2025 day 11 in Python

2025/day11/README.md

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+# Day 11: Python
+
+Straightforward. Uses `networkx` because I thought it would be very helpful but it only really saves
+me from writing a topological sort algorithm in the end.
+
+```console
+$ uv run ./solve.py input.txt
+Part 1: secret
+Part 2: secret
+```

2025/day11/pyproject.toml

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+[project]
+name = "solve"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "networkx>=3.6.1",
+]

2025/day11/sample.txt

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+aaa: you hhh
+you: bbb ccc
+bbb: ddd eee
+ccc: ddd eee fff
+ddd: ggg
+eee: out
+fff: out
+ggg: out
+hhh: ccc fff iii
+iii: out

2025/day11/sample2.txt

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+svr: aaa bbb
+aaa: fft
+fft: ccc
+bbb: tty
+tty: ccc
+ccc: ddd eee
+ddd: hub
+hub: fff
+eee: dac
+dac: fff
+fff: ggg hhh
+ggg: out
+hhh: out
+you: out

2025/day11/solve.py

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+#!/usr/bin/env python3
+
+from collections import defaultdict
+import fileinput
+from typing import Iterable
+
+import networkx as nx
+
+def parse_graph() -> nx.Graph:
+    graph = nx.DiGraph()
+
+    for line in fileinput.input():
+        source, rem = line.split(": ")
+        
+        for sink in rem.strip().split(" "):
+            graph.add_edge(source, sink)
+
+    return graph
+
+def count(gen: Iterable) -> int:
+    return sum(1 for _ in gen)
+
+def main() -> None:
+    graph = parse_graph()
+
+    # Observation: graph is a DAG, so one needs to go in front of the other. We can do this in three
+    # steps:
+    # svr → closest(dac, fft) -> furthest(dac,fft)
+    rank = {
+        node: rank
+        for rank, node in enumerate(nx.topological_sort(graph))
+    }
+
+    rev_rank = {rank: node for node, rank in rank.items()}
+
+    if rank["dac"] > rank["fft"]:
+        closest = "fft"
+        furthest = "dac"
+    else:
+        closest = "dac"
+        furthest = "fft"
+
+    
+    def ranked_all_paths(source: str, dest: str) -> int:
+        counts = defaultdict(int)
+
+        counts[dest] = 1
+
+        for r in range(rank[dest], rank[source], -1):
+            node = rev_rank[r]
+            if node not in counts:
+                continue
+
+            for u, _ in graph.in_edges(node):
+                counts[u] += counts[node]
+
+        return counts[source]
+
+    assert nx.has_path(graph, closest, furthest)
+
+    print("Part 1", ranked_all_paths("you", "out"))
+
+    first = ranked_all_paths("svr", closest)
+    second = ranked_all_paths(closest, furthest)
+    third = ranked_all_paths(furthest, "out")
+    print("Part 2:", first * second * third)
+
+
+if __name__ == "__main__":
+    main()