course schedule

tests/test_course_schedule.py

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