wieerwill/advent_of_code_2023
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

solce Part01 of Day05 in python

Browse Source
This commit is contained in:
WieErWill 2023-12-05 20:29:08 +01:00
parent 1e26ddb113
commit 31c742428f
4 changed files with 385 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

100
Day05/README.md Normal file
View File

@ -0,0 +1,100 @@
# Day 5: If You Give A Seed A Fertilizer
## Part One
You take the boat and find the gardener right where you were told he would be: managing a giant "garden" that looks more to you like a farm.
"A water source? Island Island is the water source!" You point out that Snow Island isn't receiving any water.
"Oh, we had to stop the water because we ran out of sand to filter it with! Can't make snow with dirty water. Don't worry, I'm sure we'll get more sand soon; we only turned off the water a few days... weeks... oh no." His face sinks into a look of horrified realization.
"I've been so busy making sure everyone here has food that I completely forgot to check why we stopped getting more sand! There's a ferry leaving soon that is headed over in that direction - it's much faster than your boat. Could you please go check it out?"
You barely have time to agree to this request when he brings up another. "While you wait for the ferry, maybe you can help us with our food production problem. The latest Island Island Almanac just arrived and we're having trouble making sense of it."
The almanac (your puzzle input) lists all of the seeds that need to be planted. It also lists what type of soil to use with each kind of seed, what type of fertilizer to use with each kind of soil, what type of water to use with each kind of fertilizer, and so on. Every type of seed, soil, fertilizer and so on is identified with a number, but numbers are reused by each category - that is, soil 123 and fertilizer 123 aren't necessarily related to each other.
For example:
```
seeds: 79 14 55 13
seed-to-soil map:
50 98 2
52 50 48
soil-to-fertilizer map:
0 15 37
37 52 2
39 0 15
fertilizer-to-water map:
49 53 8
0 11 42
42 0 7
57 7 4
water-to-light map:
88 18 7
18 25 70
light-to-temperature map:
45 77 23
81 45 19
68 64 13
temperature-to-humidity map:
0 69 1
1 0 69
humidity-to-location map:
60 56 37
56 93 4
```
The almanac starts by listing which seeds need to be planted: seeds 79, 14, 55, and 13.
The rest of the almanac contains a list of maps which describe how to convert numbers from a source category into numbers in a destination category. That is, the section that starts with seed-to-soil map: describes how to convert a seed number (the source) to a soil number (the destination). This lets the gardener and his team know which soil to use with which seeds, which water to use with which fertilizer, and so on.
Rather than list every source number and its corresponding destination number one by one, the maps describe entire ranges of numbers that can be converted. Each line within a map contains three numbers: the destination range start, the source range start, and the range length.
Consider again the example seed-to-soil map:
```
50 98 2
52 50 48
```
The first line has a destination range start of 50, a source range start of 98, and a range length of 2. This line means that the source range starts at 98 and contains two values: 98 and 99. The destination range is the same length, but it starts at 50, so its two values are 50 and 51. With this information, you know that seed number 98 corresponds to soil number 50 and that seed number 99 corresponds to soil number 51.
The second line means that the source range starts at 50 and contains 48 values: 50, 51, ..., 96, 97. This corresponds to a destination range starting at 52 and also containing 48 values: 52, 53, ..., 98, 99. So, seed number 53 corresponds to soil number 55.
Any source numbers that aren't mapped correspond to the same destination number. So, seed number 10 corresponds to soil number 10.
So, the entire list of seed numbers and their corresponding soil numbers looks like this:
```
seed soil
0 0
1 1
... ...
48 48
49 49
50 52
51 53
... ...
96 98
97 99
98 50
99 51
```
With this map, you can look up the soil number required for each initial seed number:
- Seed number 79 corresponds to soil number 81.
- Seed number 14 corresponds to soil number 14.
- Seed number 55 corresponds to soil number 57.
- Seed number 13 corresponds to soil number 13.
The gardener and his team want to get started as soon as possible, so they'd like to know the closest location that needs a seed. Using these maps, find the lowest location number that corresponds to any of the initial seeds. To do this, you'll need to convert each seed number through other categories until you can find its corresponding location number. In this example, the corresponding types are:
- Seed 79, soil 81, fertilizer 81, water 81, light 74, temperature 78, humidity 78, location 82.
- Seed 14, soil 14, fertilizer 53, water 49, light 42, temperature 42, humidity 43, location 43.
- Seed 55, soil 57, fertilizer 57, water 53, light 46, temperature 82, humidity 82, location 86.
- Seed 13, soil 13, fertilizer 52, water 41, light 34, temperature 34, humidity 35, location 35.
So, the lowest location number in this example is 35.
What is the lowest location number that corresponds to any of the initial seed numbers?
## Part Two

174
Day05/input.txt Normal file
View File

@ -0,0 +1,174 @@
seeds: 194657215 187012821 1093203236 6077151 44187305 148722449 2959577030 152281079 3400626717 198691716 1333399202 287624830 2657325069 35258407 1913289352 410917164 1005856673 850939 839895010 162018909
seed-to-soil map:
466206721 134904099 264145987
3226739510 2500159633 122177414
1107118949 4139510909 155456387
2314679916 2622337047 59899451
2642618541 1908002826 511067679
0 399050086 167531444
1262575336 2682236498 1052104580
3448620320 1415756771 259155097
302435543 566581530 163771178
3348916924 4039807513 99703396
3153686220 1674911868 73053290
3788293662 1747965158 160037668
3948331330 3734341078 305466435
2374579367 1228806725 186950046
2561529413 2419070505 81089128
167531444 0 134904099
3707775417 1148288480 80518245
4253797765 1107118949 41169531
soil-to-fertilizer map:
3913658055 3217667557 44136240
3043638173 1755409772 387575354
1214033686 3261803797 213545970
3431213527 3475349767 482444528
1994011339 2522356968 695310589
2689321928 1214033686 354316245
1427579656 2142985126 379371842
1806951498 1568349931 187059841
fertilizer-to-water map:
2553394045 2097964132 64191777
3153687517 3499502814 665965431
1104565830 789107360 151317021
4084493704 2165934452 60088979
981078109 1551802916 123487721
2935219151 4165468245 66838136
10669639 1277616562 132965227
839228347 1410581789 141221127
3942173186 2018304529 79659603
393057134 444333135 344145590
2617585822 2253442971 317633329
4237573988 3156387517 57393308
1341340213 99436946 344896189
143634866 1746717555 204406814
776848617 0 21473714
386359019 1270918447 6698115
4168968434 3430897260 68605554
2497629182 3375132397 55764863
3819652948 3213780825 9721342
1686236402 940424381 47687418
4021832789 4232306381 62660915
4144582683 2162155909 3778543
1733923820 1675290637 30520902
737202724 21473714 39645893
2018304529 2591683508 479324653
798322331 1705811539 40906016
0 1260248808 10669639
980449474 788478725 628635
3002057287 3223502167 151630230
3829374290 2226023431 27419540
348041680 61119607 38317339
3856793830 3071008161 85379356
1764444722 1073569161 186679647
4148361226 2571076300 20607208
1255882851 988111799 85457362
water-to-light map:
3143216572 2396957585 46085818
2930160319 3087666064 82806318
3012966637 3275730008 11481558
1791164654 628261856 251676187
1156959152 1008045214 174725983
3597974089 4238330323 56636973
2659665097 3287211566 62612544
489714994 0 304501033
2323644539 2017991146 71374674
2611713237 3480351863 47951860
4135255968 3931716786 159711328
1331685135 879938043 128107171
2396957585 2748883399 70018348
408833803 1297158141 80881191
1469631779 1182771197 103330914
4004728215 3349824110 58812180
1012078485 2008335392 9655754
3024448195 2932857654 118768377
192304632 2089365820 87451432
4063540395 3408636290 71715573
3823753472 2665304126 83579273
117236420 1933267180 75068212
2218325460 1378039332 105319079
2722277641 3170472382 32223106
1459792306 618379493 9839473
3225342423 3528303723 55360789
901528396 304501033 110507199
3654611062 2471800766 96107890
1012035595 628218966 42890
1118925110 1719748519 38034042
3907332745 2567908656 97395470
2466975933 3786979482 144737304
794216027 1612436150 107312369
2901402956 2443043403 28757363
0 415008232 117236420
3750718952 3202695488 73034520
3189302390 3051626031 36040033
3394659119 3583664512 203314970
2754500747 4091428114 146902209
2042840841 1757782561 175484619
3280703212 2818901747 113955907
1021734239 532244652 86134841
279756064 1483358411 129077739
1572962693 2176817252 218201961
1107869080 1286102111 11056030
light-to-temperature map:
1609050489 2309171782 372577802
2023682469 2836643763 897111138
834447570 143604042 411534753
428779503 1217157762 28824561
143604042 931982301 108906615
252510657 1040888916 176268846
3431278062 1484221851 471209429
1981628291 3733754901 42054178
4140073117 2681749584 154894179
1484221851 4170138658 124828638
3902487491 1955431280 237585626
457604064 555138795 376843506
3036948483 3775809079 394329579
2920793607 2193016906 116154876
temperature-to-humidity map:
1348484361 0 45849582
1394333943 726347262 166590764
1797084784 3346946555 119105515
1163891565 1265639794 165909682
2199751891 3274125222 72821333
4012454029 2231107899 181228118
1008425725 207338839 56688993
2322219090 3174539335 24543729
3987057737 3199083064 25396292
1560924707 45849582 62712410
3424140824 1837299459 190417072
2272573224 3224479356 27702302
2346762819 2412336017 518856401
329181964 1432789749 172164254
3783666369 2027716531 203391368
753484930 471406467 254940795
1916190299 2931192418 243346917
501346218 892938026 44760077
1329801247 1604954003 18683114
2865619220 3567337219 558521604
546106295 264027832 207378635
2300275526 3252181658 21943564
4193682147 3466052070 101285149
327941691 1431549476 1240273
0 937698103 327941691
2159537216 1797084784 40214675
3614557896 4125858823 169108473
1065114718 108561992 98776847
humidity-to-location map:
440744287 1133551978 536306564
4042633851 4000620330 37465866
977050851 1669858542 136276424
2136551597 4038086196 256881100
198620952 0 242123335
1113327275 242123335 891428643
4080099717 3802748040 197872290
2695699324 2136551597 1346934527
4277972007 3785752751 16995289
2393432697 3483486124 302266627
0 1806134966 198620952

78
Day05/python/solution1.py Normal file
View File

@ -0,0 +1,78 @@
import os
def map_seed_through_category(seed, line):
"""Maps a single seed through a category based on a mapping line."""
dest_start, source_start, range_length = map(int, line.split())
if source_start <= seed < source_start + range_length:
return dest_start + (seed - source_start)
return seed
def process_category(file, seeds):
"""Processes seeds through a single category based on the file lines."""
print(f"Starting category processing")
updated_seeds = [-1] * len(seeds) # Initialize with -1 to indicate unmapped seeds
for line in file:
line = line.strip()
print(f"Processing category line: {line}")
if not line or ':' in line: # End of the current category map
break
dest_start, source_start, range_length = map(int, line.split())
for i, seed in enumerate(seeds):
if updated_seeds[i] == -1 and source_start <= seed < source_start + range_length:
updated_seeds[i] = dest_start + (seed - source_start)
# For seeds that weren't mapped in this category, keep their original value
for i, seed in enumerate(updated_seeds):
if seed == -1:
updated_seeds[i] = seeds[i]
print(f"Seeds after category processing: {updated_seeds}")
return updated_seeds
def process_file(file_path, is_test=False):
"""Processes the file to find the lowest location number for the seeds."""
try:
with open(file_path, 'r') as file:
seeds = list(map(int, file.readline().split(':')[1].split()))
print(f"Initial Seeds: {seeds}")
while True:
line = file.readline()
if not line: # End of file
break
if ':' in line: # Start of a new category map
seeds = process_category(file, seeds)
lowest_location = min(seeds)
print(f"Lowest location from {file_path}: {lowest_location}")
return lowest_location
except FileNotFoundError:
print(f"Error: File '{file_path}' not found.")
except Exception as e:
print(f"An error occurred processing '{file_path}': {e}")
def test():
"""Run tests using the test.txt file."""
expected_result = 35 # Based on the given example
result = process_file('../test.txt')
assert result == expected_result, f"Test failed, expected 35 but got {result}"
print(f"Test passed: {result}")
def main():
"""Main function to process the input file and display results."""
try:
# Run tests first
test()
# Process actual input
result = process_file("../input.txt")
print(f"Total result from input.txt: {result}")
except Exception as e:
print(f"An error occurred: {e}")
if __name__ == "__main__":
main()

33
Day05/test.txt Normal file
View File

@ -0,0 +1,33 @@
seeds: 79 14 55 13
seed-to-soil map:
50 98 2
52 50 48
soil-to-fertilizer map:
0 15 37
37 52 2
39 0 15
fertilizer-to-water map:
49 53 8
0 11 42
42 0 7
57 7 4
water-to-light map:
88 18 7
18 25 70
light-to-temperature map:
45 77 23
81 45 19
68 64 13
temperature-to-humidity map:
0 69 1
1 0 69
humidity-to-location map:
60 56 37
56 93 4