task 1, 2

petryainiyas/task1/bst.py

@@ -0,0 +1,118 @@
+from typing import Any, Dict, List, Optional
+
+
+Node = Dict[str, Any]
+
+
+def _make_node(name: str, phone: str) -> Node:
+    return {"name": name, "phone": phone, "left": None, "right": None}
+
+
+def bst_insert(root: Optional[Node], name: str, phone: str) -> Node:
+    new_node = _make_node(name, phone)
+
+    if root is None:
+        return new_node
+
+    current = root
+    parent = None
+
+    while current is not None:
+        parent = current
+        if name < current["name"]:
+            current = current["left"]
+        elif name > current["name"]:
+            current = current["right"]
+        else:
+            current["phone"] = phone
+            return root
+
+    if name < parent["name"]:
+        parent["left"] = new_node
+    else:
+        parent["right"] = new_node
+
+    return root
+
+
+def bst_find(root: Optional[Node], name: str) -> Optional[str]:
+    current = root
+    while current is not None:
+        if name < current["name"]:
+            current = current["left"]
+        elif name > current["name"]:
+            current = current["right"]
+        else:
+            return current["phone"]
+    return None
+
+
+def _find_min_node(node: Node) -> Node:
+    current = node
+    while current["left"] is not None:
+        current = current["left"]
+    return current
+
+
+def bst_delete(root: Optional[Node], name: str) -> Optional[Node]:
+    if root is None:
+        return None
+
+    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
+
+    if current["left"] is None or current["right"] is None:
+        child = current["left"] if current["left"] is not None else current["right"]
+
+        if parent is None:
+            return child
+
+        if parent["left"] is current:
+            parent["left"] = child
+        else:
+            parent["right"] = child
+        return root
+
+    succ_parent = current
+    successor = current["right"]
+    while successor["left"] is not None:
+        succ_parent = successor
+        successor = successor["left"]
+
+    current["name"] = successor["name"]
+    current["phone"] = successor["phone"]
+
+    successor_child = successor["right"]
+    if succ_parent["left"] is successor:
+        succ_parent["left"] = successor_child
+    else:
+        succ_parent["right"] = successor_child
+
+    return root
+
+
+def bst_list_all(root: Optional[Node]) -> List[Dict[str, str]]:
+    result: List[Dict[str, str]] = []
+    stack: List[Node] = []
+    current = root
+
+    while current is not None or stack:
+        while current is not None:
+            stack.append(current)
+            current = current["left"]
+
+        current = stack.pop()
+        result.append({"name": current["name"], "phone": current["phone"]})
+        current = current["right"]
+
+    return result

petryainiyas/task1/docs/data/results.csv

@@ -0,0 +1,109 @@
+Структура,Режим,Операция,Замер,Время (сек)
+LinkedList,случайный,insert,1,4.2622492010
+LinkedList,случайный,find,1,0.0314994130
+LinkedList,случайный,delete,1,0.0149069000
+LinkedList,случайный,insert,2,4.0154580330
+LinkedList,случайный,find,2,0.0393284500
+LinkedList,случайный,delete,2,0.0210732100
+LinkedList,случайный,insert,3,4.0436019780
+LinkedList,случайный,find,3,0.0344933660
+LinkedList,случайный,delete,3,0.0152639850
+LinkedList,случайный,insert,4,3.7182993220
+LinkedList,случайный,find,4,0.0327698850
+LinkedList,случайный,delete,4,0.0149959540
+LinkedList,случайный,insert,5,3.7082228200
+LinkedList,случайный,find,5,0.0303762490
+LinkedList,случайный,delete,5,0.0141406560
+LinkedList,случайный,insert,среднее,3.9495662708
+LinkedList,случайный,find,среднее,0.0336934726
+LinkedList,случайный,delete,среднее,0.0160761410
+HashTable,случайный,insert,1,0.2059865770
+HashTable,случайный,find,1,0.0014966100
+HashTable,случайный,delete,1,0.0006891700
+HashTable,случайный,insert,2,0.2024331460
+HashTable,случайный,find,2,0.0015934880
+HashTable,случайный,delete,2,0.0007212620
+HashTable,случайный,insert,3,0.2126128040
+HashTable,случайный,find,3,0.0016566220
+HashTable,случайный,delete,3,0.0008358420
+HashTable,случайный,insert,4,0.2157934910
+HashTable,случайный,find,4,0.0015542810
+HashTable,случайный,delete,4,0.0007269120
+HashTable,случайный,insert,5,0.2079924580
+HashTable,случайный,find,5,0.0013696990
+HashTable,случайный,delete,5,0.0006616050
+HashTable,случайный,insert,среднее,0.2089636952
+HashTable,случайный,find,среднее,0.0015341400
+HashTable,случайный,delete,среднее,0.0007269582
+BST,случайный,insert,1,0.0166981280
+BST,случайный,find,1,0.0001569360
+BST,случайный,delete,1,0.0000917280
+BST,случайный,insert,2,0.0184119040
+BST,случайный,find,2,0.0001517110
+BST,случайный,delete,2,0.0001163770
+BST,случайный,insert,3,0.0174662270
+BST,случайный,find,3,0.0001582930
+BST,случайный,delete,3,0.0000892660
+BST,случайный,insert,4,0.0191369100
+BST,случайный,find,4,0.0002087170
+BST,случайный,delete,4,0.0001067050
+BST,случайный,insert,5,0.0184276900
+BST,случайный,find,5,0.0002767720
+BST,случайный,delete,5,0.0001067660
+BST,случайный,insert,среднее,0.0180281718
+BST,случайный,find,среднее,0.0001904858
+BST,случайный,delete,среднее,0.0001021684
+LinkedList,отсортированный,insert,1,2.9875078340
+LinkedList,отсортированный,find,1,0.0237300610
+LinkedList,отсортированный,delete,1,0.0111698260
+LinkedList,отсортированный,insert,2,3.0573987940
+LinkedList,отсортированный,find,2,0.0243270360
+LinkedList,отсортированный,delete,2,0.0115366030
+LinkedList,отсортированный,insert,3,2.9641987260
+LinkedList,отсортированный,find,3,0.0236313330
+LinkedList,отсортированный,delete,3,0.0112848510
+LinkedList,отсортированный,insert,4,3.0345914950
+LinkedList,отсортированный,find,4,0.0240271220
+LinkedList,отсортированный,delete,4,0.0112117310
+LinkedList,отсортированный,insert,5,2.9481954700
+LinkedList,отсортированный,find,5,0.0239006100
+LinkedList,отсортированный,delete,5,0.0110857710
+LinkedList,отсортированный,insert,среднее,2.9983784638
+LinkedList,отсортированный,find,среднее,0.0239232324
+LinkedList,отсортированный,delete,среднее,0.0112577564
+HashTable,отсортированный,insert,1,0.1997087560
+HashTable,отсортированный,find,1,0.0017550400
+HashTable,отсортированный,delete,1,0.0008407980
+HashTable,отсортированный,insert,2,0.1968675190
+HashTable,отсортированный,find,2,0.0019886760
+HashTable,отсортированный,delete,2,0.0008920910
+HashTable,отсортированный,insert,3,0.1907563580
+HashTable,отсортированный,find,3,0.0018447440
+HashTable,отсортированный,delete,3,0.0008684640
+HashTable,отсортированный,insert,4,0.2625327630
+HashTable,отсортированный,find,4,0.0016053140
+HashTable,отсортированный,delete,4,0.0008098670
+HashTable,отсортированный,insert,5,0.1936840590
+HashTable,отсортированный,find,5,0.0019015160
+HashTable,отсортированный,delete,5,0.0009053780
+HashTable,отсортированный,insert,среднее,0.2087098910
+HashTable,отсортированный,find,среднее,0.0018190580
+HashTable,отсортированный,delete,среднее,0.0008633196
+BST,отсортированный,insert,1,4.2195800190
+BST,отсортированный,find,1,0.0389314570
+BST,отсортированный,delete,1,0.0190308920
+BST,отсортированный,insert,2,4.1356184250
+BST,отсортированный,find,2,0.0383339310
+BST,отсортированный,delete,2,0.0194247740
+BST,отсортированный,insert,3,4.1204731890
+BST,отсортированный,find,3,0.0388593320
+BST,отсортированный,delete,3,0.0215428460
+BST,отсортированный,insert,4,4.2120902370
+BST,отсортированный,find,4,0.0378190250
+BST,отсортированный,delete,4,0.0188528460
+BST,отсортированный,insert,5,4.1304951260
+BST,отсортированный,find,5,0.0359927840
+BST,отсортированный,delete,5,0.0179617110
+BST,отсортированный,insert,среднее,4.1636513992
+BST,отсортированный,find,среднее,0.0379873058
+BST,отсортированный,delete,среднее,0.0193626138

petryainiyas/task1/experiments.py

@@ -0,0 +1,172 @@
+from __future__ import annotations
+
+import csv
+import random
+import time
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+from linked_list import ll_insert, ll_find, ll_delete
+from hash_table import ht_insert, ht_find, ht_delete
+from bst import bst_insert, bst_find, bst_delete
+from utils import generate_records, prepare_records_variants
+
+
+Record = Tuple[str, str]
+
+
+def make_missing_names(count: int = 10) -> List[str]:
+    return [f"None_{i}" for i in range(count)]
+
+
+def pick_existing_names(records: List[Record], count: int, seed: int = 42) -> List[str]:
+    rng = random.Random(seed)
+    unique_names = list(dict.fromkeys(name for name, _ in records))
+    if len(unique_names) < count:
+        raise ValueError(f"Not enough unique names: need {count}, got {len(unique_names)}")
+    return rng.sample(unique_names, count)
+
+
+def pick_delete_names(records: List[Record], count: int = 50, seed: int = 43) -> List[str]:
+    rng = random.Random(seed)
+    unique_names = list(dict.fromkeys(name for name, _ in records))
+    if len(unique_names) < count:
+        raise ValueError(f"Not enough unique names: need {count}, got {len(unique_names)}")
+    return rng.sample(unique_names, count)
+
+
+def build_structure(structure_name: str, records: List[Record], buckets_count: int = 2048):
+    if structure_name == "linked_list":
+        structure = None
+        for name, phone in records:
+            structure = ll_insert(structure, name, phone)
+        return structure
+
+    if structure_name == "hash_table":
+        buckets = [None] * buckets_count
+        for name, phone in records:
+            buckets = ht_insert(buckets, name, phone)
+        return buckets
+
+    if structure_name == "bst":
+        root = None
+        for name, phone in records:
+            root = bst_insert(root, name, phone)
+        return root
+
+    raise ValueError(f"Unknown structure: {structure_name}")
+
+
+def do_find(structure_name: str, structure: object, existing_names: List[str], missing_names: List[str]) -> None:
+    if structure_name == "linked_list":
+        for name in existing_names:
+            ll_find(structure, name)
+        for name in missing_names:
+            ll_find(structure, name)
+        return
+
+    if structure_name == "hash_table":
+        for name in existing_names:
+            ht_find(structure, name)
+        for name in missing_names:
+            ht_find(structure, name)
+        return
+
+    if structure_name == "bst":
+        for name in existing_names:
+            bst_find(structure, name)
+        for name in missing_names:
+            bst_find(structure, name)
+        return
+
+    raise ValueError(f"Unknown structure: {structure_name}")
+
+
+def do_delete(structure_name: str, structure: object, delete_names: List[str]):
+    if structure_name == "linked_list":
+        for name in delete_names:
+            structure = ll_delete(structure, name)
+        return structure
+
+    if structure_name == "hash_table":
+        for name in delete_names:
+            structure = ht_delete(structure, name)
+        return structure
+
+    if structure_name == "bst":
+        for name in delete_names:
+            structure = bst_delete(structure, name)
+        return structure
+
+    raise ValueError(f"Unknown structure: {structure_name}")
+
+
+def measure_once(structure_name: str, records: List[Record], buckets_count: int = 2048) -> Dict[str, float]:
+    existing_names = pick_existing_names(records, 100, seed=42)
+    missing_names = make_missing_names(10)
+    delete_names = pick_delete_names(records, 50, seed=43)
+
+    start = time.perf_counter()
+    structure = build_structure(structure_name, records, buckets_count=buckets_count)
+    insert_time = time.perf_counter() - start
+
+    start = time.perf_counter()
+    do_find(structure_name, structure, existing_names, missing_names)
+    find_time = time.perf_counter() - start
+
+    start = time.perf_counter()
+    structure = do_delete(structure_name, structure, delete_names)
+    delete_time = time.perf_counter() - start
+
+    return {"insert": insert_time, "find": find_time, "delete": delete_time}
+
+
+def run_experiments(n: int = 10000, buckets_count: int = 2048, repeats: int = 5):
+    records = generate_records(n, repeat_names=False)
+    records_shuffled, records_sorted = prepare_records_variants(records)
+
+    datasets = [
+        ("случайный", records_shuffled),
+        ("отсортированный", records_sorted),
+    ]
+    structures = [
+        ("LinkedList", "linked_list"),
+        ("HashTable", "hash_table"),
+        ("BST", "bst"),
+    ]
+    operations = ("insert", "find", "delete")
+
+    rows = [["Структура", "Режим", "Операция", "Замер", "Время (сек)"]]
+
+    for mode_name, dataset_records in datasets:
+        for human_name, structure_name in structures:
+            times_by_op = {op: [] for op in operations}
+
+            for attempt in range(1, repeats + 1):
+                result = measure_once(structure_name, dataset_records, buckets_count=buckets_count)
+                for op_name in operations:
+                    elapsed = result[op_name]
+                    times_by_op[op_name].append(elapsed)
+                    rows.append([human_name, mode_name, op_name, attempt, f"{elapsed:.10f}"])
+
+            for op_name in operations:
+                avg_time = sum(times_by_op[op_name]) / len(times_by_op[op_name])
+                rows.append([human_name, mode_name, op_name, "среднее", f"{avg_time:.10f}"])
+
+    return rows
+
+
+def save_results_csv(rows, filename: str = "results.csv"):
+    with open(filename, "w", newline="", encoding="utf-8") as f:
+        writer = csv.writer(f)
+        writer.writerows(rows)
+
+
+def main():
+    rows = run_experiments(n=10000, buckets_count=2048, repeats=5)
+    save_results_csv(rows, "results.csv")
+    print("Saved results.csv")
+
+
+if __name__ == "__main__":
+    main()

petryainiyas/task1/hash_table.py

@@ -0,0 +1,44 @@
+
+
+from typing import Any, Dict, List, Optional
+
+from linked_list import ll_insert, ll_find, ll_delete, ll_list_all
+
+
+Bucket = Optional[Dict[str, Any]]
+
+
+def _hash_name(name: str, buckets_count: int) -> int:
+    if buckets_count <= 0:
+        return 0
+    return sum(ord(ch) for ch in name) % buckets_count
+
+
+def ht_insert(buckets: List[Bucket], name: str, phone: str) -> List[Bucket]:
+    if not buckets:
+        return buckets
+    index = _hash_name(name, len(buckets))
+    buckets[index] = ll_insert(buckets[index], name, phone)
+    return buckets
+
+
+def ht_find(buckets: List[Bucket], name: str) -> Optional[str]:
+    if not buckets:
+        return None
+    index = _hash_name(name, len(buckets))
+    return ll_find(buckets[index], name)
+
+
+def ht_delete(buckets: List[Bucket], name: str) -> List[Bucket]:
+    if not buckets:
+        return buckets
+    index = _hash_name(name, len(buckets))
+    buckets[index] = ll_delete(buckets[index], name)
+    return buckets
+
+
+def ht_list_all(buckets: List[Bucket]) -> List[Dict[str, str]]:
+    records: List[Dict[str, str]] = []
+    for head in buckets:
+        records.extend(ll_list_all(head))
+    return sorted(records, key=lambda x: x["name"])

petryainiyas/task1/linked_list.py

@@ -0,0 +1,73 @@
+
+
+from typing import Any, Dict, List, Optional
+
+
+Node = Dict[str, Any]
+
+
+def _make_node(name: str, phone: str) -> Node:
+    return {"name": name, "phone": phone, "next": None}
+
+
+def sort_records(records: List[Dict[str, str]]) -> List[Dict[str, str]]:
+
+    return sorted(records, key=lambda x: x["name"])
+
+
+def ll_insert(head: Optional[Node], name: str, phone: str) -> Node:
+
+    new_node = _make_node(name, phone)
+
+    if head is None:
+        return new_node
+
+    current = head
+    while current is not None:
+        if current["name"] == name:
+            current["phone"] = phone
+            return head
+        if current["next"] is None:
+            current["next"] = new_node
+            return head
+        current = current["next"]
+
+    return head
+
+
+def ll_find(head: Optional[Node], name: str) -> Optional[str]:
+    current = head
+    while current is not None:
+        if current["name"] == name:
+            return current["phone"]
+        current = current["next"]
+    return None
+
+
+def ll_delete(head: Optional[Node], name: str) -> Optional[Node]:
+    if head is None:
+        return None
+
+    if head["name"] == name:
+        return head["next"]
+
+    prev = head
+    current = head["next"]
+
+    while current is not None:
+        if current["name"] == name:
+            prev["next"] = current["next"]
+            return head
+        prev = current
+        current = current["next"]
+
+    return head
+
+
+def ll_list_all(head: Optional[Node]) -> List[Dict[str, str]]:
+    records: List[Dict[str, str]] = []
+    current = head
+    while current is not None:
+        records.append({"name": current["name"], "phone": current["phone"]})
+        current = current["next"]
+    return sort_records(records)

petryainiyas/task1/main.py

@@ -0,0 +1,21 @@
+
+
+from __future__ import annotations
+
+import csv
+from pathlib import Path
+
+from experiments import run_experiments, save_results_csv
+from plot_results import build_graphs, load_average_results
+
+
+def main():
+    rows = run_experiments(n=10000, buckets_count=2048, repeats=5)
+    save_results_csv(rows, "results.csv")
+    averaged = load_average_results("results.csv")
+    build_graphs(averaged, output_dir="docs/data")
+    print("Done.")
+
+
+if __name__ == "__main__":
+    main()

petryainiyas/task1/plot_results.py

@@ -0,0 +1,66 @@
+from __future__ import annotations
+import csv
+from collections import defaultdict
+from pathlib import Path
+import matplotlib.pyplot as plt
+from typing import List, Dict, Any
+
+# Карта соответствия заголовков CSV для удобства поддержки
+_CSV_KEYS = {
+    "STRUCTURE": "Структура",
+    "MODE": "Режим",
+    "OP": "Операция",
+    "MEASURE": "Замер",
+    "TIME": "Время (сек)"
+}
+
+def load_average_results(csv_file: str) -> List[Dict[str, Any]]:
+    """Загружает только строки со средними значениями из CSV."""
+    with open(csv_file, "r", encoding="utf-8") as fh:
+        return [
+            {
+                "structure": row[_CSV_KEYS["STRUCTURE"]],
+                "mode": row[_CSV_KEYS["MODE"]],
+                "operation": row[_CSV_KEYS["OP"]],
+                "time": float(row[_CSV_KEYS["TIME"]])
+            }
+            for row in csv.DictReader(fh)
+            if row[_CSV_KEYS["MEASURE"]] == "среднее"
+        ]
+
+def _render_chart(operation: str, data: List[Dict[str, Any]], save_path: Path) -> None:
+    """Вспомогательная функция для отрисовки одного столбчатого графика."""
+    fig, ax = plt.subplots(figsize=(10, 5))
+    labels = [f"{rec['structure']}\n{rec['mode']}" for rec in data]
+    values = [rec["time"] for rec in data]
+
+    ax.bar(labels, values, color="cornflowerblue", edgecolor="navy")
+    ax.set_title(f"{operation.capitalize()} Performance Comparison")
+    ax.set_xlabel("Data Structure & Input Order")
+    ax.set_ylabel("Execution Time (seconds)")
+    ax.tick_params(axis="x", rotation=15)
+    fig.tight_layout()
+    fig.savefig(save_path, dpi=150)
+    plt.close(fig)
+    print(f"Saved chart: {save_path}")
+
+def build_graphs(results: List[Dict[str, Any]], output_dir: str = "docs/data") -> None:
+    """Группирует результаты по операциям и сохраняет графики."""
+    out_path = Path(output_dir)
+    out_path.mkdir(parents=True, exist_ok=True)
+
+    grouped = defaultdict(list)
+    for record in results:
+        grouped[record["operation"]].append(record)
+
+    for op_name in ("insert", "find", "delete"):
+        if op_name in grouped:
+            target_file = out_path / f"{op_name}.png"
+            _render_chart(op_name, grouped[op_name], target_file)
+
+def main():
+    avg_data = load_average_results("results.csv")
+    build_graphs(avg_data)
+
+if __name__ == "__main__":
+    main()

petryainiyas/task1/requirements.txt

@@ -0,0 +1 @@
+matplotlib>=3.8

petryainiyas/task1/results.csv

@@ -0,0 +1,109 @@
+Структура,Режим,Операция,Замер,Время (сек)
+LinkedList,случайный,insert,1,6.8132659000
+LinkedList,случайный,find,1,0.0553455000
+LinkedList,случайный,delete,1,0.0304272000
+LinkedList,случайный,insert,2,6.8263299000
+LinkedList,случайный,find,2,0.0562645000
+LinkedList,случайный,delete,2,0.0303858000
+LinkedList,случайный,insert,3,6.8117682000
+LinkedList,случайный,find,3,0.0567219000
+LinkedList,случайный,delete,3,0.0302671000
+LinkedList,случайный,insert,4,7.0393228000
+LinkedList,случайный,find,4,0.0544359000
+LinkedList,случайный,delete,4,0.0313359000
+LinkedList,случайный,insert,5,7.0633509000
+LinkedList,случайный,find,5,0.0552176000
+LinkedList,случайный,delete,5,0.0318664000
+LinkedList,случайный,insert,среднее,6.9108075400
+LinkedList,случайный,find,среднее,0.0555970800
+LinkedList,случайный,delete,среднее,0.0308564800
+HashTable,случайный,insert,1,0.3898307000
+HashTable,случайный,find,1,0.0022226000
+HashTable,случайный,delete,1,0.0012723000
+HashTable,случайный,insert,2,0.3844561000
+HashTable,случайный,find,2,0.0024825000
+HashTable,случайный,delete,2,0.0013425000
+HashTable,случайный,insert,3,0.3740853000
+HashTable,случайный,find,3,0.0026141000
+HashTable,случайный,delete,3,0.0013710000
+HashTable,случайный,insert,4,0.3870099000
+HashTable,случайный,find,4,0.0022063000
+HashTable,случайный,delete,4,0.0015940000
+HashTable,случайный,insert,5,0.3869087000
+HashTable,случайный,find,5,0.0022110000
+HashTable,случайный,delete,5,0.0012524000
+HashTable,случайный,insert,среднее,0.3844581400
+HashTable,случайный,find,среднее,0.0023473000
+HashTable,случайный,delete,среднее,0.0013664400
+BST,случайный,insert,1,0.0375842000
+BST,случайный,find,1,0.0003637000
+BST,случайный,delete,1,0.0001893000
+BST,случайный,insert,2,0.0364385000
+BST,случайный,find,2,0.0003284000
+BST,случайный,delete,2,0.0002408000
+BST,случайный,insert,3,0.0359604000
+BST,случайный,find,3,0.0003705000
+BST,случайный,delete,3,0.0001883000
+BST,случайный,insert,4,0.0371920000
+BST,случайный,find,4,0.0003347000
+BST,случайный,delete,4,0.0001711000
+BST,случайный,insert,5,0.0385580000
+BST,случайный,find,5,0.0003628000
+BST,случайный,delete,5,0.0001828000
+BST,случайный,insert,среднее,0.0371466200
+BST,случайный,find,среднее,0.0003520200
+BST,случайный,delete,среднее,0.0001944600
+LinkedList,отсортированный,insert,1,6.7166487000
+LinkedList,отсортированный,find,1,0.0614362000
+LinkedList,отсортированный,delete,1,0.0324487000
+LinkedList,отсортированный,insert,2,6.8582294000
+LinkedList,отсортированный,find,2,0.0588546000
+LinkedList,отсортированный,delete,2,0.0332572000
+LinkedList,отсортированный,insert,3,6.6991410000
+LinkedList,отсортированный,find,3,0.0521304000
+LinkedList,отсортированный,delete,3,0.0296734000
+LinkedList,отсортированный,insert,4,6.7166336000
+LinkedList,отсортированный,find,4,0.0521848000
+LinkedList,отсортированный,delete,4,0.0286064000
+LinkedList,отсортированный,insert,5,6.6510829000
+LinkedList,отсортированный,find,5,0.0547075000
+LinkedList,отсортированный,delete,5,0.0285625000
+LinkedList,отсортированный,insert,среднее,6.7283471200
+LinkedList,отсортированный,find,среднее,0.0558627000
+LinkedList,отсортированный,delete,среднее,0.0305096400
+HashTable,отсортированный,insert,1,0.3645209000
+HashTable,отсортированный,find,1,0.0032770000
+HashTable,отсортированный,delete,1,0.0018631000
+HashTable,отсортированный,insert,2,0.3579217000
+HashTable,отсортированный,find,2,0.0032143000
+HashTable,отсортированный,delete,2,0.0016427000
+HashTable,отсортированный,insert,3,0.3684879000
+HashTable,отсортированный,find,3,0.0026412000
+HashTable,отсортированный,delete,3,0.0014870000
+HashTable,отсортированный,insert,4,0.3873619000
+HashTable,отсортированный,find,4,0.0028024000
+HashTable,отсортированный,delete,4,0.0015786000
+HashTable,отсортированный,insert,5,0.3642992000
+HashTable,отсортированный,find,5,0.0031264000
+HashTable,отсортированный,delete,5,0.0015886000
+HashTable,отсортированный,insert,среднее,0.3685183200
+HashTable,отсортированный,find,среднее,0.0030122600
+HashTable,отсортированный,delete,среднее,0.0016320000
+BST,отсортированный,insert,1,10.5552378000
+BST,отсортированный,find,1,0.1016856000
+BST,отсортированный,delete,1,0.0422728000
+BST,отсортированный,insert,2,10.3035871000
+BST,отсортированный,find,2,0.1008642000
+BST,отсортированный,delete,2,0.0450330000
+BST,отсортированный,insert,3,10.6304005000
+BST,отсортированный,find,3,0.1073470000
+BST,отсортированный,delete,3,0.0816121000
+BST,отсортированный,insert,4,10.3183078000
+BST,отсортированный,find,4,0.1005074000
+BST,отсортированный,delete,4,0.0422195000
+BST,отсортированный,insert,5,10.3131368000
+BST,отсортированный,find,5,0.1001096000
+BST,отсортированный,delete,5,0.0416660000
+BST,отсортированный,insert,среднее,10.4241340000
+BST,отсортированный,find,среднее,0.1021027600
+BST,отсортированный,delete,среднее,0.0505606800

petryainiyas/task1/utils.py

@@ -0,0 +1,29 @@
+import random
+from typing import List, Tuple
+
+Record = Tuple[str, str]
+
+NAME_POOL = (
+    "User_Alex", "User_Bob", "User_Cat", "User_Dan", "User_Eva",
+    "User_Fox", "User_Geo", "User_Hen", "User_Ira", "User_Leo"
+)
+
+def generate_records(n: int, repeat_names: bool = False, seed: int = 42) -> List[Record]:
+    """Генерирует n кортежей (имя, телефон)."""
+    rng = random.Random(seed)
+    if repeat_names:
+        return [
+            (rng.choice(NAME_POOL), str(rng.randint(10**9, 10**10 - 1)))
+            for _ in range(n)
+        ]
+    return [
+        (f"User_{i:05d}", str(10**9 + i))
+        for i in range(n)
+    ]
+
+def prepare_records_variants(records: List[Record], seed: int = 42) -> Tuple[List[Record], List[Record]]:
+    """Возвращает пару: (перемешанный список, отсортированный по имени список)."""
+    shuffled = records.copy()
+    random.Random(seed).shuffle(shuffled)
+    sorted_records = sorted(records, key=lambda rec: rec[0])
+    return shuffled, sorted_records

petryainiyas/task2/builders/maze_builder.py

@@ -0,0 +1,7 @@
+from abc import ABC, abstractmethod
+
+
+class MazeBuilder(ABC):
+    @abstractmethod
+    def buildFromFile(self, filename):
+        raise NotImplementedError

petryainiyas/task2/builders/text_file_maze_builder.py

@@ -0,0 +1,52 @@
+from core.cell import Cell
+from core.maze import Maze
+from builders.maze_builder import MazeBuilder
+
+
+class TextFileMazeBuilder(MazeBuilder):
+    def buildFromFile(self, filename):
+        with open(filename, "r", encoding="utf-8") as f:
+            lines = [line.rstrip("\n") for line in f]
+
+        if not lines:
+            raise ValueError("Maze file is empty")
+
+        width = max(len(line) for line in lines)
+        height = len(lines)
+
+        cells = []
+        startCell = None
+        exitCell = None
+
+        for y, line in enumerate(lines):
+            row = []
+            for x in range(width):
+                ch = line[x] if x < len(line) else "#"
+
+                if ch == "#":
+                    cell = Cell(x, y, isWall=True)
+                elif ch == "S":
+                    if startCell is not None:
+                        raise ValueError("Multiple start cells found")
+                    cell = Cell(x, y, isWall=False, isStart=True)
+                    startCell = cell
+                elif ch == "E":
+                    if exitCell is not None:
+                        raise ValueError("Multiple exit cells found")
+                    cell = Cell(x, y, isWall=False, isExit=True)
+                    exitCell = cell
+                elif ch in (" ", "."):
+                    cell = Cell(x, y, isWall=False)
+                elif ch.isdigit():
+                    cell = Cell(x, y, isWall=False, weight=max(1, int(ch)))
+                else:
+                    raise ValueError(f"Unsupported symbol '{ch}' at ({x}, {y})")
+                row.append(cell)
+            cells.append(row)
+
+        if startCell is None:
+            raise ValueError("Start cell 'S' not found")
+        if exitCell is None:
+            raise ValueError("Exit cell 'E' not found")
+
+        return Maze(cells, width, height, startCell, exitCell)

petryainiyas/task2/commands/command.py

@@ -0,0 +1,11 @@
+from abc import ABC, abstractmethod
+
+
+class Command(ABC):
+    @abstractmethod
+    def execute(self):
+        raise NotImplementedError
+
+    @abstractmethod
+    def undo(self):
+        raise NotImplementedError

petryainiyas/task2/commands/move_command.py

@@ -0,0 +1,37 @@
+from commands.command import Command
+
+
+class MoveCommand(Command):
+    DIRECTION_TO_DELTA = {
+        "W": (0, -1),
+        "A": (-1, 0),
+        "S": (0, 1),
+        "D": (1, 0),
+    }
+
+    def __init__(self, player, maze, direction):
+        self.player = player
+        self.maze = maze
+        self.direction = direction.upper()
+        self.previousCell = None
+
+    def execute(self):
+        if self.direction not in self.DIRECTION_TO_DELTA:
+            return False
+
+        dx, dy = self.DIRECTION_TO_DELTA[self.direction]
+        current = self.player.currentCell
+        new_cell = self.maze.getCell(current.x + dx, current.y + dy)
+
+        if new_cell is None or not new_cell.isPassable():
+            return False
+
+        self.previousCell = current
+        self.player.setCell(new_cell)
+        return True
+
+    def undo(self):
+        if self.previousCell is None:
+            return False
+        self.player.setCell(self.previousCell)
+        return True

petryainiyas/task2/controller/game_controller.py

@@ -0,0 +1,30 @@
+from commands.move_command import MoveCommand
+
+
+class GameController:
+    def __init__(self, maze, player, view):
+        self.maze = maze
+        self.player = player
+        self.view = view
+        self.history = []
+
+    def move(self, direction):
+        command = MoveCommand(self.player, self.maze, direction)
+        if command.execute():
+            self.history.append(command)
+            self.view.update({"type": "move", "direction": direction})
+            self.view.render(self.maze, player_position=self.player.currentCell)
+            return True
+        print("Cannot move there")
+        return False
+
+    def undo(self):
+        if not self.history:
+            print("Nothing to undo")
+            return False
+        command = self.history.pop()
+        if command.undo():
+            self.view.update({"type": "undo"})
+            self.view.render(self.maze, player_position=self.player.currentCell)
+            return True
+        return False

petryainiyas/task2/core/cell.py

@@ -0,0 +1,26 @@
+from dataclasses import dataclass
+
+
+@dataclass
+class Cell:
+    x: int
+    y: int
+    isWall: bool = False
+    isStart: bool = False
+    isExit: bool = False
+    weight: int = 1
+
+    def isPassable(self):
+        return not self.isWall
+
+    def __repr__(self):
+        parts = [f"Cell({self.x}, {self.y}"]
+        if self.isWall:
+            parts.append("WALL")
+        if self.isStart:
+            parts.append("START")
+        if self.isExit:
+            parts.append("EXIT")
+        if self.weight != 1:
+            parts.append(f"w={self.weight}")
+        return ", ".join(parts) + ")"

petryainiyas/task2/core/maze.py

@@ -0,0 +1,49 @@
+class Maze:
+    def __init__(self, cells, width, height, startCell=None, exitCell=None):
+        self.cells = cells
+        self.width = width
+        self.height = height
+        self.startCell = startCell
+        self.exitCell = exitCell
+
+    def getCell(self, x, y):
+        if 0 <= x < self.width and 0 <= y < self.height:
+            return self.cells[y][x]
+        return None
+
+    def getNeighbors(self, cell):
+        neighbors = []
+        for dx, dy in ((0, -1), (0, 1), (-1, 0), (1, 0)):
+            nx, ny = cell.x + dx, cell.y + dy
+            neighbor = self.getCell(nx, ny)
+            if neighbor is not None and neighbor.isPassable():
+                neighbors.append(neighbor)
+        return neighbors
+
+    def render_lines(self, player_position=None, path=None):
+        path_set = {(c.x, c.y) for c in path} if path else set()
+        player_pos = None if player_position is None else (player_position.x, player_position.y)
+        lines = []
+        for y in range(self.height):
+            row = []
+            for x in range(self.width):
+                cell = self.cells[y][x]
+                if player_pos == (x, y):
+                    row.append("P")
+                elif cell.isStart:
+                    row.append("S")
+                elif cell.isExit:
+                    row.append("E")
+                elif cell.isWall:
+                    row.append("#")
+                elif (x, y) in path_set:
+                    row.append("*")
+                elif cell.weight > 1:
+                    row.append(str(cell.weight))
+                else:
+                    row.append(" ")
+            lines.append("".join(row))
+        return lines
+
+    def render(self, player_position=None, path=None):
+        return "\n".join(self.render_lines(player_position=player_position, path=path))

petryainiyas/task2/core/player.py

@@ -0,0 +1,6 @@
+class Player:
+    def __init__(self, currentCell):
+        self.currentCell = currentCell
+
+    def setCell(self, cell):
+        self.currentCell = cell

petryainiyas/task2/core/search_stats.py

@@ -0,0 +1,11 @@
+from dataclasses import dataclass, field
+
+
+@dataclass
+class SearchStats:
+    timeMs: float
+    visitedCells: int
+    pathLength: int
+    path: list = field(default_factory=list)
+    found: bool = False
+    algorithm: str = ""

petryainiyas/task2/experiment.py

@@ -0,0 +1,225 @@
+from pathlib import Path
+from statistics import mean
+import csv
+import random
+
+import matplotlib.pyplot as plt
+
+from core.cell import Cell
+from core.maze import Maze
+from solver.maze_solver import MazeSolver
+from strategies.astar_strategy import AStarStrategy
+from strategies.bfs_strategy import BFSStrategy
+from strategies.dfs_strategy import DFSStrategy
+from strategies.dijkstra_strategy import DijkstraStrategy
+
+
+BASE_DIR = Path(__file__).resolve().parent
+OUT_DIR = BASE_DIR / "experiment_results"
+
+
+def build_maze_from_symbols(lines):
+    height = len(lines)
+    width = max(len(line) for line in lines)
+    cells = []
+    start = None
+    exit_cell = None
+    for y, line in enumerate(lines):
+        row = []
+        for x in range(width):
+            ch = line[x] if x < len(line) else "#"
+            if ch == "#":
+                cell = Cell(x, y, isWall=True)
+            elif ch == "S":
+                cell = Cell(x, y, isWall=False, isStart=True)
+                start = cell
+            elif ch == "E":
+                cell = Cell(x, y, isWall=False, isExit=True)
+                exit_cell = cell
+            elif ch == " " or ch == ".":
+                cell = Cell(x, y, isWall=False)
+            elif ch.isdigit():
+                cell = Cell(x, y, isWall=False, weight=int(ch))
+            else:
+                raise ValueError(f"Unknown symbol '{ch}' at {x},{y}")
+            row.append(cell)
+        cells.append(row)
+    return Maze(cells, width, height, start, exit_cell)
+
+
+def generate_empty_maze(width, height):
+    lines = [" " * width for _ in range(height)]
+    lines = [list(row) for row in lines]
+    lines[1][1] = "S"
+    lines[height - 2][width - 2] = "E"
+    return build_maze_from_symbols(["".join(row) for row in lines])
+
+
+def generate_simple_maze(width, height):
+    grid = [["#" for _ in range(width)] for _ in range(height)]
+    for x in range(1, width - 1):
+        grid[1][x] = " "
+    for y in range(1, height - 1):
+        grid[y][width - 2] = " "
+    grid[1][1] = "S"
+    grid[height - 2][width - 2] = "E"
+    return build_maze_from_symbols(["".join(row) for row in grid])
+
+
+def generate_branching_maze(width, height, seed=42, wall_density=0.30):
+    rng = random.Random(seed)
+    grid = [["#" for _ in range(width)] for _ in range(height)]
+    x, y = 1, 1
+    grid[y][x] = "S"
+    while (x, y) != (width - 2, height - 2):
+        candidates = []
+        for dx, dy in [(1, 0), (0, 1)]:
+            nx, ny = x + dx, y + dy
+            if 1 <= nx < width - 1 and 1 <= ny < height - 1:
+                candidates.append((nx, ny))
+        if not candidates:
+            break
+        x, y = rng.choice(candidates)
+        grid[y][x] = " "
+    grid[height - 2][width - 2] = "E"
+
+    # carve extra corridors and dead ends
+    for yy in range(1, height - 1):
+        for xx in range(1, width - 1):
+            if grid[yy][xx] == "#" and rng.random() > wall_density:
+                grid[yy][xx] = " "
+    grid[1][1] = "S"
+    grid[height - 2][width - 2] = "E"
+    return build_maze_from_symbols(["".join(row) for row in grid])
+
+
+def generate_no_path_maze(width, height):
+    grid = [[" " for _ in range(width)] for _ in range(height)]
+    for x in range(width):
+        grid[height // 2][x] = "#"
+    grid[1][1] = "S"
+    grid[height - 2][width - 2] = "E"
+    return build_maze_from_symbols(["".join(row) for row in grid])
+
+
+def generate_weighted_maze(width, height, seed=123):
+    rng = random.Random(seed)
+    grid = [[" " for _ in range(width)] for _ in range(height)]
+    for y in range(height):
+        for x in range(width):
+            r = rng.random()
+            if r < 0.12:
+                grid[y][x] = "#"
+            elif r < 0.25:
+                grid[y][x] = "3"
+            elif r < 0.40:
+                grid[y][x] = "2"
+            else:
+                grid[y][x] = "1"
+    # ensure path-ish
+    for x in range(width):
+        grid[1][x] = "1"
+    for y in range(1, height):
+        grid[y][width - 2] = "1"
+    grid[1][1] = "S"
+    grid[height - 2][width - 2] = "E"
+    return build_maze_from_symbols(["".join(row) for row in grid])
+
+
+def bench_one_maze(maze_name, maze, strategies, repeats=5):
+    summary_rows = []
+    raw_rows = []
+    for strategy_name, strategy_factory in strategies:
+        times, visiteds, lengths = [], [], []
+        for run in range(1, repeats + 1):
+            solver = MazeSolver(maze)
+            solver.setStrategy(strategy_factory())
+            stats = solver.solve()
+            raw_rows.append([maze_name, strategy_name, run, f"{stats.timeMs:.6f}", stats.visitedCells, stats.pathLength])
+            times.append(stats.timeMs)
+            visiteds.append(stats.visitedCells)
+            lengths.append(stats.pathLength)
+        summary_rows.append([maze_name, strategy_name, f"{mean(times):.6f}", f"{mean(visiteds):.2f}", f"{mean(lengths):.2f}", repeats])
+    return summary_rows, raw_rows
+
+
+def save_csv(path, rows):
+    with open(path, "w", newline="", encoding="utf-8") as f:
+        csv.writer(f).writerows(rows)
+
+
+def plot_summary(summary_rows):
+    by_maze = {}
+    for row in summary_rows[1:]:
+        maze_name, strategy, avg_time, avg_visited, avg_len, runs = row
+        by_maze.setdefault(maze_name, []).append((strategy, float(avg_time), float(avg_visited), float(avg_len)))
+
+    for maze_name, items in by_maze.items():
+        items.sort(key=lambda t: t[0])
+        strategies = [i[0] for i in items]
+        x = list(range(len(strategies)))
+
+        plt.figure(figsize=(8, 4))
+        plt.bar(x, [i[1] for i in items])
+        plt.xticks(x, strategies)
+        plt.ylabel("ms")
+        plt.title(f"{maze_name} — avg time")
+        plt.tight_layout()
+        plt.savefig(OUT_DIR / f"{maze_name}_time.png", dpi=150)
+        plt.close()
+
+        plt.figure(figsize=(8, 4))
+        plt.bar(x, [i[2] for i in items])
+        plt.xticks(x, strategies)
+        plt.ylabel("cells")
+        plt.title(f"{maze_name} — visited cells")
+        plt.tight_layout()
+        plt.savefig(OUT_DIR / f"{maze_name}_visited.png", dpi=150)
+        plt.close()
+
+        plt.figure(figsize=(8, 4))
+        plt.bar(x, [i[3] for i in items])
+        plt.xticks(x, strategies)
+        plt.ylabel("cells")
+        plt.title(f"{maze_name} — path length")
+        plt.tight_layout()
+        plt.savefig(OUT_DIR / f"{maze_name}_length.png", dpi=150)
+        plt.close()
+
+
+def main():
+    OUT_DIR.mkdir(exist_ok=True)
+
+    strategies = [
+        ("BFS", BFSStrategy),
+        ("DFS", DFSStrategy),
+        ("A*", AStarStrategy),
+        ("Dijkstra", DijkstraStrategy),
+    ]
+
+    mazes = [
+        ("small_10x10", generate_simple_maze(10, 10)),
+        ("medium_50x50", generate_branching_maze(50, 50)),
+        ("large_100x100", generate_branching_maze(100, 100, seed=99, wall_density=0.35)),
+        ("empty_30x30", generate_empty_maze(30, 30)),
+        ("no_path_30x30", generate_no_path_maze(30, 30)),
+        ("weighted_30x30", generate_weighted_maze(30, 30)),
+    ]
+
+    summary = [["maze", "strategy", "avg_time_ms", "avg_visited_cells", "avg_path_length", "runs"]]
+    raw = [["maze", "strategy", "run", "time_ms", "visited_cells", "path_length"]]
+
+    for maze_name, maze in mazes:
+        s_rows, r_rows = bench_one_maze(maze_name, maze, strategies, repeats=5)
+        summary.extend(s_rows)
+        raw.extend(r_rows)
+
+    save_csv(OUT_DIR / "summary.csv", summary)
+    save_csv(OUT_DIR / "raw.csv", raw)
+    plot_summary(summary)
+
+    print("Saved to", OUT_DIR.resolve())
+
+
+if __name__ == "__main__":
+    main()

petryainiyas/task2/experiment_results/raw.csv

@@ -0,0 +1,121 @@
+maze,strategy,run,time_ms,visited_cells,path_length
+small_10x10,BFS,1,0.086300,15,15
+small_10x10,BFS,2,0.061100,15,15
+small_10x10,BFS,3,0.059300,15,15
+small_10x10,BFS,4,0.058400,15,15
+small_10x10,BFS,5,0.058500,15,15
+small_10x10,DFS,1,0.073400,15,15
+small_10x10,DFS,2,0.063500,15,15
+small_10x10,DFS,3,0.062500,15,15
+small_10x10,DFS,4,0.062700,15,15
+small_10x10,DFS,5,0.070900,15,15
+small_10x10,A*,1,0.110100,15,15
+small_10x10,A*,2,0.089200,15,15
+small_10x10,A*,3,0.087800,15,15
+small_10x10,A*,4,0.087600,15,15
+small_10x10,A*,5,0.087000,15,15
+small_10x10,Dijkstra,1,0.290000,15,15
+small_10x10,Dijkstra,2,0.083300,15,15
+small_10x10,Dijkstra,3,0.091500,15,15
+small_10x10,Dijkstra,4,0.081000,15,15
+small_10x10,Dijkstra,5,0.080400,15,15
+medium_50x50,BFS,1,6.799200,1579,95
+medium_50x50,BFS,2,6.960100,1579,95
+medium_50x50,BFS,3,6.337000,1579,95
+medium_50x50,BFS,4,7.431700,1579,95
+medium_50x50,BFS,5,6.517900,1579,95
+medium_50x50,DFS,1,6.463000,1277,647
+medium_50x50,DFS,2,6.815500,1277,647
+medium_50x50,DFS,3,5.816100,1277,647
+medium_50x50,DFS,4,6.492400,1277,647
+medium_50x50,DFS,5,6.532500,1277,647
+medium_50x50,A*,1,6.940500,927,95
+medium_50x50,A*,2,7.275400,927,95
+medium_50x50,A*,3,7.062500,927,95
+medium_50x50,A*,4,7.727600,927,95
+medium_50x50,A*,5,7.321000,927,95
+medium_50x50,Dijkstra,1,11.483200,1579,95
+medium_50x50,Dijkstra,2,11.194200,1579,95
+medium_50x50,Dijkstra,3,11.255200,1579,95
+medium_50x50,Dijkstra,4,10.512500,1579,95
+medium_50x50,Dijkstra,5,10.696400,1579,95
+large_100x100,BFS,1,25.623500,5566,195
+large_100x100,BFS,2,24.348800,5566,195
+large_100x100,BFS,3,25.452600,5566,195
+large_100x100,BFS,4,30.516900,5566,195
+large_100x100,BFS,5,33.694700,5566,195
+large_100x100,DFS,1,19.415200,3543,1531
+large_100x100,DFS,2,19.919000,3543,1531
+large_100x100,DFS,3,19.104600,3543,1531
+large_100x100,DFS,4,20.000600,3543,1531
+large_100x100,DFS,5,17.840200,3543,1531
+large_100x100,A*,1,7.509300,853,195
+large_100x100,A*,2,7.221200,853,195
+large_100x100,A*,3,6.486700,853,195
+large_100x100,A*,4,6.357600,853,195
+large_100x100,A*,5,6.723800,853,195
+large_100x100,Dijkstra,1,40.782300,5571,195
+large_100x100,Dijkstra,2,41.155000,5571,195
+large_100x100,Dijkstra,3,39.456200,5571,195
+large_100x100,Dijkstra,4,41.388700,5571,195
+large_100x100,Dijkstra,5,40.962500,5571,195
+empty_30x30,BFS,1,4.143200,896,55
+empty_30x30,BFS,2,3.987000,896,55
+empty_30x30,BFS,3,3.777100,896,55
+empty_30x30,BFS,4,3.682300,896,55
+empty_30x30,BFS,5,3.737900,896,55
+empty_30x30,DFS,1,4.024200,842,815
+empty_30x30,DFS,2,4.333900,842,815
+empty_30x30,DFS,3,5.411000,842,815
+empty_30x30,DFS,4,4.677200,842,815
+empty_30x30,DFS,5,5.177400,842,815
+empty_30x30,A*,1,6.603700,784,55
+empty_30x30,A*,2,6.200600,784,55
+empty_30x30,A*,3,6.798400,784,55
+empty_30x30,A*,4,7.178500,784,55
+empty_30x30,A*,5,6.660800,784,55
+empty_30x30,Dijkstra,1,6.396000,896,55
+empty_30x30,Dijkstra,2,6.275200,896,55
+empty_30x30,Dijkstra,3,6.845700,896,55
+empty_30x30,Dijkstra,4,6.531200,896,55
+empty_30x30,Dijkstra,5,6.783400,896,55
+no_path_30x30,BFS,1,2.000100,450,0
+no_path_30x30,BFS,2,1.797900,450,0
+no_path_30x30,BFS,3,1.796200,450,0
+no_path_30x30,BFS,4,1.774100,450,0
+no_path_30x30,BFS,5,1.775200,450,0
+no_path_30x30,DFS,1,2.090400,450,0
+no_path_30x30,DFS,2,2.222600,450,0
+no_path_30x30,DFS,3,2.454300,450,0
+no_path_30x30,DFS,4,2.476200,450,0
+no_path_30x30,DFS,5,2.073700,450,0
+no_path_30x30,A*,1,3.651700,450,0
+no_path_30x30,A*,2,3.495200,450,0
+no_path_30x30,A*,3,3.754200,450,0
+no_path_30x30,A*,4,3.286800,450,0
+no_path_30x30,A*,5,3.335200,450,0
+no_path_30x30,Dijkstra,1,3.050900,450,0
+no_path_30x30,Dijkstra,2,3.109900,450,0
+no_path_30x30,Dijkstra,3,3.292500,450,0
+no_path_30x30,Dijkstra,4,3.418600,450,0
+no_path_30x30,Dijkstra,5,3.212100,450,0
+weighted_30x30,BFS,1,3.418900,788,55
+weighted_30x30,BFS,2,3.368200,788,55
+weighted_30x30,BFS,3,3.516400,788,55
+weighted_30x30,BFS,4,3.224300,788,55
+weighted_30x30,BFS,5,3.131100,788,55
+weighted_30x30,DFS,1,3.291200,693,479
+weighted_30x30,DFS,2,3.362300,693,479
+weighted_30x30,DFS,3,3.523200,693,479
+weighted_30x30,DFS,4,3.521400,693,479
+weighted_30x30,DFS,5,3.332300,693,479
+weighted_30x30,A*,1,1.181000,126,55
+weighted_30x30,A*,2,1.080200,126,55
+weighted_30x30,A*,3,1.368400,126,55
+weighted_30x30,A*,4,1.109800,126,55
+weighted_30x30,A*,5,1.079300,126,55
+weighted_30x30,Dijkstra,1,6.112700,781,55
+weighted_30x30,Dijkstra,2,5.464800,781,55
+weighted_30x30,Dijkstra,3,5.794500,781,55
+weighted_30x30,Dijkstra,4,6.171700,781,55
+weighted_30x30,Dijkstra,5,6.640500,781,55

petryainiyas/task2/experiment_results/summary.csv

@@ -0,0 +1,25 @@
+maze,strategy,avg_time_ms,avg_visited_cells,avg_path_length,runs
+small_10x10,BFS,0.064720,15.00,15.00,5
+small_10x10,DFS,0.066600,15.00,15.00,5
+small_10x10,A*,0.092340,15.00,15.00,5
+small_10x10,Dijkstra,0.125240,15.00,15.00,5
+medium_50x50,BFS,6.809180,1579.00,95.00,5
+medium_50x50,DFS,6.423900,1277.00,647.00,5
+medium_50x50,A*,7.265400,927.00,95.00,5
+medium_50x50,Dijkstra,11.028300,1579.00,95.00,5
+large_100x100,BFS,27.927300,5566.00,195.00,5
+large_100x100,DFS,19.255920,3543.00,1531.00,5
+large_100x100,A*,6.859720,853.00,195.00,5
+large_100x100,Dijkstra,40.748940,5571.00,195.00,5
+empty_30x30,BFS,3.865500,896.00,55.00,5
+empty_30x30,DFS,4.724740,842.00,815.00,5
+empty_30x30,A*,6.688400,784.00,55.00,5
+empty_30x30,Dijkstra,6.566300,896.00,55.00,5
+no_path_30x30,BFS,1.828700,450.00,0.00,5
+no_path_30x30,DFS,2.263440,450.00,0.00,5
+no_path_30x30,A*,3.504620,450.00,0.00,5
+no_path_30x30,Dijkstra,3.216800,450.00,0.00,5
+weighted_30x30,BFS,3.331780,788.00,55.00,5
+weighted_30x30,DFS,3.406080,693.00,479.00,5
+weighted_30x30,A*,1.163740,126.00,55.00,5
+weighted_30x30,Dijkstra,6.036840,781.00,55.00,5

petryainiyas/task2/main.py

@@ -0,0 +1,59 @@
+from builders.text_file_maze_builder import TextFileMazeBuilder
+from core.player import Player
+from observer.console_view import ConsoleView
+from solver.maze_solver import MazeSolver
+from strategies.astar_strategy import AStarStrategy
+from strategies.bfs_strategy import BFSStrategy
+from strategies.dfs_strategy import DFSStrategy
+from controller.game_controller import GameController
+
+
+from pathlib import Path
+
+BASE_DIR = Path(__file__).resolve().parent
+
+
+def run_demo():
+    builder = TextFileMazeBuilder()
+    maze = builder.buildFromFile(str(BASE_DIR / "mazes" / "maze_small.txt"))
+
+    view = ConsoleView()
+    view.update({"type": "maze_loaded", "message": "Maze loaded"})
+    view.render(maze)
+
+    solver = MazeSolver(maze)
+    solver.addObserver(view)
+
+    for strategy in (BFSStrategy(), DFSStrategy(), AStarStrategy()):
+        solver.setStrategy(strategy)
+        stats = solver.solve()
+
+        print()
+        print(f"=== {strategy.name} ===")
+        print(f"Time: {stats.timeMs:.3f} ms")
+        print(f"Visited cells: {stats.visitedCells}")
+        print(f"Path length: {stats.pathLength}")
+        print(f"Path found: {'yes' if stats.found else 'no'}")
+
+        view.render(maze, path=stats.path)
+
+    player = Player(maze.startCell)
+    controller = GameController(maze, player, view)
+
+    print("Manual mode: W/A/S/D move, Z undo, Q quit")
+    view.render(maze, player_position=player.currentCell)
+
+    while True:
+        cmd = input("Command: ").strip().upper()
+        if cmd == "Q":
+            break
+        if cmd == "Z":
+            controller.undo()
+        elif cmd in {"W", "A", "S", "D"}:
+            controller.move(cmd)
+        else:
+            print("Unknown command")
+
+
+if __name__ == "__main__":
+    run_demo()

petryainiyas/task2/mazes/maze_empty.txt

@@ -0,0 +1,9 @@
+S                          
+
+
+
+
+
+
+
+                         E 

petryainiyas/task2/mazes/maze_large.txt

@@ -0,0 +1,11 @@
+####################################################################################################
+#S   #     #        #     #    #      #         #      #   #    #   #    #   #   #    #         E#
+# # ### ### # ###### # ### # ## # #### # ####### # #### # # ### ## # ## # # ## # ## # ##### ### ##
+# #     #   #      # #   # #  # #    # #       # #    # # #   #    #    # #    # #    #   #   #  #
+# ##### # ######## # ### # ## # #### # ####### ## ### # # #### ####### ## ####### ####### # ### ##
+#     # #      #   #     #    #      #       #    #   # #      #     # #      #   #     # #   #  #
+### # # ###### # ########### ########### ### ####### # ####### ### # # ###### # ### ### # ### ####
+#   # #      # #     #     #         #   #   #    #   #     #   #   # #      #   #   #   #   #    #
+# ### ###### # ##### # ### # ####### # ### ### ## # ###### # ### # ### ###### # ### # ### ### ## #
+#                 #           #       #           #           #        #               #           #
+####################################################################################################

petryainiyas/task2/mazes/maze_medium.txt

@@ -0,0 +1,11 @@
+##################################################
+#S   #     #        #     #    #      #         E#
+# # ### ### # ###### # ### # ## # #### # ####### ##
+# #     #   #      # #   # #  # #    # #       #  #
+# ##### # ######## # ### # ## # #### # ####### ## #
+#     # #      #   #     #    #      #       #    #
+### # # ###### # ########### ########### ### ######
+#   # #      # #     #     #         #   #   #    #
+# ### ###### # ##### # ### # ####### # ### ### ## #
+#                 #           #       #           #
+##################################################

petryainiyas/task2/mazes/maze_no_path.txt

@@ -0,0 +1,9 @@
+##########
+#S       #
+# ###### #
+#      # #
+##########
+#      #E#
+# ###### #
+#        #
+##########

petryainiyas/task2/mazes/maze_small.txt

@@ -0,0 +1,7 @@
+##########
+#S     #E#
+# ## # # ##
+#    #   #
+# #### # #
+#      # #
+##########

petryainiyas/task2/mazes/maze_weighted.txt

@@ -0,0 +1,10 @@
+1111111111111111111111111111
+1S11111111111111111111111111
+1111111111111111111111111111
+1111111111111111111111111111
+1111111111111222222222222111
+1111111111111222222222222111
+1111111111111333333333333111
+1111111111111333333333333111
+111111111111111111111111111E
+1111111111111111111111111111

petryainiyas/task2/observer/console_view.py

@@ -0,0 +1,26 @@
+import os
+from observer.observer import Observer
+
+
+class ConsoleView(Observer):
+    def update(self, event):
+        if isinstance(event, str):
+            print(f"[EVENT] {event}")
+        elif isinstance(event, dict):
+            event_type = event.get("type", "unknown")
+            if event_type == "search_finished":
+                stats = event.get("stats")
+                print(f"[EVENT] search finished: {stats}")
+            else:
+                print(f"[EVENT] {event_type}: {event}")
+        else:
+            print("[EVENT] unknown")
+
+    def clear(self):
+        os.system("cls" if os.name == "nt" else "clear")
+
+    def render(self, maze, player_position=None, path=None, clear_screen=False):
+        if clear_screen:
+            self.clear()
+        print(maze.render(player_position=player_position, path=path))
+        print()

petryainiyas/task2/observer/observer.py

@@ -0,0 +1,7 @@
+from abc import ABC, abstractmethod
+
+
+class Observer(ABC):
+    @abstractmethod
+    def update(self, event):
+        raise NotImplementedError

petryainiyas/task2/requirements.txt

@@ -0,0 +1 @@
+matplotlib

petryainiyas/task2/solver/maze_solver.py

@@ -0,0 +1,50 @@
+import time
+from core.search_stats import SearchStats
+
+
+class MazeSolver:
+    def __init__(self, maze, strategy=None):
+        self.maze = maze
+        self.strategy = strategy
+        self.observers = []
+
+    def setStrategy(self, strategy):
+        self.strategy = strategy
+
+    def addObserver(self, observer):
+        if observer not in self.observers:
+            self.observers.append(observer)
+
+    def removeObserver(self, observer):
+        if observer in self.observers:
+            self.observers.remove(observer)
+
+    def notify(self, event):
+        for observer in self.observers:
+            observer.update(event)
+
+    def solve(self):
+        if self.strategy is None:
+            raise ValueError("Strategy is not set")
+        self.notify({"type": "search_started", "strategy": self.strategy.name})
+
+        start_time = time.perf_counter()
+        path = self.strategy.findPath(self.maze, self.maze.startCell, self.maze.exitCell)
+        end_time = time.perf_counter()
+
+        stats = SearchStats(
+            timeMs=(end_time - start_time) * 1000.0,
+            visitedCells=getattr(self.strategy, "visitedCount", 0),
+            pathLength=len(path),
+            path=path,
+            found=bool(path),
+            algorithm=getattr(self.strategy, "name", "")
+        )
+
+        if stats.found:
+            self.notify({"type": "path_found", "strategy": stats.algorithm, "length": stats.pathLength})
+        else:
+            self.notify({"type": "path_not_found", "strategy": stats.algorithm})
+
+        self.notify({"type": "search_finished", "stats": stats})
+        return stats

petryainiyas/task2/strategies/astar_strategy.py

@@ -0,0 +1,45 @@
+import heapq
+from strategies.pathfinding_strategy import PathFindingStrategy
+
+
+class AStarStrategy(PathFindingStrategy):
+    name = "A*"
+
+    def heuristic(self, cell, exitCell):
+        return abs(cell.x - exitCell.x) + abs(cell.y - exitCell.y)
+
+    def findPath(self, maze, start, exitCell):
+        self.visitedCount = 0
+        if start is None or exitCell is None:
+            return []
+
+        open_set = []
+        heapq.heappush(open_set, (0, 0, start.x, start.y, start))
+        parent = {}
+        g_score = {(start.x, start.y): 0}
+        closed = set()
+
+        while open_set:
+            f_score, current_g, _, _, current = heapq.heappop(open_set)
+            pos = (current.x, current.y)
+
+            if pos in closed:
+                continue
+
+            closed.add(pos)
+            self.visitedCount += 1
+
+            if current.x == exitCell.x and current.y == exitCell.y:
+                return self._restore_path(parent, start, exitCell)
+
+            for neighbor in maze.getNeighbors(current):
+                npos = (neighbor.x, neighbor.y)
+                tentative_g = current_g + getattr(neighbor, "weight", 1)
+
+                if tentative_g < g_score.get(npos, float("inf")):
+                    g_score[npos] = tentative_g
+                    parent[npos] = current
+                    new_f = tentative_g + self.heuristic(neighbor, exitCell)
+                    heapq.heappush(open_set, (new_f, tentative_g, neighbor.x, neighbor.y, neighbor))
+
+        return []

petryainiyas/task2/strategies/bfs_strategy.py

@@ -0,0 +1,31 @@
+from collections import deque
+from strategies.pathfinding_strategy import PathFindingStrategy
+
+
+class BFSStrategy(PathFindingStrategy):
+    name = "BFS"
+
+    def findPath(self, maze, start, exitCell):
+        self.visitedCount = 0
+        if start is None or exitCell is None:
+            return []
+
+        queue = deque([start])
+        visited = {(start.x, start.y)}
+        parent = {}
+
+        while queue:
+            current = queue.popleft()
+            self.visitedCount += 1
+
+            if current.x == exitCell.x and current.y == exitCell.y:
+                return self._restore_path(parent, start, exitCell)
+
+            for neighbor in maze.getNeighbors(current):
+                pos = (neighbor.x, neighbor.y)
+                if pos not in visited:
+                    visited.add(pos)
+                    parent[pos] = current
+                    queue.append(neighbor)
+
+        return []

petryainiyas/task2/strategies/dfs_strategy.py

@@ -0,0 +1,35 @@
+from strategies.pathfinding_strategy import PathFindingStrategy
+
+
+class DFSStrategy(PathFindingStrategy):
+    name = "DFS"
+
+    def findPath(self, maze, start, exitCell):
+        self.visitedCount = 0
+        if start is None or exitCell is None:
+            return []
+
+        stack = [start]
+        visited = set()
+        parent = {}
+
+        while stack:
+            current = stack.pop()
+            pos = (current.x, current.y)
+            if pos in visited:
+                continue
+
+            visited.add(pos)
+            self.visitedCount += 1
+
+            if current.x == exitCell.x and current.y == exitCell.y:
+                return self._restore_path(parent, start, exitCell)
+
+            neighbors = maze.getNeighbors(current)
+            for neighbor in reversed(neighbors):
+                npos = (neighbor.x, neighbor.y)
+                if npos not in visited:
+                    parent[npos] = current
+                    stack.append(neighbor)
+
+        return []

petryainiyas/task2/strategies/dijkstra_strategy.py

@@ -0,0 +1,41 @@
+import heapq
+from strategies.pathfinding_strategy import PathFindingStrategy
+
+
+class DijkstraStrategy(PathFindingStrategy):
+    name = "Dijkstra"
+
+    def findPath(self, maze, start, exitCell):
+        self.visitedCount = 0
+        if start is None or exitCell is None:
+            return []
+
+        pq = [(0, start.x, start.y, start)]
+        dist = {(start.x, start.y): 0}
+        parent = {}
+        closed = set()
+
+        while pq:
+            current_cost, _, _, current = heapq.heappop(pq)
+            pos = (current.x, current.y)
+
+            if pos in closed:
+                continue
+
+            closed.add(pos)
+            self.visitedCount += 1
+
+            if current.x == exitCell.x and current.y == exitCell.y:
+                return self._restore_path(parent, start, exitCell)
+
+            for neighbor in maze.getNeighbors(current):
+                npos = (neighbor.x, neighbor.y)
+                step_cost = getattr(neighbor, "weight", 1)
+                new_cost = current_cost + step_cost
+
+                if new_cost < dist.get(npos, float("inf")):
+                    dist[npos] = new_cost
+                    parent[npos] = current
+                    heapq.heappush(pq, (new_cost, neighbor.x, neighbor.y, neighbor))
+
+        return []

petryainiyas/task2/strategies/pathfinding_strategy.py

@@ -0,0 +1,30 @@
+from abc import ABC, abstractmethod
+
+
+class PathFindingStrategy(ABC):
+    name = "Base"
+
+    def __init__(self):
+        self.visitedCount = 0
+
+    @abstractmethod
+    def findPath(self, maze, start, exitCell):
+        raise NotImplementedError
+
+    def _restore_path(self, parent, start, exitCell):
+        if exitCell is None or start is None:
+            return []
+
+        path = []
+        current = exitCell
+
+        while True:
+            path.append(current)
+            if current.x == start.x and current.y == start.y:
+                break
+            current = parent.get((current.x, current.y))
+            if current is None:
+                return []
+
+        path.reverse()
+        return path