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127 lines
4.5 KiB
Python
127 lines
4.5 KiB
Python
"""Tests for Course Schedule puzzle generation"""
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import pytest
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from reasoning_gym.graphs.course_schedule import CourseScheduleConfig, CourseScheduleDataset
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def test_course_schedule_config_validation():
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"""Test that invalid configs raise appropriate errors"""
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(num_courses=-1) # Negative not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(num_courses=0) # Zero not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(max_num_prerequisites=-1) # Negative not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(max_num_prerequisites=0) # Zero not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(num_courses=3, max_num_prerequisites=5) # max_num_prerequisites > num_courses
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(p_solvable=-0.1) # < 0 not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(p_solvable=1.1) # > 1 not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(p_solvable=1.1) # > 1 not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(min_cycle_length=2) # < 3 not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = CourseScheduleConfig(min_cycle_length=3, max_cycle_length=2) # min_cycle_length > max_cycle_length
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config.validate()
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def test_course_schedule_dataset_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = CourseScheduleConfig(seed=42, size=10)
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dataset1 = CourseScheduleDataset(config)
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dataset2 = CourseScheduleDataset(config)
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for i in range(len(dataset1)):
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assert dataset1[i] == dataset2[i]
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def test_course_schedule_dataset_items():
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"""Test basic properties of generated items"""
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config = CourseScheduleConfig(num_courses=15, size=10, seed=42)
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dataset = CourseScheduleDataset(config)
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for i in range(len(dataset)):
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item = dataset[i]
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# Check item structure
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assert isinstance(item, dict)
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assert "question" in item
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assert "answer" in item
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assert "metadata" in item
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# Check metadata
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assert "courses" in item["metadata"]
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assert "prerequisites" in item["metadata"]
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assert "solution" in item["metadata"]
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assert "solvable" in item["metadata"]
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courses = item["metadata"]["courses"]
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prerequisites = item["metadata"]["prerequisites"]
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solvable = item["metadata"]["solvable"] # Solution dictated by p_solvable
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solution = item["metadata"]["solution"] # Solution obtained from topological sort
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# Verify metadata
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assert len(courses) == config.num_courses
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assert max(courses) == config.num_courses - 1
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assert len(prerequisites) <= config.max_num_prerequisites * config.num_courses
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assert all(len(prereq) == 2 for prereq in prerequisites)
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for course, prereq in prerequisites:
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assert course < config.num_courses
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assert prereq < config.num_courses
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assert course != prereq
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assert solution == solvable
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def test_course_schedule_dataset_iteration():
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"""Test that iteration respects dataset size"""
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config = CourseScheduleConfig(size=5, seed=42)
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dataset = CourseScheduleDataset(config)
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items = list(dataset)
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assert len(items) == config.size
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# Test multiple iterations yield same items
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assert items == list(dataset)
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def test_course_schedule_answer():
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"""Test the _can_finish method"""
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config = CourseScheduleConfig(seed=42)
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dataset = CourseScheduleDataset(config)
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prerequisites = [[0, 1]]
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assert dataset._can_finish(num_courses=2, prerequisites=prerequisites) == True
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# Direct cycle
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prerequisites = [[0, 1], [1, 0]]
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assert dataset._can_finish(num_courses=2, prerequisites=prerequisites) == False
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# Empty prerequisites
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prerequisites = []
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assert dataset._can_finish(num_courses=2, prerequisites=prerequisites) == True
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# Indirect cycle of length 3
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prerequisites = [[0, 1], [1, 2], [2, 0]]
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assert dataset._can_finish(num_courses=3, prerequisites=prerequisites) == False
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