"""Tests for spell backward task generation""" import pytest from reasoning_gym.algorithmic.spell_backward import SpellBackwardConfig, SpellBackwardCurriculum, SpellBackwardDataset def test_spell_backward_config_validation(): """Test that invalid configs raise appropriate errors""" with pytest.raises(AssertionError): config = SpellBackwardConfig(min_word_len=0) config.validate() with pytest.raises(AssertionError): config = SpellBackwardConfig(min_word_len=4, max_word_len=3) config.validate() def test_spell_backward_dataset_deterministic(): """Test that dataset generates same items with same seed""" config = SpellBackwardConfig(seed=42, size=10) dataset1 = SpellBackwardDataset(config) dataset2 = SpellBackwardDataset(config) for i in range(len(dataset1)): assert dataset1[i] == dataset2[i] def test_spell_backward_dataset_items(): """Test basic properties of generated items""" config = SpellBackwardConfig(min_word_len=3, size=10, seed=42) dataset = SpellBackwardDataset(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 "word" in item["metadata"] assert "word_len" in item["metadata"] # Verify word length constraint word = item["metadata"]["word"] assert len(word) >= config.min_word_len # Verify answer is correct assert item["answer"] == word[::-1] def test_spell_backward_dataset_iteration(): """Test that iteration respects dataset size""" config = SpellBackwardConfig(size=5, seed=42) dataset = SpellBackwardDataset(config) items = list(dataset) assert len(items) == config.size # Test multiple iterations yield same items assert items == list(dataset) def test_spell_backward_curriculum(): curriculum = SpellBackwardCurriculum() base_value = {"size": 150, "seed": 1} base_cfg: SpellBackwardConfig = curriculum.generate_configuration(base_value) assert base_cfg.seed == 1 assert base_cfg.size == 150 assert base_cfg.min_word_len == 3 and base_cfg.max_word_len == 3 # test incrementing attribute levels curriculum.increment_attr_level("word_len") increased_cfg = curriculum.generate_configuration(base_value) assert increased_cfg.min_word_len == 3 and increased_cfg.max_word_len == 5 # test decrementing attribute levels curriculum.decrement_attr_level("word_len") partially_decreased_cfg = curriculum.generate_configuration(base_value) assert partially_decreased_cfg.min_word_len == 3 and partially_decreased_cfg.max_word_len == 3