reasoning-gym/tests/test_word_sequence_reversal.py

75 lines
2.6 KiB
Python

import pytest
from reasoning_gym.algorithmic.word_sequence_reversal import WordSequenceReversalConfig, WordSequenceReversalDataset
def test_word_sequence_reversal_config_validation():
"""Test that invalid configs raise appropriate errors"""
with pytest.raises(AssertionError):
config = WordSequenceReversalConfig(min_words=0)
config.validate()
with pytest.raises(AssertionError):
config = WordSequenceReversalConfig(min_words=10, max_words=5)
config.validate()
def test_word_sequence_reversal_dataset_deterministic():
"""Test that dataset generates same items with same seed"""
config = WordSequenceReversalConfig(seed=42, size=10)
dataset1 = WordSequenceReversalDataset(config)
dataset2 = WordSequenceReversalDataset(config)
for i in range(len(dataset1)):
assert dataset1[i] == dataset2[i]
def test_word_sequence_reversal_dataset_items():
"""Test basic properties of generated items"""
config = WordSequenceReversalConfig(min_words=3, max_words=6, size=10, seed=42)
dataset = WordSequenceReversalDataset(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 "num_words" in item["metadata"]
assert "words" in item["metadata"]
# Verify word count constraints
words = item["metadata"]["words"]
assert len(words) >= config.min_words
assert len(words) <= config.max_words
# Verify reversal is correct
question_words = [w.strip() for w in item["question"].split(":")[1].strip().split(",")]
answer_words = item["answer"].split(", ")
assert answer_words == list(reversed(question_words))
def test_word_sequence_reversal_dataset_iteration():
"""Test that iteration respects dataset size"""
config = WordSequenceReversalConfig(size=5, seed=42)
dataset = WordSequenceReversalDataset(config)
items = list(dataset)
assert len(items) == config.size
# Test multiple iterations yield same items
assert items == list(dataset)
def test_word_sequence_reversal_text_preprocessing():
"""Test that text preprocessing handles edge cases"""
config = WordSequenceReversalConfig(size=1, seed=42)
dataset = WordSequenceReversalDataset(config)
# Verify words were extracted from text
assert len(dataset.words) > 0
# Verify words contain only alphanumeric characters
assert all(word.isalnum() for word in dataset.words)