refactor: move some classes and functions to separate files

task6/entities.py

@@ -0,0 +1,21 @@
+from dataclasses import dataclass
+from typing import Literal
+
+
+@dataclass
+class Request:
+    request_time: int
+    plane: Plane
+
+@dataclass
+class ProcessedRequest(Request):
+    start_process_time: int
+    process_time: int
+    type_: Literal["landing", "launching"]
+
+class Plane:
+    __id_increment = 0
+
+    def __init__(self) -> None:
+        self.id = self.__id_increment
+        Plane.__id_increment += 1

task6/main.py

@@ -0,0 +1,100 @@
+from stats import Stats, finalize_waiting_stats, show_stats
+from entities import Plane, ProcessedRequest, Request
+from queues import EnforcingQueue, PermissiveQueue, Queue
+
+from numpy import random
+from typing import Final, Iterable, Optional
+
+from numpy.typing import NDArray
+
+
+def warn_about_outcoming_queue_overload(queue: Queue) -> None:
+    print(f"Outcoming queue is overloaded: {len(queue)} planes/{queue.size} planes")
+
+def reject_plane(plane: Plane) -> None:
+    stats.rejected_in_requests += 1
+    print(f"Rejected incoming plane №{plane.id}")
+
+def launch_plane(plane: Plane, stats: Stats) -> None:
+    stats.launches_count += 1
+    print(f"Launched plane №{plane.id}")
+
+def land_plane(plane: Plane, stats: Stats) -> None:
+    stats.landings_count += 1
+    print(f"Plane №{plane.id} landed")
+
+def generate_timeline(incoming_planes_per_hour: float, outcoming_planes_per_hour: float, interval_minutes: int) -> Iterable[tuple[int, int]]:
+    def _generate(planes_per_hour: float) -> NDArray:
+        return random.poisson(planes_per_hour / 60, interval_minutes)
+
+    incoming_planes_per_minute = _generate(incoming_planes_per_hour)
+    outcoming_planes_per_minute = _generate(outcoming_planes_per_hour)
+    return zip(incoming_planes_per_minute, outcoming_planes_per_minute)
+
+def process_new_request(in_queue: Queue[Request], out_queue: Queue[Request], current_time: int, process_duration: int) -> ProcessedRequest:
+    plane: Optional[Plane]
+    if in_queue:
+        request = in_queue.pop()
+        plane = request.plane
+        stats.in_waiting_time.append(current_time - request.request_time)
+        print(f"{current_time}: Processing incoming plane №{plane.id}")
+        process_type = "landing"
+    else:
+        request = out_queue.pop()
+        plane = request.plane
+        stats.out_waiting_time.append(current_time - request.request_time)
+        print(f"{current_time}: Processing outcoming plane №{plane.id}")
+        process_type = "launching"
+    return ProcessedRequest(request.request_time, request.plane, current_time, current_time + process_duration, process_type)
+
+takeoff_duration: Final[int] = int(input("Takeoff duration: ")) # minutes
+
+max_queue: Final[int] = int(input("Max queue: "))
+interval: Final[int] = int(input("Interval: ")) # minutes
+incoming_planes, outcoming_planes = map(float, input("Planes: ").split()) # per hour
+
+in_queue: Queue[Request] = EnforcingQueue[Request](max_queue)
+out_queue: Queue[Request] = PermissiveQueue[Request](max_queue, warn_about_outcoming_queue_overload)
+
+current_request: Optional[ProcessedRequest] = None
+
+stats = Stats()
+timeline = generate_timeline(5,2, interval)
+
+i = 0
+
+for i, (in_planes_count, out_planes_count) in enumerate(timeline):
+    stats.total_plane_requests += in_planes_count + out_planes_count
+    stats.in_requests += in_planes_count
+    stats.out_requests += out_planes_count
+
+    for _ in range(in_planes_count):
+        new_plane = Plane()
+        try:
+            in_queue.add(Request(i, new_plane))
+            stats.accepted_in_requests += 1
+        except IndexError:
+            reject_plane(new_plane)
+            stats.rejected_in_requests += 1
+    for _ in range(out_planes_count):
+        new_plane = Plane()
+        out_queue.add(Request(i, new_plane))
+        stats.accepted_out_requests += 1
+    
+    if not current_request:
+        if len(in_queue) or len(out_queue):
+            current_request = process_new_request(in_queue, out_queue, i, takeoff_duration)
+            continue
+        stats.sleep_minutes += 1
+    if current_request and current_request.process_time == i:
+        if current_request.type_ == "launching":
+            launch_plane(current_request.plane, stats)
+        else:
+            land_plane(current_request.plane, stats)
+        current_request = None
+
+stats.in_queued = len(in_queue)
+stats.out_queued = len(out_queue)
+
+finalize_waiting_stats(stats, in_queue, out_queue, i)
+show_stats(stats)

task6/queues.py

@@ -0,0 +1,50 @@
+from abc import ABC, abstractmethod
+from collections import deque
+from typing import Callable, Optional, Self, override
+
+
+class Queue[T](ABC):
+    def __init__(self, size: int) -> None:
+        self.size = size
+        self.queue: deque[T] = deque()
+    
+    def __len__(self) -> int:
+        return len(self.queue)
+
+    def __bool__(self) -> bool:
+        return bool(self.queue)
+
+    @abstractmethod
+    def add(self, item: T) -> None: pass
+
+    @abstractmethod
+    def pop(self) -> T: pass
+
+class PermissiveQueue[T](Queue):
+    def __init__(self, size: int, overload_function: Optional[Callable[[Self], None]] = None) -> None:
+        super().__init__(size)
+        self._on_overload = overload_function
+
+    @override
+    def add(self, item: T) -> None:
+        self.queue.append(item)
+        if self._on_overload and len(self.queue) > self.size:
+            self._on_overload(self)
+    
+    @override
+    def pop(self) -> T:
+        return self.queue.popleft()
+
+class EnforcingQueue[T](Queue):
+    def __init__(self, size: int) -> None:
+        super().__init__(size)
+
+    @override
+    def add(self, item: T) -> None:
+        if len(self.queue) >= self.size:
+            raise IndexError
+        self.queue.append(item)
+    
+    @override
+    def pop(self) -> T:
+        return self.queue.popleft()

task6/stats.py

@@ -0,0 +1,53 @@
+from dataclasses import dataclass, field
+
+from numpy import average
+
+from entities import Request
+from queues import Queue
+
+
+@dataclass
+class Stats:
+    total_plane_requests = 0
+
+    in_requests = 0
+    out_requests = 0
+
+    accepted_in_requests = 0
+    accepted_out_requests = 0
+
+    rejected_in_requests = 0
+    rejected_out_requests = 0
+
+    landings_count = 0
+    launches_count = 0
+
+    in_queued = 0
+    out_queued = 0
+
+    sleep_minutes = 0
+
+    in_waiting_time: list[float] = field(default_factory=list)
+    out_waiting_time: list[float] = field(default_factory=list)
+
+def show_stats(stats: Stats) -> None:
+    string = f"""============
+Total requests: {stats.total_plane_requests}
+In requests: {stats.in_requests}
+Out requests: {stats.out_requests}
+Accepted in requests: {stats.accepted_in_requests}
+Accepted out requests: {stats.accepted_out_requests}
+Rejected in/out: {stats.rejected_in_requests}/{stats.rejected_out_requests}
+Landings: {stats.landings_count}
+Launches: {stats.launches_count}
+Left in queues (in/out): {stats.in_queued}/{stats.out_queued}
+Sleep: {stats.sleep_minutes}
+Average waiting time (in/out): {average(stats.in_waiting_time)}/{average(stats.out_waiting_time)}
+"""
+    print(string)
+
+def finalize_waiting_stats(stats: Stats, in_queue: Queue[Request], out_queue: Queue[Request], current_time: int) -> None:
+    for item in in_queue.queue:
+        stats.in_waiting_time.append(current_time - item.request_time)
+    for item in out_queue.queue:
+        stats.out_waiting_time.append(current_time - item.request_time)

task7/main.py

@@ -0,0 +1,40 @@
+from itertools import combinations, repeat
+import random
+from typing import Any, Final, Iterable
+from collections import Counter
+
+from icecream import ic
+
+
+sets_count: Final[int] = random.randint(2, 1000)
+elements_count: Final[Iterable[int]] = (random.randint(3, 10000) for _ in repeat(None, sets_count))
+
+ic(sets_count)
+
+sets: list[set[int]] = [
+    set(
+        random.sample(range(-2_000_000_000, 2_000_000_000 + 1), count)
+    )
+    for count in elements_count
+]
+
+elements_to_sets: dict[int, list[int]] = {}
+pair_counts: Counter[tuple[int, int]] = Counter()
+
+for i, set_ in enumerate(sets):
+    for element in set_:
+        elements_to_sets.setdefault(element, list()).append(i)
+
+ic(len(elements_to_sets))
+
+for sets_ in filter(lambda x: len(x) > 1, elements_to_sets.values()):
+    pair_counts.update(combinations(sets_, 2))
+
+sets_with_most_intersections: list[tuple[Any, int]] = pair_counts.most_common(1)
+
+if sets_with_most_intersections:
+    max_intersection: int = sets_with_most_intersections[0][1]
+else:
+    max_intersection = 0
+
+print(max_intersection)

task7/naive_approach.py

@@ -0,0 +1,36 @@
+from itertools import repeat
+import random
+from typing import Final, Iterable
+
+from icecream import ic
+
+
+sets_count: Final[int] = random.randint(2, 1000)
+elements_count: Final[Iterable[int]] = (random.randint(3, 10000) for _ in repeat(None, sets_count))
+
+ic(sets_count)
+
+sets: list[set[int]] = [
+    set(
+        random.sample(range(-2_000_000_000, 2_000_000_000 + 1), count)
+    )
+    for count in elements_count
+]
+sets.sort(key=lambda x: len(x), reverse=True)
+ic(list(map(len, sets)))
+
+max_intersection = 0
+
+for i in range(len(sets) - 1):
+    if max_intersection >= len(sets[i]):
+        ic(f"break on {i}")
+        break
+    for j in range(i + 1, len(sets)):
+        if max_intersection > len(sets[j]):
+            ic(f"break on {i};{j}")
+            break
+        if (intersection := len(sets[i].intersection(sets[j]))) > max_intersection:
+            max_intersection = intersection
+            ic(max_intersection)
+
+print(max_intersection)