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from concurrent.futures import ThreadPoolExecutor |
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import pandas as pd |
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from typing import List, Tuple |
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class TrieNode: |
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def __init__(self): |
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self.children = {} |
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self.end_of_word = False |
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class Trie: |
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def __init__(self): |
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self.root = TrieNode() |
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def insert(self, word): |
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node = self.root |
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for char in word: |
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if char not in node.children: |
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node.children[char] = TrieNode() |
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node = node.children[char] |
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node.end_of_word = True |
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def longest_common_prefix(self, word): |
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node = self.root |
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common_prefix_length = 0 |
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for char in word: |
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if char in node.children: |
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common_prefix_length += len(char) |
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node = node.children[char] |
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else: |
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break |
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return common_prefix_length |
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def calculate_length(value): |
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val = 0 |
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if isinstance(value, bool): |
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val = 4 |
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elif isinstance(value, (int, float)): |
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val = len(str(value)) |
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elif isinstance(value, str): |
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val = len(value) |
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else: |
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val = 0 |
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return val**2 |
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def evaluate_df_prefix_hit_cnt(df: pd.DataFrame) -> Tuple[int, int]: |
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""" |
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Function to evaluate the prefix hit count of a DataFrame |
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""" |
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def max_overlap(trie, row_string): |
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return min(len(row_string), trie.longest_common_prefix(row_string)) |
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trie = Trie() |
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total_prefix_hit_count = 0 |
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total_string_length = 0 |
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def process_row(index, row): |
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nonlocal total_string_length, total_prefix_hit_count |
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row_string = "".join(row.fillna("").astype(str).values) |
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total_string_length += len(row_string) |
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row_prefix_hit_count = max_overlap(trie, row_string) |
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trie.insert(row_string) |
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total_prefix_hit_count += row_prefix_hit_count |
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for index, row in df.iterrows(): |
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process_row(index, row) |
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total_prefix_hit_rate = total_prefix_hit_count / total_string_length if total_string_length > 0 else 0 |
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assert total_prefix_hit_count <= total_string_length |
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return total_prefix_hit_count, total_prefix_hit_rate * 100 |