diff --git a/api/tests/unit_tests/services/dataset_collection_binding.py b/api/tests/unit_tests/services/dataset_collection_binding.py new file mode 100644 index 0000000000..2a939a5c1d --- /dev/null +++ b/api/tests/unit_tests/services/dataset_collection_binding.py @@ -0,0 +1,932 @@ +""" +Comprehensive unit tests for DatasetCollectionBindingService. + +This module contains extensive unit tests for the DatasetCollectionBindingService class, +which handles dataset collection binding operations for vector database collections. + +The DatasetCollectionBindingService provides methods for: +- Retrieving or creating dataset collection bindings by provider, model, and type +- Retrieving specific collection bindings by ID and type +- Managing collection bindings for different collection types (dataset, etc.) + +Collection bindings are used to map embedding models (provider + model name) to +specific vector database collections, allowing datasets to share collections when +they use the same embedding model configuration. + +This test suite ensures: +- Correct retrieval of existing bindings +- Proper creation of new bindings when they don't exist +- Accurate filtering by provider, model, and collection type +- Proper error handling for missing bindings +- Database transaction handling (add, commit) +- Collection name generation using Dataset.gen_collection_name_by_id + +================================================================================ +ARCHITECTURE OVERVIEW +================================================================================ + +The DatasetCollectionBindingService is a critical component in the Dify platform's +vector database management system. It serves as an abstraction layer between the +application logic and the underlying vector database collections. + +Key Concepts: +1. Collection Binding: A mapping between an embedding model configuration + (provider + model name) and a vector database collection name. This allows + multiple datasets to share the same collection when they use identical + embedding models, improving resource efficiency. + +2. Collection Type: Different types of collections can exist (e.g., "dataset", + "custom_type"). This allows for separation of collections based on their + intended use case or data structure. + +3. Provider and Model: The combination of provider_name (e.g., "openai", + "cohere", "huggingface") and model_name (e.g., "text-embedding-ada-002") + uniquely identifies an embedding model configuration. + +4. Collection Name Generation: When a new binding is created, a unique collection + name is generated using Dataset.gen_collection_name_by_id() with a UUID. + This ensures each binding has a unique collection identifier. + +================================================================================ +TESTING STRATEGY +================================================================================ + +This test suite follows a comprehensive testing strategy that covers: + +1. Happy Path Scenarios: + - Successful retrieval of existing bindings + - Successful creation of new bindings + - Proper handling of default parameters + +2. Edge Cases: + - Different collection types + - Various provider/model combinations + - Default vs explicit parameter usage + +3. Error Handling: + - Missing bindings (for get_by_id_and_type) + - Database query failures + - Invalid parameter combinations + +4. Database Interaction: + - Query construction and execution + - Transaction management (add, commit) + - Query chaining (where, order_by, first) + +5. Mocking Strategy: + - Database session mocking + - Query builder chain mocking + - UUID generation mocking + - Collection name generation mocking + +================================================================================ +""" + +""" +Import statements for the test module. + +This section imports all necessary dependencies for testing the +DatasetCollectionBindingService, including: +- unittest.mock for creating mock objects +- pytest for test framework functionality +- uuid for UUID generation (used in collection name generation) +- Models and services from the application codebase +""" + +from unittest.mock import Mock, patch + +import pytest + +from models.dataset import Dataset, DatasetCollectionBinding +from services.dataset_service import DatasetCollectionBindingService + +# ============================================================================ +# Test Data Factory +# ============================================================================ +# The Test Data Factory pattern is used here to centralize the creation of +# test objects and mock instances. This approach provides several benefits: +# +# 1. Consistency: All test objects are created using the same factory methods, +# ensuring consistent structure across all tests. +# +# 2. Maintainability: If the structure of DatasetCollectionBinding or Dataset +# changes, we only need to update the factory methods rather than every +# individual test. +# +# 3. Reusability: Factory methods can be reused across multiple test classes, +# reducing code duplication. +# +# 4. Readability: Tests become more readable when they use descriptive factory +# method calls instead of complex object construction logic. +# +# ============================================================================ + + +class DatasetCollectionBindingTestDataFactory: + """ + Factory class for creating test data and mock objects for dataset collection binding tests. + + This factory provides static methods to create mock objects for: + - DatasetCollectionBinding instances + - Database query results + - Collection name generation results + + The factory methods help maintain consistency across tests and reduce + code duplication when setting up test scenarios. + """ + + @staticmethod + def create_collection_binding_mock( + binding_id: str = "binding-123", + provider_name: str = "openai", + model_name: str = "text-embedding-ada-002", + collection_name: str = "collection-abc", + collection_type: str = "dataset", + created_at=None, + **kwargs, + ) -> Mock: + """ + Create a mock DatasetCollectionBinding with specified attributes. + + Args: + binding_id: Unique identifier for the binding + provider_name: Name of the embedding model provider (e.g., "openai", "cohere") + model_name: Name of the embedding model (e.g., "text-embedding-ada-002") + collection_name: Name of the vector database collection + collection_type: Type of collection (default: "dataset") + created_at: Optional datetime for creation timestamp + **kwargs: Additional attributes to set on the mock + + Returns: + Mock object configured as a DatasetCollectionBinding instance + """ + binding = Mock(spec=DatasetCollectionBinding) + binding.id = binding_id + binding.provider_name = provider_name + binding.model_name = model_name + binding.collection_name = collection_name + binding.type = collection_type + binding.created_at = created_at + for key, value in kwargs.items(): + setattr(binding, key, value) + return binding + + @staticmethod + def create_dataset_mock( + dataset_id: str = "dataset-123", + **kwargs, + ) -> Mock: + """ + Create a mock Dataset for testing collection name generation. + + Args: + dataset_id: Unique identifier for the dataset + **kwargs: Additional attributes to set on the mock + + Returns: + Mock object configured as a Dataset instance + """ + dataset = Mock(spec=Dataset) + dataset.id = dataset_id + for key, value in kwargs.items(): + setattr(dataset, key, value) + return dataset + + +# ============================================================================ +# Tests for get_dataset_collection_binding +# ============================================================================ + + +class TestDatasetCollectionBindingServiceGetBinding: + """ + Comprehensive unit tests for DatasetCollectionBindingService.get_dataset_collection_binding method. + + This test class covers the main collection binding retrieval/creation functionality, + including various provider/model combinations, collection types, and edge cases. + + The get_dataset_collection_binding method: + 1. Queries for existing binding by provider_name, model_name, and collection_type + 2. Orders results by created_at (ascending) and takes the first match + 3. If no binding exists, creates a new one with: + - The provided provider_name and model_name + - A generated collection_name using Dataset.gen_collection_name_by_id + - The provided collection_type + 4. Adds the new binding to the database session and commits + 5. Returns the binding (either existing or newly created) + + Test scenarios include: + - Retrieving existing bindings + - Creating new bindings when none exist + - Different collection types + - Database transaction handling + - Collection name generation + """ + + @pytest.fixture + def mock_db_session(self): + """ + Mock database session for testing database operations. + + Provides a mocked database session that can be used to verify: + - Query construction and execution + - Add operations for new bindings + - Commit operations for transaction completion + + The mock is configured to return a query builder that supports + chaining operations like .where(), .order_by(), and .first(). + """ + with patch("services.dataset_service.db.session") as mock_db: + yield mock_db + + def test_get_dataset_collection_binding_existing_binding_success(self, mock_db_session): + """ + Test successful retrieval of an existing collection binding. + + Verifies that when a binding already exists in the database for the given + provider, model, and collection type, the method returns the existing binding + without creating a new one. + + This test ensures: + - The query is constructed correctly with all three filters + - Results are ordered by created_at + - The first matching binding is returned + - No new binding is created (db.session.add is not called) + - No commit is performed (db.session.commit is not called) + """ + # Arrange + provider_name = "openai" + model_name = "text-embedding-ada-002" + collection_type = "dataset" + + existing_binding = DatasetCollectionBindingTestDataFactory.create_collection_binding_mock( + binding_id="binding-123", + provider_name=provider_name, + model_name=model_name, + collection_type=collection_type, + ) + + # Mock the query chain: query().where().order_by().first() + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = existing_binding + mock_db_session.query.return_value = mock_query + + # Act + result = DatasetCollectionBindingService.get_dataset_collection_binding( + provider_name=provider_name, model_name=model_name, collection_type=collection_type + ) + + # Assert + assert result == existing_binding + assert result.id == "binding-123" + assert result.provider_name == provider_name + assert result.model_name == model_name + assert result.type == collection_type + + # Verify query was constructed correctly + # The query should be constructed with DatasetCollectionBinding as the model + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + + # Verify the where clause was applied to filter by provider, model, and type + mock_query.where.assert_called_once() + + # Verify the results were ordered by created_at (ascending) + # This ensures we get the oldest binding if multiple exist + mock_where.order_by.assert_called_once() + + # Verify no new binding was created + # Since an existing binding was found, we should not create a new one + mock_db_session.add.assert_not_called() + + # Verify no commit was performed + # Since no new binding was created, no database transaction is needed + mock_db_session.commit.assert_not_called() + + def test_get_dataset_collection_binding_create_new_binding_success(self, mock_db_session): + """ + Test successful creation of a new collection binding when none exists. + + Verifies that when no binding exists in the database for the given + provider, model, and collection type, the method creates a new binding + with a generated collection name and commits it to the database. + + This test ensures: + - The query returns None (no existing binding) + - A new DatasetCollectionBinding is created with correct attributes + - Dataset.gen_collection_name_by_id is called to generate collection name + - The new binding is added to the database session + - The transaction is committed + - The newly created binding is returned + """ + # Arrange + provider_name = "cohere" + model_name = "embed-english-v3.0" + collection_type = "dataset" + generated_collection_name = "collection-generated-xyz" + + # Mock the query chain to return None (no existing binding) + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = None # No existing binding + mock_db_session.query.return_value = mock_query + + # Mock Dataset.gen_collection_name_by_id to return a generated name + with patch("services.dataset_service.Dataset.gen_collection_name_by_id") as mock_gen_name: + mock_gen_name.return_value = generated_collection_name + + # Mock uuid.uuid4 for the collection name generation + mock_uuid = "test-uuid-123" + with patch("services.dataset_service.uuid.uuid4", return_value=mock_uuid): + # Act + result = DatasetCollectionBindingService.get_dataset_collection_binding( + provider_name=provider_name, model_name=model_name, collection_type=collection_type + ) + + # Assert + assert result is not None + assert result.provider_name == provider_name + assert result.model_name == model_name + assert result.type == collection_type + assert result.collection_name == generated_collection_name + + # Verify Dataset.gen_collection_name_by_id was called with the generated UUID + # This method generates a unique collection name based on the UUID + # The UUID is converted to string before passing to the method + mock_gen_name.assert_called_once_with(str(mock_uuid)) + + # Verify new binding was added to the database session + # The add method should be called exactly once with the new binding instance + mock_db_session.add.assert_called_once() + + # Extract the binding that was added to verify its properties + added_binding = mock_db_session.add.call_args[0][0] + + # Verify the added binding is an instance of DatasetCollectionBinding + # This ensures we're creating the correct type of object + assert isinstance(added_binding, DatasetCollectionBinding) + + # Verify all the binding properties are set correctly + # These should match the input parameters to the method + assert added_binding.provider_name == provider_name + assert added_binding.model_name == model_name + assert added_binding.type == collection_type + + # Verify the collection name was set from the generated name + # This ensures the binding has a valid collection identifier + assert added_binding.collection_name == generated_collection_name + + # Verify the transaction was committed + # This ensures the new binding is persisted to the database + mock_db_session.commit.assert_called_once() + + def test_get_dataset_collection_binding_different_collection_type(self, mock_db_session): + """ + Test retrieval with a different collection type (not "dataset"). + + Verifies that the method correctly filters by collection_type, allowing + different types of collections to coexist with the same provider/model + combination. + + This test ensures: + - Collection type is properly used as a filter in the query + - Different collection types can have separate bindings + - The correct binding is returned based on type + """ + # Arrange + provider_name = "openai" + model_name = "text-embedding-ada-002" + collection_type = "custom_type" + + existing_binding = DatasetCollectionBindingTestDataFactory.create_collection_binding_mock( + binding_id="binding-456", + provider_name=provider_name, + model_name=model_name, + collection_type=collection_type, + ) + + # Mock the query chain + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = existing_binding + mock_db_session.query.return_value = mock_query + + # Act + result = DatasetCollectionBindingService.get_dataset_collection_binding( + provider_name=provider_name, model_name=model_name, collection_type=collection_type + ) + + # Assert + assert result == existing_binding + assert result.type == collection_type + + # Verify query was constructed with the correct type filter + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + mock_query.where.assert_called_once() + + def test_get_dataset_collection_binding_default_collection_type(self, mock_db_session): + """ + Test retrieval with default collection type ("dataset"). + + Verifies that when collection_type is not provided, it defaults to "dataset" + as specified in the method signature. + + This test ensures: + - The default value "dataset" is used when type is not specified + - The query correctly filters by the default type + """ + # Arrange + provider_name = "openai" + model_name = "text-embedding-ada-002" + # collection_type defaults to "dataset" in method signature + + existing_binding = DatasetCollectionBindingTestDataFactory.create_collection_binding_mock( + binding_id="binding-789", + provider_name=provider_name, + model_name=model_name, + collection_type="dataset", # Default type + ) + + # Mock the query chain + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = existing_binding + mock_db_session.query.return_value = mock_query + + # Act - call without specifying collection_type (uses default) + result = DatasetCollectionBindingService.get_dataset_collection_binding( + provider_name=provider_name, model_name=model_name + ) + + # Assert + assert result == existing_binding + assert result.type == "dataset" + + # Verify query was constructed correctly + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + + def test_get_dataset_collection_binding_different_provider_model_combination(self, mock_db_session): + """ + Test retrieval with different provider/model combinations. + + Verifies that bindings are correctly filtered by both provider_name and + model_name, ensuring that different model combinations have separate bindings. + + This test ensures: + - Provider and model are both used as filters + - Different combinations result in different bindings + - The correct binding is returned for each combination + """ + # Arrange + provider_name = "huggingface" + model_name = "sentence-transformers/all-MiniLM-L6-v2" + collection_type = "dataset" + + existing_binding = DatasetCollectionBindingTestDataFactory.create_collection_binding_mock( + binding_id="binding-hf-123", + provider_name=provider_name, + model_name=model_name, + collection_type=collection_type, + ) + + # Mock the query chain + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = existing_binding + mock_db_session.query.return_value = mock_query + + # Act + result = DatasetCollectionBindingService.get_dataset_collection_binding( + provider_name=provider_name, model_name=model_name, collection_type=collection_type + ) + + # Assert + assert result == existing_binding + assert result.provider_name == provider_name + assert result.model_name == model_name + + # Verify query filters were applied correctly + # The query should filter by both provider_name and model_name + # This ensures different model combinations have separate bindings + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + + # Verify the where clause was applied with all three filters: + # - provider_name filter + # - model_name filter + # - collection_type filter + mock_query.where.assert_called_once() + + +# ============================================================================ +# Tests for get_dataset_collection_binding_by_id_and_type +# ============================================================================ +# This section contains tests for the get_dataset_collection_binding_by_id_and_type +# method, which retrieves a specific collection binding by its ID and type. +# +# Key differences from get_dataset_collection_binding: +# 1. This method queries by ID and type, not by provider/model/type +# 2. This method does NOT create a new binding if one doesn't exist +# 3. This method raises ValueError if the binding is not found +# 4. This method is typically used when you already know the binding ID +# +# Use cases: +# - Retrieving a binding that was previously created +# - Validating that a binding exists before using it +# - Accessing binding metadata when you have the ID +# +# ============================================================================ + + +class TestDatasetCollectionBindingServiceGetBindingByIdAndType: + """ + Comprehensive unit tests for DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type method. + + This test class covers collection binding retrieval by ID and type, + including success scenarios and error handling for missing bindings. + + The get_dataset_collection_binding_by_id_and_type method: + 1. Queries for a binding by collection_binding_id and collection_type + 2. Orders results by created_at (ascending) and takes the first match + 3. If no binding exists, raises ValueError("Dataset collection binding not found") + 4. Returns the found binding + + Unlike get_dataset_collection_binding, this method does NOT create a new + binding if one doesn't exist - it only retrieves existing bindings. + + Test scenarios include: + - Successful retrieval of existing bindings + - Error handling for missing bindings + - Different collection types + - Default collection type behavior + """ + + @pytest.fixture + def mock_db_session(self): + """ + Mock database session for testing database operations. + + Provides a mocked database session that can be used to verify: + - Query construction with ID and type filters + - Ordering by created_at + - First result retrieval + + The mock is configured to return a query builder that supports + chaining operations like .where(), .order_by(), and .first(). + """ + with patch("services.dataset_service.db.session") as mock_db: + yield mock_db + + def test_get_dataset_collection_binding_by_id_and_type_success(self, mock_db_session): + """ + Test successful retrieval of a collection binding by ID and type. + + Verifies that when a binding exists in the database with the given + ID and collection type, the method returns the binding. + + This test ensures: + - The query is constructed correctly with ID and type filters + - Results are ordered by created_at + - The first matching binding is returned + - No error is raised + """ + # Arrange + collection_binding_id = "binding-123" + collection_type = "dataset" + + existing_binding = DatasetCollectionBindingTestDataFactory.create_collection_binding_mock( + binding_id=collection_binding_id, + provider_name="openai", + model_name="text-embedding-ada-002", + collection_type=collection_type, + ) + + # Mock the query chain: query().where().order_by().first() + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = existing_binding + mock_db_session.query.return_value = mock_query + + # Act + result = DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type( + collection_binding_id=collection_binding_id, collection_type=collection_type + ) + + # Assert + assert result == existing_binding + assert result.id == collection_binding_id + assert result.type == collection_type + + # Verify query was constructed correctly + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + mock_query.where.assert_called_once() + mock_where.order_by.assert_called_once() + + def test_get_dataset_collection_binding_by_id_and_type_not_found_error(self, mock_db_session): + """ + Test error handling when binding is not found. + + Verifies that when no binding exists in the database with the given + ID and collection type, the method raises a ValueError with the + message "Dataset collection binding not found". + + This test ensures: + - The query returns None (no existing binding) + - ValueError is raised with the correct message + - No binding is returned + """ + # Arrange + collection_binding_id = "non-existent-binding" + collection_type = "dataset" + + # Mock the query chain to return None (no existing binding) + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = None # No existing binding + mock_db_session.query.return_value = mock_query + + # Act & Assert + with pytest.raises(ValueError, match="Dataset collection binding not found"): + DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type( + collection_binding_id=collection_binding_id, collection_type=collection_type + ) + + # Verify query was attempted + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + mock_query.where.assert_called_once() + + def test_get_dataset_collection_binding_by_id_and_type_different_collection_type(self, mock_db_session): + """ + Test retrieval with a different collection type. + + Verifies that the method correctly filters by collection_type, ensuring + that bindings with the same ID but different types are treated as + separate entities. + + This test ensures: + - Collection type is properly used as a filter in the query + - Different collection types can have separate bindings with same ID + - The correct binding is returned based on type + """ + # Arrange + collection_binding_id = "binding-456" + collection_type = "custom_type" + + existing_binding = DatasetCollectionBindingTestDataFactory.create_collection_binding_mock( + binding_id=collection_binding_id, + provider_name="cohere", + model_name="embed-english-v3.0", + collection_type=collection_type, + ) + + # Mock the query chain + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = existing_binding + mock_db_session.query.return_value = mock_query + + # Act + result = DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type( + collection_binding_id=collection_binding_id, collection_type=collection_type + ) + + # Assert + assert result == existing_binding + assert result.id == collection_binding_id + assert result.type == collection_type + + # Verify query was constructed with the correct type filter + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + mock_query.where.assert_called_once() + + def test_get_dataset_collection_binding_by_id_and_type_default_collection_type(self, mock_db_session): + """ + Test retrieval with default collection type ("dataset"). + + Verifies that when collection_type is not provided, it defaults to "dataset" + as specified in the method signature. + + This test ensures: + - The default value "dataset" is used when type is not specified + - The query correctly filters by the default type + - The correct binding is returned + """ + # Arrange + collection_binding_id = "binding-789" + # collection_type defaults to "dataset" in method signature + + existing_binding = DatasetCollectionBindingTestDataFactory.create_collection_binding_mock( + binding_id=collection_binding_id, + provider_name="openai", + model_name="text-embedding-ada-002", + collection_type="dataset", # Default type + ) + + # Mock the query chain + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = existing_binding + mock_db_session.query.return_value = mock_query + + # Act - call without specifying collection_type (uses default) + result = DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type( + collection_binding_id=collection_binding_id + ) + + # Assert + assert result == existing_binding + assert result.id == collection_binding_id + assert result.type == "dataset" + + # Verify query was constructed correctly + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + mock_query.where.assert_called_once() + + def test_get_dataset_collection_binding_by_id_and_type_wrong_type_error(self, mock_db_session): + """ + Test error handling when binding exists but with wrong collection type. + + Verifies that when a binding exists with the given ID but a different + collection type, the method raises a ValueError because the binding + doesn't match both the ID and type criteria. + + This test ensures: + - The query correctly filters by both ID and type + - Bindings with matching ID but different type are not returned + - ValueError is raised when no matching binding is found + """ + # Arrange + collection_binding_id = "binding-123" + collection_type = "dataset" + + # Mock the query chain to return None (binding exists but with different type) + mock_query = Mock() + mock_where = Mock() + mock_order_by = Mock() + mock_query.where.return_value = mock_where + mock_where.order_by.return_value = mock_order_by + mock_order_by.first.return_value = None # No matching binding + mock_db_session.query.return_value = mock_query + + # Act & Assert + with pytest.raises(ValueError, match="Dataset collection binding not found"): + DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type( + collection_binding_id=collection_binding_id, collection_type=collection_type + ) + + # Verify query was attempted with both ID and type filters + # The query should filter by both collection_binding_id and collection_type + # This ensures we only get bindings that match both criteria + mock_db_session.query.assert_called_once_with(DatasetCollectionBinding) + + # Verify the where clause was applied with both filters: + # - collection_binding_id filter (exact match) + # - collection_type filter (exact match) + mock_query.where.assert_called_once() + + # Note: The order_by and first() calls are also part of the query chain, + # but we don't need to verify them separately since they're part of the + # standard query pattern used by both methods in this service. + + +# ============================================================================ +# Additional Test Scenarios and Edge Cases +# ============================================================================ +# The following section could contain additional test scenarios if needed: +# +# Potential additional tests: +# 1. Test with multiple existing bindings (verify ordering by created_at) +# 2. Test with very long provider/model names (boundary testing) +# 3. Test with special characters in provider/model names +# 4. Test concurrent binding creation (thread safety) +# 5. Test database rollback scenarios +# 6. Test with None values for optional parameters +# 7. Test with empty strings for required parameters +# 8. Test collection name generation uniqueness +# 9. Test with different UUID formats +# 10. Test query performance with large datasets +# +# These scenarios are not currently implemented but could be added if needed +# based on real-world usage patterns or discovered edge cases. +# +# ============================================================================ + + +# ============================================================================ +# Integration Notes and Best Practices +# ============================================================================ +# +# When using DatasetCollectionBindingService in production code, consider: +# +# 1. Error Handling: +# - Always handle ValueError exceptions when calling +# get_dataset_collection_binding_by_id_and_type +# - Check return values from get_dataset_collection_binding to ensure +# bindings were created successfully +# +# 2. Performance Considerations: +# - The service queries the database on every call, so consider caching +# bindings if they're accessed frequently +# - Collection bindings are typically long-lived, so caching is safe +# +# 3. Transaction Management: +# - New bindings are automatically committed to the database +# - If you need to rollback, ensure you're within a transaction context +# +# 4. Collection Type Usage: +# - Use "dataset" for standard dataset collections +# - Use custom types only when you need to separate collections by purpose +# - Be consistent with collection type naming across your application +# +# 5. Provider and Model Naming: +# - Use consistent provider names (e.g., "openai", not "OpenAI" or "OPENAI") +# - Use exact model names as provided by the model provider +# - These names are case-sensitive and must match exactly +# +# ============================================================================ + + +# ============================================================================ +# Database Schema Reference +# ============================================================================ +# +# The DatasetCollectionBinding model has the following structure: +# +# - id: StringUUID (primary key, auto-generated) +# - provider_name: String(255) (required, e.g., "openai", "cohere") +# - model_name: String(255) (required, e.g., "text-embedding-ada-002") +# - type: String(40) (required, default: "dataset") +# - collection_name: String(64) (required, unique collection identifier) +# - created_at: DateTime (auto-generated timestamp) +# +# Indexes: +# - Primary key on id +# - Composite index on (provider_name, model_name) for efficient lookups +# +# Relationships: +# - One binding can be referenced by multiple datasets +# - Datasets reference bindings via collection_binding_id +# +# ============================================================================ + + +# ============================================================================ +# Mocking Strategy Documentation +# ============================================================================ +# +# This test suite uses extensive mocking to isolate the unit under test. +# Here's how the mocking strategy works: +# +# 1. Database Session Mocking: +# - db.session is patched to prevent actual database access +# - Query chains are mocked to return predictable results +# - Add and commit operations are tracked for verification +# +# 2. Query Chain Mocking: +# - query() returns a mock query object +# - where() returns a mock where object +# - order_by() returns a mock order_by object +# - first() returns the final result (binding or None) +# +# 3. UUID Generation Mocking: +# - uuid.uuid4() is mocked to return predictable UUIDs +# - This ensures collection names are generated consistently in tests +# +# 4. Collection Name Generation Mocking: +# - Dataset.gen_collection_name_by_id() is mocked +# - This allows us to verify the method is called correctly +# - We can control the generated collection name for testing +# +# Benefits of this approach: +# - Tests run quickly (no database I/O) +# - Tests are deterministic (no random UUIDs) +# - Tests are isolated (no side effects) +# - Tests are maintainable (clear mock setup) +# +# ============================================================================