import unittest
from unittest.mock import MagicMock, patch
import logging
from semantica.ontology.ontology_generator import OntologyGenerator
from semantica.ontology.class_inferrer import ClassInferrer
from semantica.ontology.naming_conventions import NamingConventions
from semantica.ontology.property_generator import PropertyGenerator

class TestOntologyClasses(unittest.TestCase):

    def setUp(self):
        # Mock dependencies
        self.mock_logger = MagicMock()
        self.mock_progress_tracker = MagicMock()
        
        # Patch get_logger and get_progress_tracker
        self.logger_patcher = patch('semantica.ontology.ontology_generator.get_logger', return_value=self.mock_logger)
        self.tracker_patcher = patch('semantica.ontology.ontology_generator.get_progress_tracker', return_value=self.mock_progress_tracker)
        
        self.logger_patcher.start()
        self.tracker_patcher.start()

        # Patch for other modules as well
        self.logger_patcher_ci = patch('semantica.ontology.class_inferrer.get_logger', return_value=self.mock_logger)
        self.tracker_patcher_ci = patch('semantica.ontology.class_inferrer.get_progress_tracker', return_value=self.mock_progress_tracker)
        self.logger_patcher_ci.start()
        self.tracker_patcher_ci.start()

        self.logger_patcher_nc = patch('semantica.ontology.naming_conventions.get_logger', return_value=self.mock_logger)
        self.tracker_patcher_nc = patch('semantica.ontology.naming_conventions.get_progress_tracker', return_value=self.mock_progress_tracker)
        self.logger_patcher_nc.start()
        self.tracker_patcher_nc.start()

        self.logger_patcher_pg = patch('semantica.ontology.property_generator.get_logger', return_value=self.mock_logger)
        self.tracker_patcher_pg = patch('semantica.ontology.property_generator.get_progress_tracker', return_value=self.mock_progress_tracker)
        self.logger_patcher_pg.start()
        self.tracker_patcher_pg.start()

    def tearDown(self):
        self.logger_patcher.stop()
        self.tracker_patcher.stop()
        self.logger_patcher_ci.stop()
        self.tracker_patcher_ci.stop()
        self.logger_patcher_nc.stop()
        self.tracker_patcher_nc.stop()
        self.logger_patcher_pg.stop()
        self.tracker_patcher_pg.stop()

    def test_naming_conventions_initialization(self):
        nc = NamingConventions()
        self.assertIsInstance(nc, NamingConventions)
        
    def test_class_inferrer_initialization(self):
        ci = ClassInferrer()
        self.assertIsInstance(ci, ClassInferrer)
        self.assertEqual(ci.min_occurrences, 2)

    def test_ontology_generator_initialization(self):
        og = OntologyGenerator()
        self.assertIsInstance(og, OntologyGenerator)
        self.assertIsInstance(og.class_inferrer, ClassInferrer)

    def test_naming_conventions_pascal_case(self):
        # We need to mock _is_pascal_case and others or test them if exposed
        # Assuming internal methods are used, let's test public method
        # But we need to see if NamingConventions actually implements logic or calls external NLP tools
        # For now, let's just test instantiation and basic call if possible
        nc = NamingConventions()
        # Mocking internal checks to avoid NLP dependencies if any
        with patch.object(nc, '_is_pascal_case', return_value=True), \
             patch.object(nc, '_is_singular', return_value=True), \
             patch.object(nc, '_is_noun_phrase', return_value=True):
            is_valid, suggestion = nc.validate_class_name("Person")
            self.assertTrue(is_valid)

    def test_infer_classes_empty(self):
        ci = ClassInferrer()
        classes = ci.infer_classes([])
        self.assertEqual(classes, [])

    def test_infer_classes_basic(self):
        ci = ClassInferrer()
        # Mocking internal methods of ClassInferrer to avoid complex logic in unit test
        # We assume infer_classes calls some internal logic.
        # Let's try to feed it some data and see what happens, assuming simple logic exists
        
        entities = [
            {"type": "Person", "name": "Alice"},
            {"type": "Person", "name": "Bob"},
            {"type": "Organization", "name": "Corp"}
        ]
        
        # If infer_classes relies on min_occurrences=2, Person should be inferred, Organization might not
        # Ideally we should mock the extraction part if it's complex
        # But let's try to see if it runs
        try:
            classes = ci.infer_classes(entities)
            self.assertIsInstance(classes, list)
            # Depending on implementation, it might return class definitions
        except Exception as e:
            self.fail(f"infer_classes failed: {e}")

if __name__ == '__main__':
    unittest.main()
