Day 19 - Linen Layout

Megathread guidelines

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FAQ

  • @Acters
    link
    224 hours ago

    Python3

    Solver uses trie just like the other python solve here, I try to not look at solve threads until after it is solved. yet, I somehow got a solve that only takes ~7 ms. previously I would rebuild the trie every time and made it take ~55 ms.

    Code
    from collections import deque
    
    def profiler(method):
        from time import perf_counter_ns
        def wrapper_method(*args: any, **kwargs: any) -> any:
            start_time = perf_counter_ns()
            ret = method(*args, **kwargs)
            stop_time = perf_counter_ns() - start_time
            time_len = min(9, ((len(str(stop_time))-1)//3)*3)
            time_conversion = {9: 'seconds', 6: 'milliseconds', 3: 'microseconds', 0: 'nanoseconds'}
            print(f"Method {method.__name__} took : {stop_time / (10**time_len)} {time_conversion[time_len]}")
            return ret
    
        return wrapper_method
    
    def build_aho_corasick(towels):
        # Each node: edges dict, failure link, output (which towels end here)
        trie = [{'fail': 0, 'out': []}]
        
        # Build trie of towels
        for index, word in enumerate(towels):
            node = 0
            for char in word:
                if char not in trie[node]:
                    trie[node][char] = len(trie)
                    trie.append({'fail': 0, 'out': []})
                node = trie[node][char]
            trie[node]['out'].append(len(word))  # store length of matched towel
    
        # Build fail links (BFS)
        queue = deque()
        # Initialize depth-1 fail links
        for c in trie[0]:
            if c not in ('fail', 'out'):
                nxt = trie[0][c]
                trie[nxt]['fail'] = 0
                queue.append(nxt)
    
        # BFS build deeper fail links
        while queue:
            r = queue.popleft()
            for c in trie[r]:
                if c in ('fail', 'out'):
                    continue
                nxt = trie[r][c]
                queue.append(nxt)
                f = trie[r]['fail']
                while f and c not in trie[f]:
                    f = trie[f]['fail']
                trie[nxt]['fail'] = trie[f][c] if c in trie[f] else 0
                trie[nxt]['out'] += trie[trie[nxt]['fail']]['out']
        return trie
    
    def count_possible_designs_aho(trie, design):
        n = len(design)
        dp = [0] * (n + 1)
        dp[0] = 1
    
        # State in the trie automaton
        state = 0
    
        for i, char in enumerate(design, 1):
            # Advance in trie
            while state and char not in trie[state]:
                state = trie[state]['fail']
            if char in trie[state]:
                state = trie[state][char]
            else:
                state = 0
            
            # For every towel match that ends here:
            for length_matched in trie[state]['out']:
                dp[i] += dp[i - length_matched]
        
        return dp[n]
    
    @profiler
    def main(input_data):
        towels,desired_patterns = ( sorted(x.split(), key=len, reverse=True) for x in input_data.replace(',', ' ').split('\n\n') )
        part1 = 0
        part2 = 0
        
        # Build Aho-Corasick structure
        trie = build_aho_corasick(towels)
        
        for pattern in desired_patterns:
            count = count_possible_designs_aho(trie, pattern)
            if count:
                part1 += 1
                part2 += count
        
        return part1,part2
    
    if __name__ == "__main__":
        with open('input', 'r') as f:
            input_data = f.read().replace('\r', '').strip()
        result = main(input_data)
        print("Part 1:", result[0], "\nPart 2:", result[1])