from concurrent.futures import ThreadPoolExecutor import pandas as pd from typing import List, Tuple class TrieNode: def __init__(self): self.children = {} self.end_of_word = False class Trie: def __init__(self): self.root = TrieNode() def insert(self, word): node = self.root for char in word: if char not in node.children: node.children[char] = TrieNode() node = node.children[char] node.end_of_word = True def longest_common_prefix(self, word): node = self.root common_prefix_length = 0 for char in word: if char in node.children: common_prefix_length += len(char) node = node.children[char] else: break return common_prefix_length def calculate_length(value): val = 0 if isinstance(value, bool): val = 4 # length of 'True' or 'False' elif isinstance(value, (int, float)): val = len(str(value)) elif isinstance(value, str): val = len(value) else: val = 0 return val**2 def evaluate_df_prefix_hit_cnt(df: pd.DataFrame) -> Tuple[int, int]: """ Function to evaluate the prefix hit count of a DataFrame """ def max_overlap(trie, row_string): return min(len(row_string), trie.longest_common_prefix(row_string)) trie = Trie() total_prefix_hit_count = 0 total_string_length = 0 def process_row(index, row): nonlocal total_string_length, total_prefix_hit_count row_string = "".join(row.fillna("").astype(str).values) # No spaces between columns total_string_length += len(row_string) row_prefix_hit_count = max_overlap(trie, row_string) trie.insert(row_string) total_prefix_hit_count += row_prefix_hit_count # Actually iterate through the DataFrame rows for index, row in df.iterrows(): process_row(index, row) total_prefix_hit_rate = total_prefix_hit_count / total_string_length if total_string_length > 0 else 0 assert total_prefix_hit_count <= total_string_length return total_prefix_hit_count, total_prefix_hit_rate * 100