diff --git a/prep exercises/laptop-allocation/laptops.py b/prep exercises/laptop-allocation/laptops.py
new file mode 100644
index 0000000..0b0b635
--- /dev/null
+++ b/prep exercises/laptop-allocation/laptops.py	
@@ -0,0 +1,77 @@
+from dataclasses import dataclass
+from enum import Enum
+from functools import lru_cache
+from typing import Dict, List, Tuple
+
+class OperatingSystem(Enum):
+    MACOS = "macOS"
+    ARCH = "Arch Linux"
+    UBUNTU = "Ubuntu"
+    WINDOWS = "windows"
+
+@dataclass(frozen=True)
+class Person:
+    name: str
+    age: int
+    preferred_operating_systems: Tuple[OperatingSystem, ...]
+
+    def __post_init__(self) -> None:
+        object.__setattr__(
+            self,
+            "preferred_operating_systems",
+            tuple(self.preferred_operating_systems),
+        )
+
+@dataclass(frozen=True)
+class Laptop:
+    id: int
+    manufacturer: str
+    model: str
+    screen_size_in_inches: float
+    operating_system: OperatingSystem
+
+def sadness_for_allocation(person: Person, laptop: Laptop) -> int:
+    try:
+        return person.preferred_operating_systems.index(laptop.operating_system)
+    except ValueError:
+        return 100
+
+
+def allocate_laptops(people: List[Person], laptops: List[Laptop]) -> Dict[Person, Laptop]:
+    if len(laptops) < len(people):
+        raise ValueError("Not enough laptops to allocate exactly one per person")
+
+    people_tuple: Tuple[Person, ...] = tuple(people)
+    laptops_tuple: Tuple[Laptop, ...] = tuple(laptops)
+
+    @lru_cache(maxsize=None)
+    def best_from(person_index: int, used_mask: int) -> Tuple[int, Tuple[int, ...]]:
+        if person_index == len(people_tuple):
+            return 0, tuple()
+
+        best_total_sadness = float("inf")
+        best_choice: Tuple[int, ...] = tuple()
+
+        for laptop_index, laptop in enumerate(laptops_tuple):
+            if used_mask & (1 << laptop_index):
+                continue
+
+            current_sadness = sadness_for_allocation(people_tuple[person_index], laptop)
+            remaining_sadness, remaining_choices = best_from(
+                person_index + 1,
+                used_mask | (1 << laptop_index),
+            )
+            candidate_total = current_sadness + remaining_sadness
+
+            if candidate_total < best_total_sadness:
+                best_total_sadness = candidate_total
+                best_choice = (laptop_index,) + remaining_choices
+
+        return best_total_sadness, best_choice
+
+    _, selected_laptop_indexes = best_from(0, 0)
+
+    return {
+        person: laptops_tuple[laptop_index]
+        for person, laptop_index in zip(people_tuple, selected_laptop_indexes)
+    }
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