From ad50ed566ba52a55eb6b43e4ed78eb36ababae74 Mon Sep 17 00:00:00 2001
From: Smirnovvs <volodya.smirnov.2005@inbox.ru>
Date: Fri, 4 Sep 2026 15:50:54 +0000
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---
 experiment.py | 132 ++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 132 insertions(+)
 create mode 100644 experiment.py

diff --git a/experiment.py b/experiment.py
new file mode 100644
index 0000000..63e0879
--- /dev/null
+++ b/experiment.py
@@ -0,0 +1,132 @@
+"""Экспериментальное сравнение структур данных."""
+
+import argparse
+import csv
+import random
+from pathlib import Path
+from statistics import mean
+from time import perf_counter
+
+from phonebook import (
+    bst_delete, bst_find, bst_insert,
+    ht_delete, ht_find, ht_insert,
+    ll_delete, ll_find, ll_insert,
+)
+
+
+def generate_records(size):
+    return [(f"User_{index:05d}", f"+7{index:010d}") for index in range(size)]
+
+
+def measure_once(structure, records, existing_names, missing_names, deleted_names, bucket_count):
+    started = perf_counter()
+    if structure == "LinkedList":
+        data = None
+        for name, phone in records:
+            data = ll_insert(data, name, phone)
+        insert_time = perf_counter() - started
+
+        started = perf_counter()
+        for name in existing_names + missing_names:
+            ll_find(data, name)
+        find_time = perf_counter() - started
+
+        started = perf_counter()
+        for name in deleted_names:
+            data = ll_delete(data, name)
+        delete_time = perf_counter() - started
+    elif structure == "HashTable":
+        data = [None] * bucket_count
+        for name, phone in records:
+            ht_insert(data, name, phone)
+        insert_time = perf_counter() - started
+
+        started = perf_counter()
+        for name in existing_names + missing_names:
+            ht_find(data, name)
+        find_time = perf_counter() - started
+
+        started = perf_counter()
+        for name in deleted_names:
+            ht_delete(data, name)
+        delete_time = perf_counter() - started
+    else:
+        data = None
+        for name, phone in records:
+            data = bst_insert(data, name, phone)
+        insert_time = perf_counter() - started
+
+        started = perf_counter()
+        for name in existing_names + missing_names:
+            bst_find(data, name)
+        find_time = perf_counter() - started
+
+        started = perf_counter()
+        for name in deleted_names:
+            data = bst_delete(data, name)
+        delete_time = perf_counter() - started
+
+    return {"insert": insert_time, "find_110": find_time, "delete_50": delete_time}
+
+
+def run_experiment(size=3000, repeats=5, seed=2026, output_dir="docs/data"):
+    rng = random.Random(seed)
+    sorted_records = generate_records(size)
+    shuffled_records = sorted_records.copy()
+    rng.shuffle(shuffled_records)
+    modes = {"shuffled": shuffled_records, "sorted": sorted_records}
+    rows = []
+
+    for mode, records in modes.items():
+        names = [record[0] for record in records]
+        test_cases = []
+        for run in range(1, repeats + 1):
+            test_cases.append((
+                run,
+                rng.sample(names, min(100, size)),
+                [f"None_{index}" for index in range(10)],
+                rng.sample(names, min(50, size)),
+            ))
+        for structure in ("LinkedList", "HashTable", "BST"):
+            for run, existing, missing, deleted in test_cases:
+                timings = measure_once(structure, records, existing, missing, deleted, max(17, size * 2 + 1))
+                for operation, elapsed in timings.items():
+                    rows.append({
+                        "structure": structure,
+                        "mode": mode,
+                        "operation": operation,
+                        "run": run,
+                        "time_seconds": elapsed,
+                    })
+
+    output = Path(output_dir)
+    output.mkdir(parents=True, exist_ok=True)
+    raw_path = output / "results_raw.csv"
+    with raw_path.open("w", newline="", encoding="utf-8-sig") as file:
+        writer = csv.DictWriter(file, fieldnames=rows[0].keys())
+        writer.writeheader()
+        writer.writerows(rows)
+
+    groups = {}
+    for row in rows:
+        key = (row["structure"], row["mode"], row["operation"])
+        groups.setdefault(key, []).append(row["time_seconds"])
+    summary = [
+        {"structure": key[0], "mode": key[1], "operation": key[2], "mean_seconds": mean(values)}
+        for key, values in groups.items()
+    ]
+    summary_path = output / "results_summary.csv"
+    with summary_path.open("w", newline="", encoding="utf-8-sig") as file:
+        writer = csv.DictWriter(file, fieldnames=summary[0].keys())
+        writer.writeheader()
+        writer.writerows(summary)
+    return raw_path, summary_path
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Сравнение структур телефонного справочника")
+    parser.add_argument("--size", type=int, default=3000)
+    parser.add_argument("--repeats", type=int, default=5)
+    args = parser.parse_args()
+    raw, summary = run_experiment(args.size, args.repeats)
+    print(f"Полные замеры: {raw}\nСредние значения: {summary}")