python 37 lines · 7 steps

Weighted loot drops in Python

A small weighted-random system that rolls loot by rarity, supports unique picks, and reports true drop odds.

Explained by highlit
Intermediate weighted-random dataclasses sampling probability
1import random
2from dataclasses import dataclass
3 
4 
5@dataclass(frozen=True)
6class LootDrop:
7 name: str
8 weight: float
9 
10 
11LOOT_TABLE = [
12 LootDrop("common_potion", 60.0),
13 LootDrop("rare_sword", 25.0),
14 LootDrop("epic_shield", 12.0),
15 LootDrop("legendary_ring", 3.0),
16]
17 
18 
19def roll_loot(table=LOOT_TABLE, rolls=1):
20 weights = [drop.weight for drop in table]
21 return random.choices(table, weights=weights, k=rolls)
22 
23 
24def roll_unique_loot(table=LOOT_TABLE, count=2):
25 pool = list(table)
26 picked = []
27 while pool and len(picked) < count:
28 weights = [drop.weight for drop in pool]
29 chosen = random.choices(pool, weights=weights, k=1)[0]
30 picked.append(chosen)
31 pool.remove(chosen)
32 return picked
33 
34 
35def drop_probabilities(table=LOOT_TABLE):
36 total = sum(drop.weight for drop in table)
37 return {drop.name: drop.weight / total for drop in table}
01 / 01
STEP 01

Walkthrough

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Three takeaways
  1. 1random.choices samples with replacement using relative weights, so absolute numbers needn't sum to 100.
  2. 2Removing a chosen item from the pool turns weighted sampling into weighted sampling without replacement.
  3. 3Weights only become real probabilities once you divide each by their total.

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