forked from UNN/2026-rff_mp
139 lines
3.9 KiB
Plaintext
139 lines
3.9 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "2acfa743",
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"metadata": {},
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"source": [
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"# 0. Подготовим окружение"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "4689b73e",
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"import os\n",
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"sys.path.insert(0, os.path.abspath( '../task1'))\n",
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"sys.path.insert(0, os.path.abspath( '../'))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "37cc11a5",
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"metadata": {},
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"source": [
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"# 1. Генерация тестовых данных\n",
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"\n",
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"Создадим список records из N=10000 элементов. Каждый элемент — кортеж (name, phone). \n",
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"Имена возъмём случайные из небольшого набора (чтобы были повторения и коллизии). \n",
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"Для проверки влияния порядка подготовим два варианта: \n",
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"\n",
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"_records_shuffled_ — случайный порядок. \n",
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"_records_sorted_ — отсортированный по имени (по алфавиту)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "a3b5c31b",
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"metadata": {},
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"outputs": [],
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"source": [
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"from util.randomNames import generate_test_data\n",
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"from util.timeTester import test\n",
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"\n",
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"records_shuffled = generate_test_data(N=10000)\n",
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"records_sorted = generate_test_data(N=10000, _sorted=True)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c2f4989c",
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"metadata": {},
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"source": [
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"# 2. Проведение замеров"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "df12d41d",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Подготовим функции СД, которые будем тестировать\n",
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"from structures.LinkedList import *\n",
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"from structures.HashTable import *\n",
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"from structures.BinaryTree import *\n",
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"\n",
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"func_list = {\"Связанный список\" : (ll_insert, ll_find, ll_delete),\n",
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" \"Хэш-таблица\" : (ht_insert, ht_find, ht_delete),\n",
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" \"Бинарное дерево\" : (bst_insert, bst_find, bst_delete)}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"id": "cc8d0436",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Проведём замеры\n",
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"report = [[\"Структура\", \"Режим\", \"Вставка\", \"Поиск\", \"Удаление\"]]\n",
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"records = {\"Cлучайный\" : records_shuffled, \"Отсортированный\" : records_sorted}\n",
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"\n",
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"TEST_ITERATIONS_NUM = 5\n",
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"\n",
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"for _ in range(TEST_ITERATIONS_NUM):\n",
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" for mode, data in records.items():\n",
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" for struct_name, fns in func_list.items():\n",
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" result = test(data, *fns)\n",
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" row = [struct_name, mode,\n",
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" result[\"insert_time\"],\n",
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" result[\"find_time\"],\n",
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" result[\"delete_time\"]]\n",
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" report.append(row)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"id": "2eedf056",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Сохраним данные в csv\n",
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"import csv\n",
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"with open(\"data/results.csv\", \"w\", newline=\"\") as f:\n",
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" writer = csv.writer(f)\n",
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" writer.writerows(report)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.14.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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