test: Add comprehensive unit tests for prime factorization dataset

This commit is contained in:
Andreas Koepf (aider) 2025-01-23 22:51:20 +01:00
parent 3c1232888c
commit e6b16c484e

View file

@ -0,0 +1,107 @@
"""Tests for prime factorization task generation"""
import pytest
from reasoning_gym.arithmetic.prime_factorization import (
PrimeFactorizationConfig,
PrimeFactorizationDataset,
)
def test_prime_factorization_config_validation():
"""Test that invalid configs raise appropriate errors"""
with pytest.raises(AssertionError):
config = PrimeFactorizationConfig(min_value=1) # Too small
config.validate()
with pytest.raises(AssertionError):
config = PrimeFactorizationConfig(min_value=100, max_value=50) # max < min
config.validate()
def test_prime_factorization_dataset_deterministic():
"""Test that dataset generates same items with same seed"""
config = PrimeFactorizationConfig(seed=42, size=10)
dataset1 = PrimeFactorizationDataset(config)
dataset2 = PrimeFactorizationDataset(config)
for i in range(len(dataset1)):
assert dataset1[i] == dataset2[i]
def test_prime_factorization_dataset_items():
"""Test basic properties of generated items"""
config = PrimeFactorizationConfig(
min_value=2,
max_value=100,
size=10,
seed=42
)
dataset = PrimeFactorizationDataset(config)
for i in range(len(dataset)):
item = dataset[i]
# Check item structure
assert isinstance(item, dict)
assert "question" in item
assert "answer" in item
assert "metadata" in item
# Check metadata
assert "number" in item["metadata"]
assert "factors" in item["metadata"]
# Verify value range
number = item["metadata"]["number"]
assert config.min_value <= number <= config.max_value
# Verify factorization is correct
factors = item["metadata"]["factors"]
product = 1
for factor in factors:
product *= factor
assert product == number
# Verify factors are prime
for factor in factors:
assert is_prime(factor), f"{factor} is not prime"
# Verify answer format
assert item["answer"] == " × ".join(map(str, factors))
def test_prime_factorization_dataset_iteration():
"""Test that iteration respects dataset size"""
config = PrimeFactorizationConfig(size=5, seed=42)
dataset = PrimeFactorizationDataset(config)
items = list(dataset)
assert len(items) == config.size
# Test multiple iterations yield same items
assert items == list(dataset)
def test_prime_factorization_known_values():
"""Test factorization of known values"""
config = PrimeFactorizationConfig(
min_value=12,
max_value=12, # Force specific number
size=1,
seed=42
)
dataset = PrimeFactorizationDataset(config)
item = dataset[0]
assert item["metadata"]["number"] == 12
assert item["metadata"]["factors"] == [2, 2, 3]
assert item["answer"] == "2 × 2 × 3"
def is_prime(n: int) -> bool:
"""Helper function to check if a number is prime"""
if n < 2:
return False
for i in range(2, int(n ** 0.5) + 1):
if n % i == 0:
return False
return True