| 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 |
| 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) |
| 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 |
|
|
| |
| 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 |
|
|
|
|
