[1] add performance measurement with random/sorted datasets

KislyuninED/docks/data/1-st-exercize/experiment.py

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+import random
+import time
+import csv
+from phonebook import ll_insert, ll_find, ll_delete, ll_list_all
+from phonebook import ht_create, ht_insert, ht_find, ht_delete, ht_list_all
+from phonebook import bst_insert, bst_find, bst_delete, bst_list_all
+
+def generate_records(n, seed=42):
+    random.seed(seed)
+    recs = []
+    for i in range(1, n+1):
+        name = f"User_{i:05d}"
+        phone = f"{random.randint(100,999)}-{random.randint(1000,9999)}"
+        recs.append((name, phone))
+    return recs
+
+def prepare_datasets(recs):
+    shuffled = recs.copy()
+    random.shuffle(shuffled)
+    sorted_recs = sorted(recs, key=lambda x: x[0])
+    return shuffled, sorted_recs
+
+def measure_structure(create_func, insert_func, find_func, delete_func, records, repeats=5):
+    insert_times = []
+    find_times = []
+    delete_times = []
+    existing_names = [name for name,_ in records]
+    search_names = random.sample(existing_names, 100) + [f"None_{i}" for i in range(10)]
+    random.shuffle(search_names)
+    delete_names = random.sample(existing_names, 50)
+    
+    for _ in range(repeats):
+        struct = create_func()
+        # вставка
+        start = time.perf_counter()
+        for name, phone in records:
+            struct = insert_func(struct, name, phone)
+        insert_times.append(time.perf_counter() - start)
+        # поиск
+        start = time.perf_counter()
+        for name in search_names:
+            find_func(struct, name)
+        find_times.append(time.perf_counter() - start)
+        # удаление
+        start = time.perf_counter()
+        for name in delete_names:
+            struct = delete_func(struct, name)
+        delete_times.append(time.perf_counter() - start)
+    return insert_times, find_times, delete_times
+
+def main():
+    N = 1000
+    base = generate_records(N)
+    shuffled, sorted_recs = prepare_datasets(base)
+    
+    results = []
+    # Linked list
+    for mode, data in [('random', shuffled), ('sorted', sorted_recs)]:
+        ins, find, dele = measure_structure(lambda: None, ll_insert, ll_find, ll_delete, data)
+        for i in range(5):
+            results.append(['LinkedList', mode, 'insert', ins[i]])
+            results.append(['LinkedList', mode, 'find', find[i]])
+            results.append(['LinkedList', mode, 'delete', dele[i]])
+    
+    # Hash table
+    for mode, data in [('random', shuffled), ('sorted', sorted_recs)]:
+        ins, find, dele = measure_structure(ht_create, ht_insert, ht_find, ht_delete, data)
+        for i in range(5):
+            results.append(['HashTable', mode, 'insert', ins[i]])
+            results.append(['HashTable', mode, 'find', find[i]])
+            results.append(['HashTable', mode, 'delete', dele[i]])
+    
+    # BST
+    for mode, data in [('random', shuffled), ('sorted', sorted_recs)]:
+        ins, find, dele = measure_structure(lambda: None, bst_insert, bst_find, bst_delete, data)
+        for i in range(5):
+            results.append(['BST', mode, 'insert', ins[i]])
+            results.append(['BST', mode, 'find', find[i]])
+            results.append(['BST', mode, 'delete', dele[i]])
+    
+    with open('results.csv', 'w', newline='') as f:
+        writer = csv.writer(f)
+        writer.writerow(['Structure','Mode','Operation','Time_sec'])
+        writer.writerows(results)
+    print("Results saved to results.csv")
+
+if __name__ == '__main__':
+    main()