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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 |