import time import csv import random import sys from typing import List, Tuple, Optional, Any, Dict #лимит рекурсии sys.setrecursionlimit(20000) def ll_insert(head: Optional[Dict], name: str, phone: str) -> Dict: """Вставка в конец связного списка""" new_node = {'name': name, 'phone': phone, 'next': None} if head is None: return new_node current = head while current['next'] is not None: # Обновляем, если уже есть if current['name'] == name: current['phone'] = phone return head current = current['next'] if current['name'] == name: current['phone'] = phone else: current['next'] = new_node return head def ll_find(head: Optional[Dict], name: str) -> Optional[str]: """Поиск в связном списке""" current = head while current is not None: if current['name'] == name: return current['phone'] current = current['next'] return None def ll_delete(head: Optional[Dict], name: str) -> Optional[Dict]: """Удаление из связного списка""" if head is None: return None if head['name'] == name: return head['next'] current = head while current['next'] is not None: if current['next']['name'] == name: current['next'] = current['next']['next'] return head current = current['next'] return head def ll_list_all(head: Optional[Dict]) -> List[Tuple[str, str]]: """Сбор всех записей из связного списка с сортировкой""" records = [] current = head while current is not None: records.append((current['name'], current['phone'])) current = current['next'] def hash_function(name: str, size: int) -> int: """Простая хеш-функция""" return sum(ord(c) for c in name) % size def ht_create(size: int = 1000) -> List[Optional[Dict]]: """Создание хеш-таблицы""" return [None] * size def ht_insert(buckets: List[Optional[Dict]], name: str, phone: str) -> None: """Вставка в хеш-таблицу""" index = hash_function(name, len(buckets)) buckets[index] = ll_insert(buckets[index], name, phone) def ht_find(buckets: List[Optional[Dict]], name: str) -> Optional[str]: """Поиск в хеш-таблице""" index = hash_function(name, len(buckets)) return ll_find(buckets[index], name) def ht_delete(buckets: List[Optional[Dict]], name: str) -> None: """Удаление из хеш-таблицы""" index = hash_function(name, len(buckets)) buckets[index] = ll_delete(buckets[index], name) def ht_list_all(buckets: List[Optional[Dict]]) -> List[Tuple[str, str]]: """Сбор всех записей из хеш-таблицы с сортировкой""" records = [] for head in buckets: current = head while current is not None: records.append((current['name'], current['phone'])) current = current['next'] records.sort(key=lambda x: x[0]) return records def bst_insert(root: Optional[Dict], name: str, phone: str) -> Dict: """Вставка в BST (итеративная)""" new_node = {'name': name, 'phone': phone, 'left': None, 'right': None} if root is None: return new_node current = root while True: if name < current['name']: if current['left'] is None: current['left'] = new_node break else: current = current['left'] elif name > current['name']: if current['right'] is None: current['right'] = new_node break else: current = current['right'] else: # Обновляем существующую запись current['phone'] = phone break return root def bst_find(root: Optional[Dict], name: str) -> Optional[str]: """Поиск в BST (итеративный)""" current = root while current is not None: if name == current['name']: return current['phone'] elif name < current['name']: current = current['left'] else: current = current['right'] return None def bst_min_node(node: Dict) -> Dict: """Поиск узла с минимальным значением""" current = node while current['left'] is not None: current = current['left'] return current def bst_delete(root: Optional[Dict], name: str) -> Optional[Dict]: """Удаление из BST (итеративная версия)""" if root is None: return None # Поиск узла для удаления и его родителя parent = None current = root while current is not None and current['name'] != name: parent = current if name < current['name']: current = current['left'] else: current = current['right'] if current is None: return root # Случай 1: узел не имеет детей if current['left'] is None and current['right'] is None: if parent is None: return None if parent['left'] == current: parent['left'] = None else: parent['right'] = None return root # Случай 2: узел имеет одного ребёнка if current['left'] is None: child = current['right'] elif current['right'] is None: child = current['left'] else: # Случай 3: узел имеет двух детей # Находим минимальный узел в правом поддереве successor_parent = current successor = current['right'] while successor['left'] is not None: successor_parent = successor successor = successor['left'] # Копируем данные из successor в current current['name'] = successor['name'] current['phone'] = successor['phone'] # Удаляем successor if successor_parent['left'] == successor: successor_parent['left'] = successor['right'] else: successor_parent['right'] = successor['right'] return root # Присоединяем ребёнка к родителю if parent is None: return child if parent['left'] == current: parent['left'] = child else: parent['right'] = child return root def bst_inorder(root: Optional[Dict], records: List[Tuple[str, str]]) -> None: """Центрированный обход BST (рекурсивный)""" if root is not None: bst_inorder(root['left'], records) records.append((root['name'], root['phone'])) bst_inorder(root['right'], records) def bst_list_all(root: Optional[Dict]) -> List[Tuple[str, str]]: """Сбор всех записей из BST (уже отсортированы)""" records = [] bst_inorder(root, records) return records records.sort(key=lambda x: x[0]) return records def generate_records(n: int) -> List[Tuple[str, str]]: """Генерация записей""" records = [(f"User_{i:05d}", f"+7-999-{i:07d}") for i in range(n)] return records def measure_insertion(structure_type: str, data: List[Tuple[str, str]], ht_size: int = 1000) -> float: """Замер времени вставки""" start = time.perf_counter() if structure_type == "LinkedList": head = None for name, phone in data: head = ll_insert(head, name, phone) elif structure_type == "HashTable": buckets = ht_create(ht_size) for name, phone in data: ht_insert(buckets, name, phone) elif structure_type == "BST": root = None for name, phone in data: root = bst_insert(root, name, phone) end = time.perf_counter() return end - start def measure_find(structure_type: str, data: List[Tuple[str, str]], existing_names: List[str], missing_names: List[str], ht_size: int = 1000) -> Tuple[float, Any]: """Замер времени поиска (возвращает время и структуру для удаления)""" # Сначала создаём структуру if structure_type == "LinkedList": head = None for name, phone in data: head = ll_insert(head, name, phone) start = time.perf_counter() for name in existing_names + missing_names: ll_find(head, name) end = time.perf_counter() return end - start, head elif structure_type == "HashTable": buckets = ht_create(ht_size) for name, phone in data: ht_insert(buckets, name, phone) start = time.perf_counter() for name in existing_names + missing_names: ht_find(buckets, name) end = time.perf_counter() return end - start, buckets elif structure_type == "BST": root = None for name, phone in data: root = bst_insert(root, name, phone) start = time.perf_counter() for name in existing_names + missing_names: bst_find(root, name) end = time.perf_counter() return end - start, root def measure_delete(structure_type: str, structure: Any, names_to_delete: List[str]) -> float: """Замер времени удаления""" start = time.perf_counter() if structure_type == "LinkedList": head = structure for name in names_to_delete: head = ll_delete(head, name) elif structure_type == "HashTable": buckets = structure for name in names_to_delete: ht_delete(buckets, name) elif structure_type == "BST": root = structure for name in names_to_delete: root = bst_delete(root, name) end = time.perf_counter() return end - start def run_experiment(n_records: int = 10000, n_find: int = 110, n_delete: int = 50, n_runs: int = 5) -> List[List]: """Запуск всех замеров""" # Генерация данных all_records = generate_records(n_records) records_shuffled = all_records.copy() random.shuffle(records_shuffled) records_sorted = sorted(all_records, key=lambda x: x[0]) # Имена для поиска all_names = [name for name, _ in all_records] existing_names = random.sample(all_names, n_find - 10) missing_names = [f"None_{i}" for i in range(10)] # Имена для удаления names_to_delete = random.sample(all_names, n_delete) structures = ["LinkedList", "HashTable", "BST"] modes = {"shuffled": records_shuffled, "sorted": records_sorted} # Заголовок CSV results = [["Структура", "Режим", "Операция", "Замер1", "Замер2", "Замер3", "Замер4", "Замер5", "Среднее"]] for structure in structures: for mode_name, mode_data in modes.items(): print(f"\nТестирование: {structure}, режим: {mode_name}") # Вставка insertion_times = [] for run in range(n_runs): print(f" Вставка, run {run+1}/{n_runs}...") t = measure_insertion(structure, mode_data) insertion_times.append(t) avg_insertion = sum(insertion_times) / n_runs results.append([structure, mode_name, "вставка"] + [f"{t:.6f}" for t in insertion_times] + [f"{avg_insertion:.6f}"]) print(f" Замеры: {[f'{t:.6f}' for t in insertion_times]}") print(f" Среднее: {avg_insertion:.6f} сек") # Поиск find_times = [] for run in range(n_runs): print(f" Поиск, run {run+1}/{n_runs}...") t, _ = measure_find(structure, mode_data, existing_names, missing_names) find_times.append(t) avg_find = sum(find_times) / n_runs results.append([structure, mode_name, "поиск"] + [f"{t:.6f}" for t in find_times] + [f"{avg_find:.6f}"]) print(f" Замеры: {[f'{t:.6f}' for t in find_times]}") print(f" Среднее: {avg_find:.6f} сек") # Удаление delete_times = [] for run in range(n_runs): print(f" Удаление, run {run+1}/{n_runs}...") # Создаём свежую структуру для каждого замера удаления if structure == "LinkedList": head = None for name, phone in mode_data: head = ll_insert(head, name, phone) t = measure_delete(structure, head, names_to_delete) elif structure == "HashTable": buckets = ht_create() for name, phone in mode_data: ht_insert(buckets, name, phone) t = measure_delete(structure, buckets, names_to_delete) elif structure == "BST": root = None for name, phone in mode_data: root = bst_insert(root, name, phone) t = measure_delete(structure, root, names_to_delete) delete_times.append(t) avg_delete = sum(delete_times) / n_runs results.append([structure, mode_name, "удаление"] + [f"{t:.6f}" for t in delete_times] + [f"{avg_delete:.6f}"]) print(f" Замеры: {[f'{t:.6f}' for t in delete_times]}") print(f" Среднее: {avg_delete:.6f} сек") return results def save_results(results: List[List], filename: str = "results.csv"): """Сохранение результатов в CSV""" with open(filename, "w", newline="", encoding="utf-8") as f: writer = csv.writer(f) writer.writerows(results) print(f"\nРезультаты сохранены в {filename}") def plot_results(results_file: str = "results.csv"): """Построение графика сравнения производительности""" import matplotlib.pyplot as plt import numpy as np # Чтение результатов из CSV data = {} with open(results_file, 'r', encoding='utf-8') as f: reader = csv.reader(f) header = next(reader) # пропускаем заголовок for row in reader: structure = row[0] mode = row[1] operation = row[2] # Берём последнюю колонку (Среднее) avg_time = float(row[-1]) if structure not in data: data[structure] = {} if mode not in data[structure]: data[structure][mode] = {} data[structure][mode][operation] = avg_time # Настройка стиля plt.style.use('seaborn-v0_8-darkgrid') fig, axes = plt.subplots(1, 3, figsize=(15, 5)) colors = ['#FF6B6B', '#4ECDC4'] structures = ["LinkedList", "HashTable", "BST"] modes = ["shuffled", "sorted"] operations = ["вставка", "поиск", "удаление"] op_titles = ["ВСТАВКИ", "ПОИСКА (110 запросов)", "УДАЛЕНИЯ (50 записей)"] for idx, (op, op_title) in enumerate(zip(operations, op_titles)): ax = axes[idx] x = np.arange(len(structures)) width = 0.35 shuffled_vals = [data[s]['shuffled'][op] for s in structures] sorted_vals = [data[s]['sorted'][op] for s in structures] bars1 = ax.bar(x - width/2, shuffled_vals, width, label='Случайный порядок', color=colors[0]) bars2 = ax.bar(x + width/2, sorted_vals, width, label='Отсортированный порядок', color=colors[1]) ax.set_xlabel('Структура данных') ax.set_ylabel('Время (секунды)') ax.set_title(f'Сравнение времени {op_title}') ax.set_xticks(x) ax.set_xticklabels(['Связный\nсписок', 'Хеш-\nтаблица', 'Двоичное\nдерево']) ax.legend() # Добавляем значения на столбцы for bars in [bars1, bars2]: for bar in bars: height = bar.get_height() fmt = '{:.4f}'.format(height) if op == 'вставка' else '{:.6f}'.format(height) ax.text(bar.get_x() + bar.get_width()/2., height, fmt, ha='center', va='bottom', fontsize=8) plt.tight_layout() plt.savefig('performance_comparison.png', dpi=150, bbox_inches='tight') plt.show() # Вывод сводной таблицы в консоль print("\n" + "=" * 90) print("СВОДНАЯ ТАБЛИЦА РЕЗУЛЬТАТОВ (среднее время в секундах)") print("=" * 90) print(f"{'Структура':<15} {'Режим':<12} {'Вставка':<14} {'Поиск':<14} {'Удаление':<14}") print("-" * 90) for structure in structures: for mode in modes: print(f"{structure:<15} {mode:<12} " f"{data[structure][mode]['вставка']:<14.6f} " f"{data[structure][mode]['поиск']:<14.6f} " f"{data[structure][mode]['удаление']:<14.6f}") print("=" * 90) def main(): print("=" * 60) print("ЭКСПЕРИМЕНТАЛЬНОЕ СРАВНЕНИЕ СТРУКТУР ДАННЫХ") print("Связный список | Хеш-таблица | Двоичное дерево поиска") print("=" * 60) # Запуск эксперимента (5 прогонов) results = run_experiment(n_records=10000, n_runs=5) # Сохранение результатов save_results(results) # Построение графика try: import matplotlib.pyplot as plt print("\nПостроение графика...") plot_results("results.csv") except ImportError: print("\nВНИМАНИЕ: Библиотека matplotlib не установлена.") print("Для построения графика выполните: pip install matplotlib") print("Результаты сохранены в CSV файл, вы можете построить график в Excel.") print("\n" + "=" * 60) print("ЭКСПЕРИМЕНТ ЗАВЕРШЁН") print("=" * 60) if __name__ == "__main__": main()