 1 from 7 to 5
+move 1 from 3 to 5
+move 8 from 9 to 2
+move 3 from 9 to 6
+move 27 from 8 to 2
+move 10 from 6 to 9
+move 1 from 6 to 4
+move 1 from 4 to 9
+move 2 from 5 to 6
+move 5 from 5 to 3
+move 2 from 6 to 9
+move 5 from 3 to 2
+move 12 from 9 to 3
+move 5 from 3 to 1
+move 3 from 1 to 5
+move 1 from 9 to 8
+move 1 from 5 to 2
+move 1 from 2 to 1
+move 1 from 1 to 6
+move 1 from 5 to 3
+move 34 from 2 to 4
+move 8 from 3 to 9
+move 1 from 6 to 1
+move 1 from 8 to 5
+move 4 from 2 to 8
+move 3 from 8 to 7
+move 1 from 7 to 2
+move 7 from 9 to 8
+move 1 from 9 to 6
+move 2 from 5 to 1
+move 1 from 6 to 9
+move 1 from 9 to 5
+move 2 from 2 to 5
+move 5 from 8 to 6
+move 2 from 8 to 5
+move 1 from 1 to 3
+move 12 from 4 to 6
+move 2 from 7 to 1
+move 4 from 1 to 6
+move 3 from 2 to 3
+move 1 from 8 to 5
+move 1 from 2 to 6
+move 1 from 1 to 9
+move 1 from 9 to 5
+move 16 from 4 to 1
+move 4 from 3 to 1
+move 8 from 1 to 8
+move 1 from 4 to 1
+move 6 from 5 to 8
+move 1 from 5 to 7
+move 12 from 6 to 9
+move 7 from 1 to 5
+move 2 from 1 to 7
+move 1 from 7 to 1
+move 9 from 9 to 6
+move 15 from 6 to 2
+move 2 from 9 to 7
+move 4 from 4 to 5
+move 2 from 2 to 9
+move 3 from 7 to 5
+move 2 from 1 to 3
+move 1 from 7 to 1
+move 10 from 2 to 3
+move 6 from 8 to 6
+move 3 from 9 to 2
+move 14 from 5 to 6
+move 1 from 8 to 4
+move 5 from 8 to 2
+move 2 from 2 to 3
+move 24 from 6 to 1
+move 3 from 1 to 2
+move 9 from 2 to 9
+move 1 from 4 to 3
+move 1 from 4 to 2
+move 1 from 8 to 4
+move 23 from 1 to 4
+move 3 from 2 to 4
+move 2 from 1 to 2
+move 1 from 8 to 4
+move 3 from 3 to 5
+move 3 from 3 to 4
+move 3 from 5 to 8
+move 3 from 2 to 7
+move 2 from 3 to 8
+move 15 from 4 to 3
+move 2 from 4 to 1
+move 19 from 3 to 9
+move 1 from 7 to 2
+move 1 from 2 to 5
+move 1 from 5 to 4
+move 1 from 7 to 6
+move 1 from 7 to 4
+move 3 from 8 to 3
+move 1 from 8 to 4
+move 5 from 3 to 8
+move 1 from 3 to 6
+move 22 from 9 to 2
+move 17 from 2 to 6
+move 3 from 9 to 3
+move 9 from 4 to 9
+move 6 from 4 to 9
+move 5 from 2 to 6
+move 1 from 4 to 2
+move 1 from 4 to 9
+move 1 from 1 to 6
+move 19 from 9 to 2
+move 4 from 8 to 7
+move 1 from 1 to 5
+move 1 from 5 to 3
+move 1 from 8 to 1
+move 1 from 8 to 2
+move 4 from 3 to 7
+move 12 from 6 to 1
+move 3 from 7 to 3
+move 7 from 2 to 7
+move 9 from 2 to 6
+move 4 from 2 to 6
+move 13 from 1 to 4
+move 8 from 6 to 4
+move 16 from 4 to 8
+move 12 from 7 to 6
+move 3 from 8 to 3
+move 1 from 1 to 2
+move 4 from 3 to 8
+move 5 from 8 to 9
+move 27 from 6 to 8
+move 2 from 3 to 7
+move 2 from 2 to 8
+move 2 from 7 to 5
+move 1 from 5 to 9
+move 1 from 5 to 1
+move 1 from 6 to 9
+move 2 from 6 to 2
+move 2 from 2 to 6
+move 2 from 9 to 2
+move 3 from 4 to 3
+move 1 from 1 to 9
+move 5 from 9 to 8
+move 1 from 9 to 5
+move 2 from 2 to 6
+move 2 from 4 to 6
+move 1 from 3 to 7
+move 1 from 5 to 6
+move 1 from 6 to 7
+move 6 from 6 to 8
+move 2 from 7 to 5
+move 2 from 3 to 2
+move 34 from 8 to 1
+move 1 from 5 to 6
+move 1 from 5 to 3
+move 1 from 6 to 1
+move 32 from 1 to 8
+move 23 from 8 to 4
+move 1 from 2 to 1
+move 24 from 8 to 4
+move 1 from 3 to 6
+move 47 from 4 to 6
+move 2 from 6 to 1
+move 3 from 1 to 5
+move 1 from 2 to 1
+move 3 from 5 to 7
+move 21 from 6 to 2
+move 3 from 7 to 8
+move 2 from 1 to 6
+move 8 from 6 to 4
+move 4 from 8 to 9
+move 3 from 2 to 8
+move 4 from 4 to 2
+move 2 from 2 to 5
+move 4 from 9 to 8
+move 2 from 1 to 5
+move 11 from 6 to 1
+move 14 from 2 to 6
+move 2 from 4 to 3
+move 1 from 2 to 9
+move 3 from 2 to 9
+move 20 from 6 to 5
+move 2 from 4 to 2
+move 4 from 9 to 1
+move 8 from 8 to 9
+move 1 from 6 to 9
+move 14 from 5 to 2
+move 10 from 2 to 7
+move 7 from 9 to 6
+move 1 from 6 to 8
+move 6 from 2 to 6
+move 1 from 2 to 5
+move 1 from 3 to 5
+move 9 from 6 to 3
+move 1 from 5 to 2
+move 9 from 7 to 3
+move 12 from 3 to 2
+move 9 from 5 to 9
+move 1 from 8 to 6
+move 3 from 3 to 5
+move 1 from 7 to 6
+move 14 from 2 to 6
+move 3 from 9 to 7
+move 6 from 1 to 2
+move 5 from 1 to 8
+move 10 from 6 to 9
+move 4 from 5 to 6
+move 3 from 2 to 4
+move 9 from 9 to 7
+move 1 from 8 to 7
+move 3 from 9 to 6
+move 3 from 3 to 7
+move 1 from 5 to 1
+move 15 from 7 to 1
+move 2 from 8 to 5
+move 2 from 5 to 4
+move 1 from 7 to 4
+move 1 from 3 to 1
+move 15 from 6 to 7
+move 2 from 4 to 9
+move 3 from 4 to 7
+move 18 from 1 to 6
+move 1 from 8 to 9
+move 6 from 9 to 7
+move 3 from 6 to 8
+move 1 from 1 to 2
+move 2 from 9 to 5
+move 2 from 2 to 9
+move 16 from 6 to 3
+move 15 from 3 to 7
+move 2 from 8 to 4
+move 1 from 3 to 7
+move 3 from 4 to 9
+move 2 from 1 to 9
+move 26 from 7 to 4
+move 1 from 2 to 1
+move 7 from 9 to 8
+move 1 from 2 to 5
+move 2 from 5 to 2
+move 8 from 7 to 5
+move 1 from 7 to 3
+move 1 from 3 to 9
+move 2 from 2 to 7
+move 1 from 6 to 4
+move 4 from 8 to 9
+move 1 from 1 to 3
+move 1 from 5 to 6
+move 2 from 5 to 7
+move 17 from 4 to 9
+move 6 from 4 to 9
+move 1 from 3 to 4
+move 6 from 7 to 9
+move 3 from 5 to 6
+move 2 from 7 to 9
+move 4 from 8 to 9
+move 4 from 6 to 4
+move 8 from 4 to 6
+move 1 from 8 to 4
+move 3 from 5 to 2
+move 2 from 4 to 3
+move 1 from 7 to 9
+move 2 from 3 to 5
+move 4 from 6 to 9
+move 1 from 6 to 1
+move 36 from 9 to 4
+move 2 from 5 to 3
+move 3 from 2 to 1
+move 3 from 1 to 4
+move 14 from 4 to 1
+move 1 from 8 to 5
+move 4 from 1 to 3
+move 5 from 9 to 5
+move 2 from 5 to 8
+move 1 from 8 to 9
+move 4 from 9 to 6
+move 3 from 5 to 8
+move 1 from 5 to 6
+move 2 from 1 to 6
+move 2 from 9 to 7
+move 6 from 6 to 4
+move 1 from 1 to 3
+move 29 from 4 to 6
+move 7 from 3 to 4
+move 1 from 8 to 9
+move 3 from 1 to 6
+move 4 from 1 to 4
+move 1 from 8 to 4
+move 4 from 4 to 3
+move 15 from 6 to 8
+move 9 from 4 to 9
+move 1 from 7 to 9
+move 8 from 8 to 3
+move 3 from 6 to 7
+move 1 from 1 to 2
+move 4 from 7 to 6
+move 7 from 8 to 5
+move 1 from 8 to 4
+move 2 from 5 to 7
+move 1 from 2 to 4
+move 5 from 6 to 1
+move 4 from 3 to 2

2022/inputs/day6.txt

@@ -0,0 +1 @@
+qfmfhmhjmjggwbbvdvwvlvrrtsrsccwsslvlffjrrtprprjjvmmclmmghhddpvddclctcqtccgbgdbgdgsdgghqhtqtvvptvppwrwprpvrrrhpphththvhhrnnhnlnslnlhnhnhgnhnpnqqsmsgsllprlprrlzzqzffmzztctbtnbtthlttqvqcqmcmpcpbbczzbqbgghcghchhvwvllfrfnnbssfzsszpsplpglpprnpnfnbnhbnbtbzzvbvpbbhjjlzzbtbvbppczppbwppqwwnwlwccglgvgrgmmdwmwrmrppnfnhhhhqthqthqqrhrshhhqbhqqjgjvjllzvzbzhbbpttjsszvzqqtzzmbmddpldpdcdnccrmcrmmpwprplrrqssvddmpdmmwfwwlrljrrdsssmhsspnpffjggqllnzlnlhnnmddfrfpfbbvssjsrrznngcghgchcmhmrrrtzztjzzhchssslsmlmvvpwpqpjqjdddmsdmmtgtmgtglttfbbgrrcprrqffmmjnjttcmczzgbzggthhsttpggrmmgwwnpnqnqvnqvqppmlpmlpmpjpljljmmtpptfppfrppfdpfdppddmdttgzgzzdbzdzhzhnnsqssvmvbbpjjzwwvnwvvzmvzmzpmpttvrvccqddpgdppgmmthmthtggsfsbbvfbvfvhfvhvvpwpddqrqgqhghnnfmfbbwrbrgbgbvgbbdttffrddqbqpqzzmttlhhsqhsqhsqhhlplttpnpsstpthhpfhpfplprrgfrgffjppghgppghgdggjmmcgmccjvvsrvsrrwgrgmrrngrgttvbtbltthrthrttmfffjpfpssncnrngrrltrltlggjgcgllrzzllhwwjwrwgrgsrgrhrphrhhqwqsqmqlmqlmqmqrmrnnwnhwnhwhzwzjwwgbghhsjspszsznzfztfzfpzzlczztctsstctqtfqfqcfqqjrjccttmqqfpfdfnfwnffqbfbblpbpfpcfcwfccblbwwmqwqrrgprpccngnhghpppwmpplcppfrfjjgmmbzbhbcbzzgdgsdsvvqllzlppnfnlnlslsljlppcscqqfjjjwzwppfgfjjsvvsggjbjljpjpzjzrzjrzzfnfpnfpnfpnfnsnggmpggdllpmmrhhdqqppttgqqcsqsjsbjsjrsrqrbqqmbmcbmcbmbfmfvfqqdbdppmrprnrggmjjhnhbhdhbbfcbbcjjdhhwjwmjmssjswscswcwzccbgbqqmqgmmsdsjsbsdbsddvttjpppcqpcqcgqqslqsssczszrzvvrtvvjppswwhnnwlwtwhhwwzfwwpfpddlvvnvnnvlnntjtqjqjzzjttvvbqbhqbhbbbwnwhnwnppdbpdpvddrqdqjjlvlqqdfdhdjhdjdcjcrcjjggfmfvvfllvfvgglzllmhmzmdddfwddqjjqjfqfcfrrstrssptsstllrflfwwgswslwlbwbwjjvhvfvhfhffhsslwsllbnbblccbwwjqwqqdllrdrnrnffcbbqqpnqqdmdndtntvvrjvvsvmvgvnnmjlwgnjcwljgwnrwpqlztwrpmpgqtwlhrcwsrrhqhjhznrtpqfdnzbfqrzwslptdbdcnqvcllpjsfdvmzqwvzbpnmfcfcjnbmhtwhttjgtnczwctpdthhwmzvzrrgsnmbflgmszgsbvghbzgcmcmszgsbfmlmpbdspqlftmqrcjtmvgcrzznlfwjcbmddplsqrfflqnqfsldwhnncczdmfrrrsbjjqsdzrsgbdbwjbslfcqglsqfddhdsrcdrgqfqthgmfjvnfdfgdncfzpvqcpscnpmfgvqbfwszwzgmqvmcrdrwplfshdgqrchmccpqfznbmfvlhdpctlqgjslrwhjfjlmqfblgjrdlnzdtwlpwhnrhrcrpfwqpmjlgrdbgpbljntmbqlblqqqpgrnjtmjqvjpzvsqdpgtchmmwbhtmgcjqdplrtptqcvdjjpqdzsrcjhcwvdcghlwrdhtdfctmqfcjcqhcvvbzgsvlggcrdgqbtznwwmnbgsfrjprqgcmlswftlwpqqqvshdprldrsghmhrqvmqmvglbvzpvtrjbhcvhqmvdtcvsllznqzjmhpnlbhmlzthbwwhhvdtcdfdcdzhnbsrnqqjvzzsvfjhbsdlsbdlqjnlpnhfcjtdppzmphghltztzcdvzwbftbvwhvgmrllqfzrpbltptdtjjqtfwjfmczzgdvclqbsbftgtlhnhrrvbpvdltstdnhqvpvtjhmghptvsfnlspslmfsftzdrwljrgblgmcbmlszmhnlfdtmsrnjqwrfmsnfgpcqgzmlwppffrmbvhnlstfpgzwwmwffrqpdfvrspbczbrclwljgzfhpsrwwpdndfgjwbjtftnjrqvmtmzvjmtlmjhhptmgjvfrlzncmhnmpfcwpjbcpftqfzvmtldqhjpwvzrdnvnwnscgzslvfgjjpcvjshctmmpjbgdwtdjtlmztsbmwrjtmltnlsmwmjnpcgpprnfwcqdldbbqbfmdnvprzqwvntgzdbrsgdpgdjbcblmqpdphmwgvbgwlpblflphvjgjsjfshbjdftcqmsdnrzbgngcvddddjvrndhdcscqqswrnvslfrlvvncqjhzlbhdqhtrlvdsvjsbglhfzfphmzfmzqdvjqdwhjgfdwmzsdmbjzstjddfmfqjhmbdgdbvvhbqgstrzpvhpthhbwljczzrmvgsmbqvzdrmhvvjlmphzjfbmfqvwhtnrlfnfmqnnjvnwjswzshwgljmfjhrwbwgtpdqnqgqdzbssbjfbsgwmfzpfjdrtrnmsdffhnbgnrdlbjzfjrvtjgjgcvvzgllljrcrshczvpfqgnwnjjnhbwgvzwrptrgrdgtczjfzzndsqhqpmtqsvmcncfszsjllzzsjjmwgplpjwlhnhgbhctrttgzqbbcflzqvqgmhgdtlvfpbtncbwsjgnzpmbspcqzzwfplfprqlnbctwwrzpjtpfrmnpvnjrjppqrzjrcmggfmhrstzhmsjllcgjhwrbhcrvdvgmvjqqgmczlmhstmthzphlvrrvqmhjzzfzbhphstflhfjdlwqvzlsszctrdchwjssdfjjfzszlqdtwwthfjdqprpfftgdrpdhhcsdcpjbhdrgzwbgjspmffcmgcjnpmwsqwsvpfwzddlcpvlgpvctrssghndhvdmmmgndcjvhdjwttqphsjpgfbsdczmplfpwpzzjlbhrjptmsshfttnmhzdzmjctbltqjmfnpndqgwjzwdwrgdjdmcbtvjqwjngrtbfrwcttpdvcqtwqndznbchjqcqttrhjpjgwdbwzvwgmdsdfmpdwctvntvnsdmfnznfrsdcllpgpnstrrfrwrfrwnhbclnqhltrcdwqwzzldgbbtzmcvnbzmwcmntqpbscqrpzcjnbgbrzpcrcmdmdfsfgdpmgvwccqjrltrgfvjdgbhjndnmtnjjhzvghscdhnhflwplrqdzrnlnsvrtrdnphgqwjwqcjvtfdfshqdwbsvgrqbdlncjmhdmrlsvdnrhztznczzllsvpqlvwgqjvgvvwgrjcvtjvhrsgbdgvlmmtjbwrnftzphnqslcpggztgsdbjsbdtzwprsbcljpbwjhcrffnvtplcdlgmbtcgbllbdmwhwcllbqstnqqvdbcjrglwbmcfqvlvtpqncbspbphflvvrrsprlhqspfmqrsdtdlftsfzrqwdfffbhccvpfdtlptqzllfsbbrfnhjgwhlfcwmmjgjndcwfhdzvvvrzmwllthwsdmbbsrfrzmqnlnqnjnfpgfvrhsbzhjftmvzrzpqpmlcbnwmbssmvssmmqpvwnsjppdhmnhpntlvqmjnbmtvjnmtbpbzrcfhjfhvztnwrmthbswwthjddjmsdnjmzhhpjdllgscdrgmhfpljfzsmszqsqqgrznddhfmstzdcqpgztgwwqpvrghtmqlgdddlqqwwwtnpldbqtf

2022/inputs/day7.txt

@@ -0,0 +1,934 @@
+$ cd /
+$ ls
+dir bgmjrlz
+dir bhp
+dir cbcwz
+169838 fddw.bgw
+dir fvhmzqc
+dir hqmlnpn
+248637 jtwpn.lnr
+319470 lnmrrht.zbn
+99548 pqpslbtn
+dir rbztmqjn
+102720 rqpt
+dir vfrtt
+$ cd bgmjrlz
+$ ls
+dir dhqzgdl
+dir djtchhmw
+dir tvq
+$ cd dhqzgdl
+$ ls
+dir jjshzrhd
+dir jlfz
+dir vqvvwgt
+dir zcqbt
+$ cd jjshzrhd
+$ ls
+dir jjshzrhd
+$ cd jjshzrhd
+$ ls
+81645 gfhfplmm
+$ cd ..
+$ cd ..
+$ cd jlfz
+$ ls
+dir hgzg
+189290 wgdffcr
+$ cd hgzg
+$ ls
+121740 vmmcdr
+$ cd ..
+$ cd ..
+$ cd vqvvwgt
+$ ls
+142209 djtchhmw.tgr
+$ cd ..
+$ cd zcqbt
+$ ls
+204760 mlsfnt
+$ cd ..
+$ cd ..
+$ cd djtchhmw
+$ ls
+287664 cgjmd.vrb
+307590 ghrntg.zsw
+$ cd ..
+$ cd tvq
+$ ls
+270869 jjshzrhd.lzb
+$ cd ..
+$ cd ..
+$ cd bhp
+$ ls
+231648 gmj.srn
+260008 hrtbfww.gts
+287048 jgqjszsr
+dir mps
+dir sjt
+dir zvbwsw
+$ cd mps
+$ ls
+dir djtchhmw
+153066 dnpv.vff
+185096 slpz.phm
+$ cd djtchhmw
+$ ls
+310736 ddhfvv.lzl
+234532 hghrcqfd.hpn
+276144 hrtbfww.gts
+$ cd ..
+$ cd ..
+$ cd sjt
+$ ls
+dir btgrv
+dir csn
+dir ddhfvv
+dir dfbjz
+dir djtchhmw
+dir qdms
+45629 qgj.jjs
+dir rdqbdtdh
+235189 wcrsz.ccc
+$ cd btgrv
+$ ls
+dir rnhq
+$ cd rnhq
+$ ls
+205285 vmmcdr
+$ cd ..
+$ cd ..
+$ cd csn
+$ ls
+234221 nhw.rml
+$ cd ..
+$ cd ddhfvv
+$ ls
+dir glbf
+56038 gvbzwds.cff
+dir qtc
+308363 rdzj.sqr
+dir vlrs
+dir vzhm
+dir wwghpsds
+287177 zznmdh.nhn
+$ cd glbf
+$ ls
+128210 btgrv.zqp
+205284 dnt.jrd
+135774 pmnbbb
+$ cd ..
+$ cd qtc
+$ ls
+292185 zsqz
+$ cd ..
+$ cd vlrs
+$ ls
+dir btgrv
+dir jlbjlzzs
+dir lnqcr
+$ cd btgrv
+$ ls
+277089 bcpdvwqs.dmw
+262922 hghrcqfd.hpn
+$ cd ..
+$ cd jlbjlzzs
+$ ls
+95245 vmmcdr
+$ cd ..
+$ cd lnqcr
+$ ls
+172326 qsrcb.fpd
+$ cd ..
+$ cd ..
+$ cd vzhm
+$ ls
+203623 fvhmzqc.dmm
+$ cd ..
+$ cd wwghpsds
+$ ls
+60280 vmmcdr
+$ cd ..
+$ cd ..
+$ cd dfbjz
+$ ls
+262505 blc.lhp
+24423 ddhfvv
+296606 fvhmzqc.ptz
+98808 hghrcqfd.hpn
+$ cd ..
+$ cd djtchhmw
+$ ls
+278654 hghrcqfd.hpn
+$ cd ..
+$ cd qdms
+$ ls
+dir djtchhmw
+154536 jjshzrhd.stf
+dir sgh
+$ cd djtchhmw
+$ ls
+246903 hghrcqfd.hpn
+$ cd ..
+$ cd sgh
+$ ls
+265535 btgrv.frs
+299957 hffpl.qzw
+$ cd ..
+$ cd ..
+$ cd rdqbdtdh
+$ ls
+dir btgrv
+dir djtchhmw
+182591 jjshzrhd
+22987 jjshzrhd.qwp
+dir jmc
+185957 mthrpb.qmm
+$ cd btgrv
+$ ls
+dir btgrv
+9328 ddhfvv
+7652 hghrcqfd.hpn
+53498 wgdffcr
+$ cd btgrv
+$ ls
+dir czgrcv
+171099 hrtbfww.gts
+22232 lqwvnz
+dir mfhbd
+193089 scld.jpg
+75876 vmmcdr
+226425 wgdffcr
+$ cd czgrcv
+$ ls
+276374 lfctmv.dbp
+268014 mpvb.rfg
+180548 wgdffcr
+$ cd ..
+$ cd mfhbd
+$ ls
+67713 fvhmzqc.llz
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd djtchhmw
+$ ls
+3290 ddhfvv.vsl
+dir fvhmzqc
+168684 hghrcqfd.hpn
+dir jmqwll
+80802 qmfhm.gtf
+282318 rzn.chg
+148018 wgdffcr
+$ cd fvhmzqc
+$ ls
+dir bjpvn
+87780 hghrcqfd.hpn
+209282 vtv.wbt
+$ cd bjpvn
+$ ls
+126911 rcq
+$ cd ..
+$ cd ..
+$ cd jmqwll
+$ ls
+240811 vmmcdr
+$ cd ..
+$ cd ..
+$ cd jmc
+$ ls
+320199 btgrv.ntz
+11100 jwcvvfnb.grd
+145758 wgdffcr
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd zvbwsw
+$ ls
+dir fvhmzqc
+$ cd fvhmzqc
+$ ls
+169680 rlnvr.bwd
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd cbcwz
+$ ls
+82379 hrtbfww.gts
+$ cd ..
+$ cd fvhmzqc
+$ ls
+140571 hrtbfww.gts
+dir hvnt
+dir jbc
+dir mzzfssn
+dir npdccs
+dir wrzzq
+$ cd hvnt
+$ ls
+102394 hrtbfww.gts
+29683 hsgstppl
+dir rmrc
+134244 rsjrj.gbr
+231284 wqhndr.hlr
+207733 wtjz
+$ cd rmrc
+$ ls
+dir btgrv
+259148 hrjqjdqq.tvm
+$ cd btgrv
+$ ls
+240410 tqv
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd jbc
+$ ls
+140479 fvhmzqc.pvm
+$ cd ..
+$ cd mzzfssn
+$ ls
+78226 brtbv.gtp
+61906 btgrv
+168944 nqll
+111153 qmrsgwh
+$ cd ..
+$ cd npdccs
+$ ls
+65889 wfpvp.wsg
+$ cd ..
+$ cd wrzzq
+$ ls
+dir btgrv
+82867 djtchhmw
+dir dzzv
+dir lpz
+dir mqqlhnvh
+$ cd btgrv
+$ ls
+dir dppvz
+dir glmtpswv
+dir qfgqfzm
+dir qhb
+$ cd dppvz
+$ ls
+296857 hrtbfww.gts
+11272 jjshzrhd
+$ cd ..
+$ cd glmtpswv
+$ ls
+268244 cgntm.tcf
+dir jjshzrhd
+dir lqnb
+128070 tzctcnq.gwr
+110659 wnrblpbs.wqf
+$ cd jjshzrhd
+$ ls
+dir cwdwh
+173945 fzstdt.pdn
+224834 nnvnqrh.zld
+dir tfzp
+$ cd cwdwh
+$ ls
+dir btgrv
+315172 ddhfvv.vdc
+109603 dsqjgv
+dir hnp
+284882 mnsb.cdh
+247067 qtntt.jhn
+200809 tvtbfn
+$ cd btgrv
+$ ls
+74389 ndfzlfzf.lth
+$ cd ..
+$ cd hnp
+$ ls
+242535 ddhfvv
+256542 nslg.qcc
+143475 wbzjdrhd.gbr
+$ cd ..
+$ cd ..
+$ cd tfzp
+$ ls
+46652 djtchhmw
+167857 rtqcpsd
+$ cd ..
+$ cd ..
+$ cd lqnb
+$ ls
+186160 ddhfvv
+287136 wgdffcr
+$ cd ..
+$ cd ..
+$ cd qfgqfzm
+$ ls
+212359 btgrv.hjj
+$ cd ..
+$ cd qhb
+$ ls
+15584 djtchhmw
+$ cd ..
+$ cd ..
+$ cd dzzv
+$ ls
+141830 hrtbfww.gts
+$ cd ..
+$ cd lpz
+$ ls
+dir djtchhmw
+14679 jjshzrhd
+dir pbcrz
+$ cd djtchhmw
+$ ls
+dir fvhmzqc
+250329 hnhzlwrm.bqp
+dir jjshzrhd
+262196 jjshzrhd.gnz
+dir qpc
+dir svmmjlr
+dir tddmdzd
+236002 vmmcdr
+101814 vwpnztc
+$ cd fvhmzqc
+$ ls
+44990 fvhmzqc.ngb
+235856 hlbhsz
+219184 hrtbfww.gts
+$ cd ..
+$ cd jjshzrhd
+$ ls
+190311 clbzz
+$ cd ..
+$ cd qpc
+$ ls
+217404 jjshzrhd.nwv
+142286 pgjgsh.sdd
+$ cd ..
+$ cd svmmjlr
+$ ls
+82636 cvbhsch
+287045 fvhmzqc.rjh
+48607 vmmcdr
+$ cd ..
+$ cd tddmdzd
+$ ls
+dir cjfjmjnh
+dir fjwwn
+7777 hghrcqfd.hpn
+220410 tgfqgcc.ngd
+$ cd cjfjmjnh
+$ ls
+dir gcs
+$ cd gcs
+$ ls
+210998 nzzjl
+79843 zltwtmnv
+$ cd ..
+$ cd ..
+$ cd fjwwn
+$ ls
+17068 rht.hhw
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd pbcrz
+$ ls
+41401 tzqjl.bhn
+144639 zqght
+$ cd ..
+$ cd ..
+$ cd mqqlhnvh
+$ ls
+dir bmcqbq
+dir cqh
+dir jjshzrhd
+dir lbvrm
+dir lwmbvsjj
+dir rrcnhbn
+67325 tfcl.npl
+$ cd bmcqbq
+$ ls
+dir bwjhtvcm
+dir wzmg
+$ cd bwjhtvcm
+$ ls
+156583 qdjmmdq
+$ cd ..
+$ cd wzmg
+$ ls
+dir ddhfvv
+dir tlhc
+$ cd ddhfvv
+$ ls
+dir jjshzrhd
+$ cd jjshzrhd
+$ ls
+202499 ddhfvv
+$ cd ..
+$ cd ..
+$ cd tlhc
+$ ls
+dir lbpmtft
+$ cd lbpmtft
+$ ls
+43196 lthlvv
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd cqh
+$ ls
+dir btgrv
+35483 djtchhmw
+318895 sfqdbd
+62778 twdpcn.rzg
+dir vwdqmtwf
+$ cd btgrv
+$ ls
+dir hrbjmbf
+dir npffrswd
+$ cd hrbjmbf
+$ ls
+196766 crw.dht
+$ cd ..
+$ cd npffrswd
+$ ls
+dir jjshzrhd
+$ cd jjshzrhd
+$ ls
+161401 dsqqh.pqg
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd vwdqmtwf
+$ ls
+299604 qrdcnbt.wmh
+$ cd ..
+$ cd ..
+$ cd jjshzrhd
+$ ls
+62584 dzfvzrf.tmc
+255105 hwfh.tfd
+$ cd ..
+$ cd lbvrm
+$ ls
+dir btgrv
+dir pvnbdwjj
+21599 tjfd.jzf
+315782 wgdffcr
+dir znz
+$ cd btgrv
+$ ls
+dir qjbhvdm
+$ cd qjbhvdm
+$ ls
+115711 mjhcwn
+$ cd ..
+$ cd ..
+$ cd pvnbdwjj
+$ ls
+156828 hrtbfww.gts
+dir jjshzrhd
+208415 vmmcdr
+$ cd jjshzrhd
+$ ls
+131751 hwfh.tfd
+$ cd ..
+$ cd ..
+$ cd znz
+$ ls
+dir ddhfvv
+150828 gpcpnwj.fzv
+119331 hrtbfww.gts
+263285 nntqssp.hqg
+dir pwtbr
+236806 vmmcdr
+$ cd ddhfvv
+$ ls
+265355 ddhfvv.bpb
+$ cd ..
+$ cd pwtbr
+$ ls
+212361 jjshzrhd.nmh
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd lwmbvsjj
+$ ls
+275264 bvbq.rdf
+dir ddhfvv
+257257 fsql
+210469 jmvchpn
+57627 lrnhn
+270278 vmmcdr
+dir vrqmtl
+$ cd ddhfvv
+$ ls
+244640 nhdztzsg
+$ cd ..
+$ cd vrqmtl
+$ ls
+123207 btgrv.qsg
+152242 qsqt
+259711 scvzvns.vvh
+$ cd ..
+$ cd ..
+$ cd rrcnhbn
+$ ls
+dir jjshzrhd
+$ cd jjshzrhd
+$ ls
+63581 btgrv.pbj
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd hqmlnpn
+$ ls
+dir djtchhmw
+dir dlqjbqbr
+240226 fdmchrth
+dir fvhmzqc
+39519 hvtvcdv
+140559 hwfh.tfd
+243880 lvcwjnzb.ptf
+dir nppp
+162576 rmqmd.wdt
+dir rscgvrdt
+dir sdcbr
+$ cd djtchhmw
+$ ls
+33004 ddhfvv.ghw
+$ cd ..
+$ cd dlqjbqbr
+$ ls
+dir fvhmzqc
+dir jjshzrhd
+dir ncwldt
+dir wfw
+$ cd fvhmzqc
+$ ls
+dir brfl
+dir ccnlzrb
+dir cjtl
+dir dfvt
+123279 fvhmzqc.qfp
+dir ppshjv
+dir smprwhmg
+$ cd brfl
+$ ls
+291222 djtchhmw.grj
+102020 hghrcqfd.hpn
+197538 hwfh.tfd
+82351 qqq.cqf
+254314 ztthgs
+$ cd ..
+$ cd ccnlzrb
+$ ls
+dir rzmdmq
+$ cd rzmdmq
+$ ls
+265088 rqtm.zmv
+$ cd ..
+$ cd ..
+$ cd cjtl
+$ ls
+107485 djtchhmw.phc
+$ cd ..
+$ cd dfvt
+$ ls
+114165 dts.rlc
+201057 frljlqzr.clp
+$ cd ..
+$ cd ppshjv
+$ ls
+305733 djtchhmw.ntn
+$ cd ..
+$ cd smprwhmg
+$ ls
+76792 ddhfvv
+$ cd ..
+$ cd ..
+$ cd jjshzrhd
+$ ls
+19740 fvhmzqc
+dir lqgsw
+dir lsmccpj
+17490 mlzznrc.mst
+$ cd lqgsw
+$ ls
+297439 crqjmhrb.grs
+$ cd ..
+$ cd lsmccpj
+$ ls
+89758 btgrv.cpt
+49280 ddhfvv.drt
+dir gclrgz
+dir gnrztgj
+275064 jjshzrhd.jzv
+98597 nbscl.wvs
+225844 vmmcdr
+$ cd gclrgz
+$ ls
+63611 djtchhmw.vfn
+156340 gbhsz
+$ cd ..
+$ cd gnrztgj
+$ ls
+23195 btgrv
+287815 fhthsd
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ncwldt
+$ ls
+70881 vmwllc.fbf
+$ cd ..
+$ cd wfw
+$ ls
+309325 ddhfvv.pqm
+201372 fvhmzqc.rfl
+143184 hghrcqfd.hpn
+51325 vlq.wgr
+$ cd ..
+$ cd ..
+$ cd fvhmzqc
+$ ls
+234497 ddhfvv.wlg
+dir fvhmzqc
+197961 fzbsr
+dir jsfbvwb
+$ cd fvhmzqc
+$ ls
+208299 bgpncvh.jhl
+$ cd ..
+$ cd jsfbvwb
+$ ls
+175184 ddhfvv.tpq
+85214 djtchhmw.btf
+2012 ttbpmsg.mlb
+$ cd ..
+$ cd ..
+$ cd nppp
+$ ls
+223933 wgdffcr
+$ cd ..
+$ cd rscgvrdt
+$ ls
+207388 glgbngv.lcd
+$ cd ..
+$ cd sdcbr
+$ ls
+277288 btgrv.phv
+49684 ddhfvv
+195222 dntzwh
+dir frcj
+206408 gfttdcnq
+147023 hrtbfww.gts
+dir tcwpvrr
+$ cd frcj
+$ ls
+37309 ctpjbmh
+54747 hwfh.tfd
+151065 phvllpq.gvh
+$ cd ..
+$ cd tcwpvrr
+$ ls
+63500 chsgcw.frm
+dir ltwvvrv
+113779 mgdqjg
+177222 vzgpfpq.qln
+$ cd ltwvvrv
+$ ls
+102472 vmmcdr
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd rbztmqjn
+$ ls
+216106 fnzwzdb.wrc
+$ cd ..
+$ cd vfrtt
+$ ls
+dir ddhfvv
+dir ftrqt
+dir fvhmzqc
+186081 hwfh.tfd
+dir jjshzrhd
+dir mzfq
+dir nhzz
+dir zblsznh
+$ cd ddhfvv
+$ ls
+28659 glfpm.hnp
+274896 hrtbfww.gts
+dir lwblgr
+dir qmc
+dir thwccb
+dir tmlwvtmc
+228636 zrn.ftn
+$ cd lwblgr
+$ ls
+237410 djtchhmw.fjz
+209100 hghrcqfd.hpn
+317411 nsgtmddt.jvj
+30033 pbhc.blz
+8818 pwf.vjv
+$ cd ..
+$ cd qmc
+$ ls
+249328 cwftvdws
+41124 pwmzz
+99884 qbvpslt
+$ cd ..
+$ cd thwccb
+$ ls
+dir ddhfvv
+$ cd ddhfvv
+$ ls
+49107 fvhmzqc.slp
+$ cd ..
+$ cd ..
+$ cd tmlwvtmc
+$ ls
+dir djtchhmw
+115288 gfdzqrb
+248419 hrtbfww.gts
+$ cd djtchhmw
+$ ls
+14211 qffwlmvm.fhp
+dir tzbd
+67495 wwttgflg.rcl
+$ cd tzbd
+$ ls
+278463 btgrv.ldc
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ftrqt
+$ ls
+95545 ddhfvv
+180375 hwfh.tfd
+$ cd ..
+$ cd fvhmzqc
+$ ls
+161318 gtwj
+$ cd ..
+$ cd jjshzrhd
+$ ls
+91626 prmznc.gwp
+dir wltvrv
+$ cd wltvrv
+$ ls
+299813 hrtbfww.gts
+$ cd ..
+$ cd ..
+$ cd mzfq
+$ ls
+101218 jjshzrhd.nwz
+200289 njwfbc.bhb
+$ cd ..
+$ cd nhzz
+$ ls
+225881 hwfh.tfd
+210133 mlb.wrt
+$ cd ..
+$ cd zblsznh
+$ ls
+dir fvhmzqc
+214252 hrtbfww.gts
+250855 qbjphgwn.vvj
+dir tdpv
+173807 wgdffcr
+$ cd fvhmzqc
+$ ls
+dir djtchhmw
+dir fsqdcwr
+dir jjshzrhd
+dir zljhz
+$ cd djtchhmw
+$ ls
+dir sdrjlqqm
+$ cd sdrjlqqm
+$ ls
+91244 fvhmzqc
+$ cd ..
+$ cd ..
+$ cd fsqdcwr
+$ ls
+dir ddhfvv
+dir nhmhgzt
+dir pdhbd
+$ cd ddhfvv
+$ ls
+199548 qwc
+$ cd ..
+$ cd nhmhgzt
+$ ls
+106393 ddhfvv.sjg
+$ cd ..
+$ cd pdhbd
+$ ls
+207023 hngmj.qls
+$ cd ..
+$ cd ..
+$ cd jjshzrhd
+$ ls
+84955 vmmcdr
+$ cd ..
+$ cd zljhz
+$ ls
+dir dmqmc
+dir jnlgsgn
+dir mhtmt
+dir mqtmpht
+$ cd dmqmc
+$ ls
+dir djtchhmw
+$ cd djtchhmw
+$ ls
+166369 hrtbfww.gts
+$ cd ..
+$ cd ..
+$ cd jnlgsgn
+$ ls
+289581 vrbqvt.bgn
+$ cd ..
+$ cd mhtmt
+$ ls
+182104 hrtbfww.gts
+285446 spgtjm.lhj
+$ cd ..
+$ cd mqtmpht
+$ ls
+179017 bgfgtqr.snr
+dir czqj
+dir gdc
+104624 jjshzrhd
+314246 mhvzncnt.vjd
+$ cd czqj
+$ ls
+69494 hft.fsp
+$ cd ..
+$ cd gdc
+$ ls
+84423 bhqnfj.cts
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd ..
+$ cd tdpv
+$ ls
+dir frgfgd
+dir sggm
+274423 zzfsmdf
+$ cd frgfgd
+$ ls
+205662 vmmcdr
+$ cd ..
+$ cd sggm
+$ ls
+260269 wzpjsjnq.nvt

2022/inputs/day8.txt

@@ -0,0 +1,99 @@
+020110220332333020110144320304042020444223003535441353331002333431100300241023221210123003331021020
+002120010112022233203323334422340102033151553341235324543343233301202102130210343113312320222102020
+000000000301021002423224442341031145215244543444223314545524515335404222310244314423023331200102012
+011200302010212334422213334343335452314532352111122533515334412241512412033340322004232020212310011
+110111200102310120411101020333232255345143342245212323552344535253214434143032323213200301101020121
+122001020113011314043121413025543341512335111452355331355351515421515411500421204113413212021112302
+011210211003201420103123304513544114145311452334355144111521441452154223512022101102111221311323311
+011030200312240341224434214241313322323544154242345656634321531531424124544551344224331443202111303
+031023120224010220144244342511241334331166432443322363352643453525244443222142533014331212133113031
+331033331100013013431114214253543323143222523423236646456363626622312534521454454123324132323233200
+313320023430241044213221132131122135436564345625426422255326234363243521151144414344130023210131130
+002203011410101343345413454143416333665335233566235623536644652644522345535525153521230411343303211
+022030323311323124542521154345356626352343324652424464566645425223224521453553252234321033403323130
+331222243010032043452454232565665256426536435254566436633323343652534544214412242551144312310221231
+231133233004211422411531255443363333555345434532475762623642433466363266634413551244254134333243030
+020231113200002214145443133533534653326664654474363645366343345466265644554325342415122332200024311
+311032340032414323451542554464466352256347635357637447736577667463426532442564245132242343241314212
+210342413212232542421452232234546643373633347344743377376553465333423522425436534352355150302110320
+012302042023135125251364365232626547463576733637455663764376436734352545425434331543241124042312202
+304042410233125532432523224245663443763753734647533535565636563665334542556665554245524241400402122
+100324144335411111343624365526556753335435457754653754663647544353454443256623466532421524442220212
+004310002315421423634565264237567445665436743333467647547754434765353667542365233361541321530411122
+340100133133254351662534562377644656735477678648447854646765556636735646456562322345353223545130204
+223422234555541234336653556365464346366386775667444744567758637737757667635354324626442355153142402
+301202352352311332364654446567354376644665887886878854847858588356564773766244445222614543212440041
+121010254322255546522625235356663453785775455846758588786788567566653645763532436352663334521520342
+223123122512444365553626454767563488464886467858877655766685458675437556363673526236645213411512224
+003314511142456453664565476333555654845565878476575468776548666885476777366354622652365442341232330
+100434351354142623236353735657745766665557455465675844665578767675874476556574642555262344222545124
+310035122251134332246455666547787878577677667587668567788744875844888844364453536232254344234442004
+332355524421462334544344655646458867688886798865795569865997666688465755335745555656646243433122421
+212252432545222565265377376368574784887787696558698987968675547855656555445333366624445325141553342
+113535121253534442546646364347455675758878676575695576785998796454646647555637657565266546254424513
+023531155256556443573534665476784478579889966685965558767695667786588646763565366352565623135242132
+332235311465633455637577656876574774599858977857599877979855878694546488485435736564352255345534352
+423312331346353345545646578646466549968669789766955768696578957665488458568376747735452426221223133
+042131555255526335474354376567744577697576655686887997959968659596857774864465577464334245541411144
+314335533542324633457667677854784879668896688676989899996875778858675674784535777333543532331142411
+342431321343652634443346854886679789759856968779866777899677797959996774647753365556465426225312415
+443122331352464374355445874586585857875568898788666678776787986756859447544446666763365552244452322
+434332122456323647344556476668759666569568769987679766689798887678765548587477474536465533643451422
+012515214225433447464677777487776597697976998888987789798887796967785955887765466437333665342324523
+151212435544622335634548655777875966867886867777679699887698988956977857868655457465635544364542154
+425332155643342656676678888575989888788767888899689899798688796666757955465858667777362363434424542
+531532414223243445466348848575895777968779899997887798776667989655588765447757447347342252524115215
+155245334655555376575664568856876978978787888977789987998877778796686666588544843473375333466131323
+442223263655353573545578848875879796997899897789887987979686977788898887848487563664644353624212355
+532342436423523433743374566649565796978689677778887988977986779775985585775684847364464225436344143
+144131162643455446377457566657777998676869667898877798979888978868889578745676553337663625625354412
+212531125562654464546354657756555595879978788779777999979988869895856856488587466676673534564554215
+515521136425625643733788668547967896969879989899779977888986996776697776777887634766746536654352314
+533115456346557773554457648785576555967877979777897997977979879979889786544548474557775226255314122
+432554142445363766476368787846679896977899887779797978979969889696765986666844737665565256236231155
+125253442625345476646468778468579567787976888987879797899978977695756855477657433457362446432521533
+451335344244435635354545558745856999567779868887799878899867977959975677866558447464563253543641554
+412221312464362643575387865576575778679997969899879799897898997777656968646646747476434353234412443
+132123436534443354553586484485777568678779897878779989966877968659558598445764456573762542646254544
+024143156436353736354736885476858987768978898698789976987668878886568974574565737457544455543452243
+413135313643263775675578866878568599957868689889887898688888897699957964455656556464353643525222353
+151155234625524455454576866886566769799886776697778986968676996687578554546778475347663665445441542
+225335432336665664467554464786765996688599897886876679899878795577796866847588643664352344525425543
+231314414363454365656445447648785668665699968677877867679686575989979554888874435546345632362455211
+215225154624264466667536475884866766856799777898688869799678789658958655666655664763723652345235254
+035354151466424636347656474544888889966575676978876877797665689589954588444647355553546242434541533
+001253252266442433343367457848868577696576876956987767987878766766685545864636355333223636351531525
+432114153244234344474473336455665467595685659677769775776598955788485844764764774633253355345153344
+440231335123622442356777766866685464699576999777998779679677676798556674878735743562224245652132511
+321533313113424533355576556587855784598797699998756887876998858868457756543476743664332364153212141
+003415211213442534357575744467674686668987887956977567898997789587764784753377657636326255155213240
+224445525333436434526743474634674544887785577959758998579798555487687877644644777665225554533252422
+114025431113445462556535777346657775747764689775588768859877487468477864653336547436625221413353402
+444431445545324552322733365535555774656466544687955795855665775645668663457547655566226341423452434
+410445115125126462226236353755455888548674587788447578688475766447586446763443644432535242233435244
+124340412535436432636663557555763744747854587474866557668648548584743443577534342355356535325312231
+200313132541126432532542747437536486654767558545587875558487658465577773437664544545354413212211212
+101333454545223643623655465756576356785656755457885765456674785763465474656725224222541315314114031
+131233142323341366245232435554365765545574774767785475776848668453355554474332533326544433554514201
+321411402434455156645353526473756763444567846554465464446465455445745336435566265254512531525210112
+030131034355454454644464565464475577344753366858566476585577545346763733342656446563454444451042420
+123233024345514531322525463344645673755773347575544437475656346736346777342352464432215452454013411
+014322323421235432556233655455544546633674634474456664346664375533773475562242423541545331424443423
+103044012005453352356343445634325645434337637364655565435774676736733553262634342435541343244030000
+320224321434222311444445623462256346445463567453434633465443337646352226626622452524224345304403330
+212420324020443535541356556336654222753455556557453353546474577342535554563532343321131244211234443
+122201202000423112251512562424625443344753367744337643545467743645523543344535431154212330403302410
+302200224224202341324112146243633653523426575646533673677763345633345645554351214352331400423031333
+123001320330302415435532414224224226352235334353577574436324344226425624263133551342153034141032032
+213131040401103044255424155325562642646633364323565455323646566426224245451451423431324433130343033
+231211142003310021532152553311226325626362465244625533422332633634454451545253314415220400420413203
+312320130422410131322514243524545532465435666446335525623552365342455442353243151122403024303312021
+133332233112042420435241253424143243654366264342464546256332442465235435334432132240241304411322221
+333302213333240222002452421142454145262355663455246362444253326353144344554554324413300122011222021
+202310030210410440001115535553444131333333663342464256255352255253344353414423520402213424030101331
+020120023231001430421410113431542415212332151336254445313532121145524443121220343020012020230032230
+210023323121322121303302233233245321224455333332343322323215223451525532222223304043001030230132022
+002222021003231011234340303045243412535411232132142332533521354111141433134004443142111110122121100
+022122131333022231003311233440122445251415343142141523345254553214425533033042143220401300010213100
+122110132221332212341431023220242412121544355542132225542445544553234342030402442141111321103231211
+122021200131211021314010312001241211235253115315252213451111223452204220130001212341202130012001221

2022/tests/day1.txt

@@ -0,0 +1,14 @@
+1000
+2000
+3000
+
+4000
+
+5000
+6000
+
+7000
+8000
+9000
+
+10000

2022/tests/day10.txt

@@ -0,0 +1,146 @@
+addx 15
+addx -11
+addx 6
+addx -3
+addx 5
+addx -1
+addx -8
+addx 13
+addx 4
+noop
+addx -1
+addx 5
+addx -1
+addx 5
+addx -1
+addx 5
+addx -1
+addx 5
+addx -1
+addx -35
+addx 1
+addx 24
+addx -19
+addx 1
+addx 16
+addx -11
+noop
+noop
+addx 21
+addx -15
+noop
+noop
+addx -3
+addx 9
+addx 1
+addx -3
+addx 8
+addx 1
+addx 5
+noop
+noop
+noop
+noop
+noop
+addx -36
+noop
+addx 1
+addx 7
+noop
+noop
+noop
+addx 2
+addx 6
+noop
+noop
+noop
+noop
+noop
+addx 1
+noop
+noop
+addx 7
+addx 1
+noop
+addx -13
+addx 13
+addx 7
+noop
+addx 1
+addx -33
+noop
+noop
+noop
+addx 2
+noop
+noop
+noop
+addx 8
+noop
+addx -1
+addx 2
+addx 1
+noop
+addx 17
+addx -9
+addx 1
+addx 1
+addx -3
+addx 11
+noop
+noop
+addx 1
+noop
+addx 1
+noop
+noop
+addx -13
+addx -19
+addx 1
+addx 3
+addx 26
+addx -30
+addx 12
+addx -1
+addx 3
+addx 1
+noop
+noop
+noop
+addx -9
+addx 18
+addx 1
+addx 2
+noop
+noop
+addx 9
+noop
+noop
+noop
+addx -1
+addx 2
+addx -37
+addx 1
+addx 3
+noop
+addx 15
+addx -21
+addx 22
+addx -6
+addx 1
+noop
+addx 2
+addx 1
+noop
+addx -10
+noop
+noop
+addx 20
+addx 1
+addx 2
+addx 2
+addx -6
+addx -11
+noop
+noop
+noop

2022/tests/day11.txt

@@ -0,0 +1,27 @@
+Monkey 0:
+  Starting items: 79, 98
+  Operation: new = old * 19
+  Test: divisible by 23
+    If true: throw to monkey 2
+    If false: throw to monkey 3
+
+Monkey 1:
+  Starting items: 54, 65, 75, 74
+  Operation: new = old + 6
+  Test: divisible by 19
+    If true: throw to monkey 2
+    If false: throw to monkey 0
+
+Monkey 2:
+  Starting items: 79, 60, 97
+  Operation: new = old * old
+  Test: divisible by 13
+    If true: throw to monkey 1
+    If false: throw to monkey 3
+
+Monkey 3:
+  Starting items: 74
+  Operation: new = old + 3
+  Test: divisible by 17
+    If true: throw to monkey 0
+    If false: throw to monkey 1

2022/tests/day12.txt

@@ -0,0 +1,5 @@
+Sabqponm
+abcryxxl
+accszExk
+acctuvwj
+abdefghi

2022/tests/day13.txt

@@ -0,0 +1,23 @@
+[1,1,3,1,1]
+[1,1,5,1,1]
+
+[[1],[2,3,4]]
+[[1],4]
+
+[9]
+[[8,7,6]]
+
+[[4,4],4,4]
+[[4,4],4,4,4]
+
+[7,7,7,7]
+[7,7,7]
+
+[]
+[3]
+
+[[[]]]
+[[]]
+
+[1,[2,[3,[4,[5,6,7]]]],8,9]
+[1,[2,[3,[4,[5,6,0]]]],8,9]

2022/tests/day14.txt

@@ -0,0 +1,2 @@
+498,4 -> 498,6 -> 496,6
+503,4 -> 502,4 -> 502,9 -> 494,9

2022/tests/day15.txt

@@ -0,0 +1,14 @@
+Sensor at x=2, y=18: closest beacon is at x=-2, y=15
+Sensor at x=9, y=16: closest beacon is at x=10, y=16
+Sensor at x=13, y=2: closest beacon is at x=15, y=3
+Sensor at x=12, y=14: closest beacon is at x=10, y=16
+Sensor at x=10, y=20: closest beacon is at x=10, y=16
+Sensor at x=14, y=17: closest beacon is at x=10, y=16
+Sensor at x=8, y=7: closest beacon is at x=2, y=10
+Sensor at x=2, y=0: closest beacon is at x=2, y=10
+Sensor at x=0, y=11: closest beacon is at x=2, y=10
+Sensor at x=20, y=14: closest beacon is at x=25, y=17
+Sensor at x=17, y=20: closest beacon is at x=21, y=22
+Sensor at x=16, y=7: closest beacon is at x=15, y=3
+Sensor at x=14, y=3: closest beacon is at x=15, y=3
+Sensor at x=20, y=1: closest beacon is at x=15, y=3

2022/tests/day16.txt

@@ -0,0 +1,10 @@
+Valve AA has flow rate=0; tunnels lead to valves DD, II, BB
+Valve BB has flow rate=13; tunnels lead to valves CC, AA
+Valve CC has flow rate=2; tunnels lead to valves DD, BB
+Valve DD has flow rate=20; tunnels lead to valves CC, AA, EE
+Valve EE has flow rate=3; tunnels lead to valves FF, DD
+Valve FF has flow rate=0; tunnels lead to valves EE, GG
+Valve GG has flow rate=0; tunnels lead to valves FF, HH
+Valve HH has flow rate=22; tunnel leads to valve GG
+Valve II has flow rate=0; tunnels lead to valves AA, JJ
+Valve JJ has flow rate=21; tunnel leads to valve II

2022/tests/day17.txt

@@ -0,0 +1 @@
+>>><<><>><<<>><>>><<<>>><<<><<<>><>><<>>

2022/tests/day18.txt

@@ -0,0 +1,13 @@
+2,2,2
+1,2,2
+3,2,2
+2,1,2
+2,3,2
+2,2,1
+2,2,3
+2,2,4
+2,2,6
+1,2,5
+3,2,5
+2,1,5
+2,3,5

2022/tests/day19.txt

@@ -0,0 +1,2 @@
+Blueprint 1: Each ore robot costs 4 ore. Each clay robot costs 2 ore. Each obsidian robot costs 3 ore and 14 clay. Each geode robot costs 2 ore and 7 obsidian.
+Blueprint 2: Each ore robot costs 2 ore. Each clay robot costs 3 ore. Each obsidian robot costs 3 ore and 8 clay. Each geode robot costs 3 ore and 12 obsidian.

2022/tests/day2.txt

@@ -0,0 +1,3 @@
+A Y
+B X
+C Z

2022/tests/day20.txt

@@ -0,0 +1,7 @@
+1
+2
+-3
+3
+-2
+0
+4

2022/tests/day21.txt

@@ -0,0 +1,15 @@
+root: pppw + sjmn
+dbpl: 5
+cczh: sllz + lgvd
+zczc: 2
+ptdq: humn - dvpt
+dvpt: 3
+lfqf: 4
+humn: 5
+ljgn: 2
+sjmn: drzm * dbpl
+sllz: 4
+pppw: cczh / lfqf
+lgvd: ljgn * ptdq
+drzm: hmdt - zczc
+hmdt: 32

2022/tests/day22.txt

@@ -0,0 +1,14 @@
+        ...#
+        .#..
+        #...
+        ....
+...#.......#
+........#...
+..#....#....
+..........#.
+        ...#....
+        .....#..
+        .#......
+        ......#.
+
+10R5L5R10L4R5L5

2022/tests/day23.txt

@@ -0,0 +1,7 @@
+....#..
+..###.#
+#...#.#
+.#...##
+#.###..
+##.#.##
+.#..#..

2022/tests/day24.txt

@@ -0,0 +1,6 @@
+#.######
+#>>.<^<#
+#.<..<<#
+#>v.><>#
+#<^v^^>#
+######.#

2022/tests/day25.txt

@@ -0,0 +1,13 @@
+1=-0-2
+12111
+2=0=
+21
+2=01
+111
+20012
+112
+1=-1=
+1-12
+12
+1=
+122

2022/tests/day3.txt

@@ -0,0 +1,6 @@
+vJrwpWtwJgWrhcsFMMfFFhFp
+jqHRNqRjqzjGDLGLrsFMfFZSrLrFZsSL
+PmmdzqPrVvPwwTWBwg
+wMqvLMZHhHMvwLHjbvcjnnSBnvTQFn
+ttgJtRGJQctTZtZT
+CrZsJsPPZsGzwwsLwLmpwMDw

2022/tests/day4.txt

@@ -0,0 +1,6 @@
+2-4,6-8
+2-3,4-5
+5-7,7-9
+2-8,3-7
+6-6,4-6
+2-6,4-8

2022/tests/day5.txt

@@ -0,0 +1,9 @@
+    [D]
+[N] [C]
+[Z] [M] [P]
+ 1   2   3
+
+move 1 from 2 to 1
+move 3 from 1 to 3
+move 2 from 2 to 1
+move 1 from 1 to 2

2022/tests/day6.txt

@@ -0,0 +1 @@
+mjqjpqmgbljsphdztnvjfqwrcgsmlb

2022/tests/day7.txt

@@ -0,0 +1,23 @@
+$ cd /
+$ ls
+dir a
+14848514 b.txt
+8504156 c.dat
+dir d
+$ cd a
+$ ls
+dir e
+29116 f
+2557 g
+62596 h.lst
+$ cd e
+$ ls
+584 i
+$ cd ..
+$ cd ..
+$ cd d
+$ ls
+4060174 j
+8033020 d.log
+5626152 d.ext
+7214296 k

2022/tests/day8.txt

@@ -0,0 +1,5 @@
+30373
+25512
+65332
+33549
+35390

2022/tests/day9.txt

@@ -0,0 +1,8 @@
+R 4
+U 4
+L 3
+D 1
+R 4
+D 1
+L 5
+R 2

2023/day1.py

@@ -0,0 +1,45 @@
+import sys
+
+lines = sys.stdin.read().splitlines()
+
+lookups_1 = {str(d): d for d in range(1, 10)}
+lookups_2 = lookups_1 | {
+    d: i + 1
+    for i, d in enumerate(
+        (
+            "one",
+            "two",
+            "three",
+            "four",
+            "five",
+            "six",
+            "seven",
+            "eight",
+            "nine",
+        )
+    )
+}
+
+
+def find_values(lookups: dict[str, int]) -> list[int]:
+    values: list[int] = []
+
+    for line in filter(bool, lines):
+        first_digit = min(
+            lookups,
+            key=lambda lookup: index
+            if (index := line.find(lookup)) >= 0
+            else len(line),
+        )
+        last_digit = max(
+            lookups,
+            key=lambda lookup: index if (index := line.rfind(lookup)) >= 0 else -1,
+        )
+
+        values.append(10 * lookups[first_digit] + lookups[last_digit])
+
+    return values
+
+
+print(f"answer 1 is {sum(find_values(lookups_1))}")
+print(f"answer 2 is {sum(find_values(lookups_2))}")

2023/day10.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day11.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day12.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day13.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day14.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day15.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day16.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day17.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day18.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day19.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day2.py

@@ -0,0 +1,45 @@
+import operator
+import sys
+from functools import reduce
+from typing import Literal, TypeAlias, cast
+
+CubeType: TypeAlias = Literal["red", "blue", "green"]
+
+MAX_CUBES: dict[CubeType, int] = {"red": 12, "green": 13, "blue": 14}
+
+# parse games
+lines = sys.stdin.read().splitlines()
+games: dict[int, list[dict[CubeType, int]]] = {}
+for line in filter(bool, lines):
+    id_part, sets_part = line.split(":")
+
+    games[int(id_part.split(" ")[-1])] = [
+        {
+            cast(CubeType, s[1]): int(s[0])
+            for cube_draw in cube_set_s.strip().split(", ")
+            if (s := cube_draw.split(" "))
+        }
+        for cube_set_s in sets_part.strip().split(";")
+    ]
+
+# part 1
+answer_1 = sum(
+    id
+    for id, set_of_cubes in games.items()
+    if all(
+        n_cubes <= MAX_CUBES[cube]
+        for cube_set in set_of_cubes
+        for cube, n_cubes in cube_set.items()
+    )
+)
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = sum(
+    reduce(
+        operator.mul,
+        (max(cube_set.get(cube, 0) for cube_set in set_of_cubes) for cube in MAX_CUBES),
+    )
+    for set_of_cubes in games.values()
+)
+print(f"answer 2 is {answer_2}")

2023/day20.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day21.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day22.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day23.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day24.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day25.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day3.py

@@ -0,0 +1,53 @@
+import string
+import sys
+from collections import defaultdict
+
+NOT_A_SYMBOL = "." + string.digits
+
+lines = sys.stdin.read().splitlines()
+
+values: list[int] = []
+gears: dict[tuple[int, int], list[int]] = defaultdict(list)
+
+for i, line in enumerate(lines):
+    j = 0
+    while j < len(line):
+        # skip everything until a digit is found (start of a number)
+        if line[j] not in string.digits:
+            j += 1
+            continue
+
+        # extract the range of the number and its value
+        k = j + 1
+        while k < len(line) and line[k] in string.digits:
+            k += 1
+
+        value = int(line[j:k])
+
+        # lookup around the number if there is a symbol - we go through the number
+        # itself but that should not matter since it only contains digits
+        found = False
+        for i2 in range(max(0, i - 1), min(i + 1, len(lines) - 1) + 1):
+            for j2 in range(max(0, j - 1), min(k, len(line) - 1) + 1):
+                assert i2 >= 0 and i2 < len(lines)
+                assert j2 >= 0 and j2 < len(line)
+
+                if lines[i2][j2] not in NOT_A_SYMBOL:
+                    found = True
+
+                    if lines[i2][j2] == "*":
+                        gears[i2, j2].append(value)
+
+        if found:
+            values.append(value)
+
+        # continue starting from the end of the number
+        j = k
+
+# part 1
+answer_1 = sum(values)
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = sum(v1 * v2 for v1, v2 in filter(lambda vs: len(vs) == 2, gears.values()))
+print(f"answer 2 is {answer_2}")

2023/day4.py

@@ -0,0 +1,41 @@
+import sys
+from dataclasses import dataclass
+
+
+@dataclass(frozen=True)
+class Card:
+    id: int
+    numbers: list[int]
+    values: list[int]
+
+
+lines = sys.stdin.read().splitlines()
+
+cards: list[Card] = []
+for line in lines:
+    id_part, e_part = line.split(":")
+    numbers_s, values_s = e_part.split("|")
+    cards.append(
+        Card(
+            id=int(id_part.split()[1]),
+            numbers=[int(v.strip()) for v in numbers_s.strip().split()],
+            values=[int(v.strip()) for v in values_s.strip().split()],
+        )
+    )
+
+winnings = [sum(1 for n in card.values if n in card.numbers) for card in cards]
+
+# part 1
+answer_1 = sum(2 ** (winning - 1) for winning in winnings if winning > 0)
+print(f"answer 1 is {answer_1}")
+
+# part 2
+card2cards = {i: list(range(i + 1, i + w + 1)) for i, w in enumerate(winnings)}
+card2values = {i: 0 for i in range(len(cards))}
+
+for i in range(len(cards)):
+    card2values[i] += 1
+    for j in card2cards[i]:
+        card2values[j] += card2values[i]
+
+print(f"answer 2 is {sum(card2values.values())}")

2023/day5.py

@@ -0,0 +1,129 @@
+import sys
+from typing import Sequence
+
+MAP_ORDER = [
+    "seed",
+    "soil",
+    "fertilizer",
+    "water",
+    "light",
+    "temperature",
+    "humidity",
+    "location",
+]
+
+lines = sys.stdin.read().splitlines()
+
+# mappings from one category to another, each list contains
+# ranges stored as (source, target, length), ordered by start and
+# completed to have no "hole"
+maps: dict[tuple[str, str], list[tuple[int, int, int]]] = {}
+
+# parsing
+index = 2
+while index < len(lines):
+    p1, _, p2 = lines[index].split()[0].split("-")
+
+    # extract the existing ranges from the file - we store as (source, target, length)
+    # whereas the file is in order (target, source, length)
+    index += 1
+    values: list[tuple[int, int, int]] = []
+    while index < len(lines) and lines[index]:
+        n1, n2, n3 = lines[index].split()
+        values.append((int(n2), int(n1), int(n3)))
+        index += 1
+
+    # sort by source value
+    values.sort()
+
+    # add a 'fake' interval starting at 0 if missing
+    if values[0][0] != 0:
+        values.insert(0, (0, 0, values[0][0]))
+
+    # fill gaps between intervals
+    for i in range(len(values) - 1):
+        next_start = values[i + 1][0]
+        end = values[i][0] + values[i][2]
+        if next_start != end:
+            values.insert(
+                i + 1,
+                (end, end, next_start - end),
+            )
+
+    # add an interval covering values up to at least 2**32 at the end
+    last_start, _, last_length = values[-1]
+    values.append((last_start + last_length, last_start + last_length, 2**32))
+
+    assert all(v1[0] + v1[2] == v2[0] for v1, v2 in zip(values[:-1], values[1:]))
+    assert values[0][0] == 0
+    assert values[-1][0] + values[-1][-1] >= 2**32
+
+    maps[p1, p2] = values
+    index += 1
+
+
+def find_range(
+    values: tuple[int, int], map: list[tuple[int, int, int]]
+) -> list[tuple[int, int]]:
+    """
+    Given an input range, use the given mapping to find the corresponding list of
+    ranges in the target domain.
+    """
+    r_start, r_length = values
+    ranges: list[tuple[int, int]] = []
+
+    # find index of the first and last intervals in map that overlaps the input
+    # interval
+    index_start, index_end = -1, -1
+
+    for index_start, (start, _, length) in enumerate(map):
+        if start <= r_start and start + length > r_start:
+            break
+
+    for index_end, (start, _, length) in enumerate(
+        map[index_start:], start=index_start
+    ):
+        if r_start + r_length >= start and r_start + r_length < start + length:
+            break
+
+    assert index_start >= 0 and index_end >= 0
+
+    # special case if one interval contains everything
+    if index_start == index_end:
+        start, target, length = map[index_start]
+        ranges.append((target + r_start - start, r_length))
+    else:
+        # add the start interval part
+        start, target, length = map[index_start]
+        ranges.append((target + r_start - start, start + length - r_start))
+
+        # add all intervals between the first and last (excluding both)
+        index = index_start + 1
+        while index < index_end:
+            start, target, length = map[index]
+            ranges.append((target, length))
+            index += 1
+
+        # add the last interval
+        start, target, length = map[index_end]
+        ranges.append((target, r_start + r_length - start))
+
+    return ranges
+
+
+def find_location_ranges(seeds: Sequence[tuple[int, int]]) -> Sequence[tuple[int, int]]:
+    for map1, map2 in zip(MAP_ORDER[:-1], MAP_ORDER[1:]):
+        seeds = [s2 for s1 in seeds for s2 in find_range(s1, maps[map1, map2])]
+    return seeds
+
+
+# part 1 - use find_range() with range of length 1
+seeds_p1 = [(int(s), 1) for s in lines[0].split(":")[1].strip().split()]
+answer_1 = min(start for start, _ in find_location_ranges(seeds_p1))
+print(f"answer 1 is {answer_1}")
+
+# # part 2
+parts = lines[0].split(":")[1].strip().split()
+seeds_p2 = [(int(s), int(e)) for s, e in zip(parts[::2], parts[1::2])]
+answer_2 = min(start for start, _ in find_location_ranges(seeds_p2))
+print(f"answer 2 is {answer_2}")

2023/day6.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day7.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")

2023/day8.py

@@ -0,0 +1,13 @@
+import sys
+from collections import defaultdict
+from dataclasses import dataclass
+
+lines = sys.stdin.read().splitlines()
+
+# part 1
+answer_1 = ...
+print(f"answer 1 is {answer_1}")
+
+# part 2
+answer_2 = ...
+print(f"answer 2 is {answer_2}")