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Testing

  • Testing strategies: Overview of the testing approach, including unit and integration testing.
  • Test cases: Detailed description of important test cases and how to run tests.

Testing Approach

Unit Testing: Focuses on testing the fetch_dataset_answer_by_question function in isolation. Mocking is used to simulate the behavior of the HuggingFaceDataset model to ensure that tests are not dependent on the database or external factors.

Integration Testing: Ensures that the fetch_dataset_answer_by_question function interacts correctly with the HuggingFaceDataset model and the database. This tests the function in a scenario that is close to its real usage within the application.

Test Environment Setup

Ensure Django is installed and configured correctly. The test cases are written using Django’s built-in TestCase class. For unit tests, the unittest.mock library is used for mocking. Running Tests Tests can be run using the Django test runner.

Execute the following command in the terminal from the root of the Django project:

python manage.py test

Unit Tests

Test Invalid Dataset:

Description: Tests the response of the function when an invalid dataset ID is provided. Execution: Call fetch_dataset_answer_by_question with an invalid dataset ID and a sample question. Expected Result: The function should return None. Test No Dataset With Question (Mocked):

Description: Tests the function's behavior when no dataset matches the provided question. Setup: Mock HuggingFaceDataset.nodes to return None. Execution: Call fetch_dataset_answer_by_question with a valid dataset ID and a question that does not exist in the dataset. Expected Result: The function should return None. Test Valid Dataset (Mocked):

Description: Validates the function's ability to return the correct answer for a valid question. Setup: Mock HuggingFaceDataset.nodes to return a predefined dataset object. Execution: Call fetch_dataset_answer_by_question with a valid dataset ID and a question that exists in the mocked dataset. Expected Result: The function should return the corresponding answer from the mocked dataset.

Integration Tests

Test Invalid Dataset:

Description: Similar to the unit test, but in an integrated environment. Execution: Identical to the unit test case. Expected Result: Identical to the unit test case. Test No Dataset With Question:

Description: Tests the function's behavior in an integrated environment when no dataset matches the provided question. Execution: Call fetch_dataset_answer_by_question with a valid dataset ID and a non-existent question. Expected Result: The function should return None. Test Valid Dataset:

Description: Validates the function's ability in an integrated environment to return the correct answer for a valid question. Execution: Call fetch_dataset_answer_by_question with a valid dataset ID and a question that exists in the real dataset. Expected Result: The function should return the corresponding answer from the dataset.