Inititate AOC 2022 in python

2022-python/README.md

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+# Advent of Code 2022
+
+Solutions for #aoc2022 in Python 3 (3.13.4).
+
+Programming setup:
+
+- Lenovo Thinkpad T14
+- OpenSUSE Tumbleweed with labwc
+- Helix editor
+- Vivaldi
+- Foot
+
+## Help scripts
+
+Display all solved puzzles:
+
+    python aoc.py
+
+To bootstrap a new puzzle (creates `input/<day_no>.txt` and `output/day_<day_no>.py`):
+
+    python aoc.py <day_no> new
+
+Manually copy the puzzle input from https://adventofcode.com and paste it in `input/<day_no>.txt`
+to start coding.
+
+    wl-paste > input/<day_no>.txt
+
+Solve separate puzzle (replace `XX` with the puzzle number):
+
+    python -m output.day_XX
+
+Solve separate puzzle using stdin (replace `XX` with the puzzle number):
+
+    wl-paste | python -m output.day_XX
+    cat tmpfile | python -m output.day_XX
+
+Execute separate puzzle on file save (replace `XX` with the puzzle number):
+
+    ls output/*.py | entr -c -s 'wlpaste | python -m output.day_XX'
+    ls output/*.py | entr -c -s 'cat tmpfile | python -m output.day_XX'
+    ls output/*.py | entr -c -r python -m output.day_XX
+
+(requires `entr` and `wl-paste`, Mac users can instead use `pbpaste`. If you
+prefer X at Linux, use `xclip -selection clipboard -o`).
+
+To lint files:
+
+    ls output/*.py | entr -r -c flake8 output --ignore=E741,E501,E203

2022-python/aoc.py

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+import sys
+from pathlib import Path
+
+
+def headline(n):
+    """Print day number and name, followed by a ruler. Used by the answer decorator"""
+    print(f"\nDay {int(n)} - https://adventofcode.com/{year}/day/{int(n)}\n")
+
+
+year = 2022
+
+try:
+    _, day_no, *name = sys.argv
+except ValueError:
+    day_no = None
+    name = None
+
+Path("./input").mkdir(parents=True, exist_ok=True)
+Path("./output").mkdir(parents=True, exist_ok=True)
+
+if day_no and name:
+    name = " ".join(name)
+    padded_no = day_no.zfill(2)
+    with open("output/day_{}.py".format(padded_no), "w") as s:
+        s.write(
+            f"""
+import re
+from collections import deque, Counter, defaultdict
+from heapq import heappop, heappush
+from itertools import compress, combinations, chain, permutations
+
+from output import matrix, D, DD, ADJ, ints, mhd, mdbg, vdbg, cw, ccw, bk
+
+
+def solve(data):
+    p1 = None
+    p2 = None
+    return p1, p2
+
+
+if __name__ == "__main__":
+    import os
+
+    # use dummy data
+    inp = \"\"\"
+        replace me
+    \"\"\".strip()
+
+    # uncomment to instead use stdin
+    # import sys; inp = sys.stdin.read().strip()
+
+    # uncomment to use AoC provided puzzle input
+    # with open("./input/{padded_no}.txt", "r") as f:
+    #     inp = f.read().strip()
+
+    # uncomment to do initial data processing shared by part 1-2
+    p1, p2 = solve(inp)
+
+    print(p1)
+    os.system(f"echo {{p1}} | wl-copy")
+    # print(p2)
+    # os.system(f"echo {{p2}} | wl-copy")
+
+    # uncomment and replace 0 with actual output to refactor code
+    # and ensure nonbreaking changes
+    # assert p1 == 0
+    # assert p2 == 0
+""".strip()
+            + "\n"
+        )
+    exit(0)
+
+print(
+    f"\n\033[95m\033[1mAdvent of Code {year}\033[0m"
+    "\n###################"
+    "\n\n\033[96mby Anders Englöf Ytterström\033[0m"
+)
+
+
+stars = 0
+for i in [str(n).zfill(2) for n in range(1, 26)]:
+    if not day_no or day_no.zfill(2) == i:
+        try:
+            day = __import__(
+                "output.day_{}".format(i),
+                globals(),
+                locals(),
+                ["solve"],
+                0,
+            )
+            with open(f"./input/{i}.txt", "r") as f:
+                data = f.read().strip()
+            headline(i)
+            try:
+                data = day.presolve(data)
+            except AttributeError:
+                pass
+            try:
+                p1, p2 = day.solve(data)
+            except AttributeError:
+                pass
+            if p1:
+                print(f"    \033[92m1)\033[0m {p1}")
+                stars += 1
+            if p2:
+                print(f"    \033[92m2)\033[0m {p2}")
+                stars += 1
+        except IOError:
+            pass
+        except ImportError:
+            pass
+if not day_no:
+    print(f"\nStars: {stars}")
+    print("".join("*" if n < stars else "•" for n in range(50)))
+print("")

2022-python/output/__init__.py

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+import re
+
+# Directions/Adjacents for 2D matrices, in the order UP, RIGHT, DOWN, LEFT
+D = [
+    (-1, 0),
+    (0, 1),
+    (1, 0),
+    (0, -1),
+]
+
+Di = [
+    (-1, -1),
+    (-1, 1),
+    (1, -1),
+    (1, 1),
+]
+
+# Directions for 2D matrices, as a dict with keys U, R, D, L
+DD = {
+    "U": (-1, 0),
+    "R": (0, 1),
+    "D": (1, 0),
+    "L": (0, -1),
+}
+
+DDa = {
+    "^": (-1, 0),
+    ">": (0, 1),
+    "v": (1, 0),
+    "<": (0, -1),
+}
+
+# Adjacent relative positions including diagonals for 2D matrices, in the order NW, N, NE, W, E, SW, S, SE
+ADJ = [
+    (-1, -1),
+    (-1, 0),
+    (1, -1),
+    (0, -1),
+    (0, 1),
+    (1, 1),
+    (1, 0),
+    (1, -1),
+]
+
+
+def ints(s):
+    """Extract all integers from a string"""
+    return [int(n) for n in re.findall(r"\d+", s)]
+
+
+def sints(s):
+    """Extract all signed integers from a string"""
+    return [int(n) for n in re.findall(r"-?\d+", s)]
+
+
+def mhd(a, b):
+    """Calculates the Manhattan distance between 2 positions in the format (y, x) or (x, y)"""
+    ar, ac = a
+    br, bc = b
+    return abs(ar - br) + abs(ac - bc)
+
+
+def matrix(d):
+    """Transform a string into an iterable matrix. Returns the matrix, row count and col count"""
+    m = [tuple(r) for r in d.split()]
+    return m, len(m), len(m[0])
+
+
+def mdbg(m):
+    """Print-debug a matrix"""
+    for r in m:
+        print("".join(r))
+
+
+def vdbg(seen, h, w):
+    """Print-debug visited positions of a matrix"""
+    for r in range(h):
+        print("".join(["#" if (r, c) in seen else " " for c in range(w)]))
+
+
+def cw(y, x):
+    """Flip a (y, x) direction counterwise: U->R, R->D, D->L, L->U.
+
+    >>> cw(-1, 0)
+    (0, 1)
+    >>> cw(0, 1)
+    (1, 0)
+    >>> cw(1, 0)
+    (0, -1)
+    >>> cw(0, -1)
+    (-1, 0)
+    """
+    return (x, y) if y == 0 else (x, -y)
+
+
+def ccw(y, x):
+    """Flip a (y, x) direction counterwise: U->L, L->D, D->R, R->U.
+
+    >>> ccw(-1, 0)
+    (0, -1)
+    >>> ccw(0, -1)
+    (1, 0)
+    >>> ccw(1, 0)
+    (0, 1)
+    >>> ccw(0, 1)
+    (-1, 0)
+    """
+    return (x, y) if x == 0 else (-x, y)
+
+
+def bfs(S, E=None):
+    """BFS algorithm, equal weighted nodes"""
+    seen = set()
+    q = [(S, 0)]
+    g = {}  # graph, required to be provided at some point
+    while q:
+        m, w = q.pop(0)
+        if m in seen:
+            continue
+        seen.add(m)
+        # investigate here
+        for s in g[m]:
+            q.append((s, w + 1))
+    # return insights
+
+
+def mhd_search(r, c, R=20):
+    """returns all coords that are within R manhattan distance from (r,c)"""
+    p = set()
+    for d in range(1, R + 1):
+        p.add((r, c + d))
+        p.add((r, c - d))
+        p.add((r + d, c))
+        p.add((r - d, c))
+        for dd in range(d):
+            p.add((r - dd, c - d + dd))
+            p.add((r + dd, c - d + dd))
+            p.add((r - dd, c - dd + d))
+            p.add((r + dd, c - dd + d))
+    return p
+
+
+def dijkstras(grid, start, target):
+    """
+    1. Create an array that holds the distance of each vertex from the starting
+       vertex. Initially, set this distance to infinity for all vertices except
+       the starting vertex which should be set to 0.
+    2. Create a priority queue (heap) and insert the starting vertex with its
+       distance of 0.
+    3. While there are still vertices left in the priority queue, select the vertex
+       with the smallest recorded distance from the starting vertex and visit its
+       neighboring vertices.
+    4. For each neighboring vertex, check if it is visited already or not. If it
+       isn’t visited yet, calculate its tentative distance by adding its weight
+       to the smallest distance found so far for its parent/previous node
+       (starting vertex in case of first-level vertices).
+    5. If this tentative distance is smaller than previously recorded value
+       (if any), update it in our ‘distances’ array.
+    6. Finally, add this visited vertex with its updated distance to our priority
+       queue and repeat step-3 until we have reached our destination or exhausted
+       all nodes.
+    """
+    import heapq
+
+    target = max(grid)
+    seen = set()
+    queue = [(start, 0)]
+    while queue:
+        cost, pos, direction, steps = heapq.heappop(queue)
+        y, x = pos
+        dy, dx = direction
+
+        if pos == target:
+            return cost
+
+        if ((pos, "and stuff")) in seen:
+            continue
+
+        seen.add((pos, "and stuff"))
+
+        neighbors = []
+        for n in neighbors:
+            heapq.heappush(queue, ("stuffs"))
+
+    return -1
+
+
+def bk(graph, p, r=set(), x=set()):
+    """Bron-Kerbosch algoritm, no pivot: https://en.wikipedia.org/wiki/Bron%E2%80%93Kerbosch_algorithm"""
+    if not p and not x:
+        yield r
+    while p:
+        v = p.pop()
+        yield from bk(graph, p & set(graph[v]), r | {v}, x & graph[v])
+        x.add(v)