vitor-aignosi
f0fb9b854e
Enhance validation script and refactor code in various modules - Updated the validation script to include automatic code formatting and linting fixes using Ruff. - Removed the `clean_tmp_files` method from the Gates class to streamline functionality. - Simplified conditional checks in the OpcRepository for better clarity and error handling. - Added model ID to the minimal retrain workflow for improved tracking. - Introduced new test cases for error handling in MLFlow and storage operations, ensuring robustness in repository interactions.
663 lines
19 KiB
Python
663 lines
19 KiB
Python
from unittest.mock import ANY, MagicMock, patch
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from pytest import fixture, mark
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from sientia_do.notifications.models import NotificationLevel
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from laborious.activities.gates import Gates
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@fixture
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def gates_activity():
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gates = Gates(
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logger=MagicMock(),
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notification_handler=MagicMock(),
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)
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gates.error = MagicMock()
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gates.debug = MagicMock()
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gates.info = MagicMock()
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gates.warning = MagicMock()
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gates.critical = MagicMock()
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gates.send_notification = MagicMock()
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return gates
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metadata = {
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'metadata': {
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'model_id': 'test_model',
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'model_name': 'test_model',
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'workflow_name': 'test_workflow',
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'schema_name': 'test_schedule',
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},
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}
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@mark.asyncio
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async def test_input_gate_invalid_filter(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'INVALID_FILTER': {'POLICY': 'STOP'}},
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'data': {'value': [1, 2, 3]},
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.input_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.error.assert_called_once_with(
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'Filter INVALID_FILTER not found', metadata['metadata']
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)
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@mark.asyncio
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@patch('laborious.activities.gates.input_filter_functions')
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async def test_input_gate_filter_exception(mock_input_filter_functions, gates_activity):
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# Arrange
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mock_input_filter_functions.__contains__.return_value = True
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mock_input_filter_functions.__getitem__.return_value = MagicMock(
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side_effect=Exception('Test error')
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)
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input_data = {
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**metadata,
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'filters': {'EMPTY_DATA': {'policy': 'STOP', 'config': {}}},
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'data': {'value': []},
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.input_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.send_notification.assert_called_once_with(
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metadata=metadata['metadata'],
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notification_id='INTPUT_GATE_ERROR__EMPTY_DATA',
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message="Error in filter EMPTY_DATA:{'policy': 'STOP', 'config': {}}: \n Test error",
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block='input_gate',
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level=NotificationLevel.ERROR,
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attachment_content=ANY,
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)
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@mark.asyncio
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async def test_input_gate_no_filters(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {},
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'data': {'value': [1, 2, 3]},
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'path_priority': ['CONTINUE', 'STOP', 'REPEAT'],
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}
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# Act
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result = await gates_activity.input_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.debug.assert_called()
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@mark.asyncio
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async def test_input_gate_with_filter(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'EMPTY_DATA': {'policy': 'STOP', 'config': {}}},
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'data': {'value': []},
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.input_gate(input_data)
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# Assert
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assert result == ('STOP', -1, 'Input data with bad quality')
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gates_activity.debug.assert_called()
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@mark.asyncio
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async def test_input_gate_with_filter_not_caught(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'EMPTY_DATA': {'policy': 'STOP', 'config': {}}},
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'data': {'value': [1, 2, 3]},
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.input_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.debug.assert_called()
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@mark.asyncio
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async def test_mlflow_response_gate_invalid_filter(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'INVALID_FILTER': {'POLICY': 'STOP'}},
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'data': {'content': {'message': 'success'}},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_response_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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@mark.asyncio
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@patch('laborious.activities.gates.mlflow_response_filter_functions')
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async def test_mlflow_response_gate_filter_exception(
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mock_mlflow_response_filter_functions, gates_activity
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):
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# Arrange
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mock_mlflow_response_filter_functions.__contains__.return_value = True
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mock_mlflow_response_filter_functions.__getitem__.return_value = MagicMock(
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side_effect=Exception('Test error')
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)
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input_data = {
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**metadata,
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'filters': {'INVALID_FILTER': {'POLICY': 'STOP'}},
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'data': {'content': {'message': 'success'}},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_response_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.send_notification.assert_called_once_with(
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metadata=metadata['metadata'],
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notification_id='MLFLOW_GATE_RESPONSE_FILTER__INVALID_FILTER',
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message="Error in filter INVALID_FILTER:{'POLICY': 'STOP'}: \n Test error",
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block='mlflow_gate',
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level=NotificationLevel.ERROR,
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attachment_content=ANY,
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)
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@mark.asyncio
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async def test_mlflow_response_gate_no_filters(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {},
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'data': {'content': {'message': 'success'}},
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'type': 'test',
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'path_priority': ['CONTINUE', 'STOP', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_response_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.debug.assert_called()
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@mark.asyncio
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async def test_mlflow_response_gate_with_filter(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'API_ERROR': {'policy': 'STOP'}},
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'data': {
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'success': False,
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'content': {'message': 'API error occurred', 'traceback': 'error trace'},
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},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_response_gate(input_data)
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# Assert
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assert result == ('STOP', -1, 'API error occurred')
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gates_activity.debug.assert_called()
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gates_activity.send_notification.assert_called()
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@mark.asyncio
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async def test_mlflow_response_gate_with_filter_not_caught(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'API_ERROR': {'policy': 'STOP'}},
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'data': {
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'success': True,
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'content': {'message': 'success'},
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},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_response_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.debug.assert_called()
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@mark.asyncio
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async def test_mlflow_content_gate_invalid_filter(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'INVALID_FILTER': {'POLICY': 'STOP'}},
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'data': {
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'success': True,
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'content': {'message': 'success'},
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},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_content_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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@mark.asyncio
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@patch('laborious.activities.gates.mlflow_content_filter_functions')
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async def test_mlflow_content_gate_filter_exception(
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mock_mlflow_content_filter_functions, gates_activity
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):
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# Arrange
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mock_mlflow_content_filter_functions.__contains__.return_value = True
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mock_mlflow_content_filter_functions.__getitem__.return_value = MagicMock(
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side_effect=Exception('Test error')
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)
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input_data = {
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**metadata,
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'filters': {'API_ERROR': {'POLICY': 'STOP'}},
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'data': {
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'success': False,
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'content': {'message': 'API error occurred', 'traceback': 'error trace'},
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},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_content_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.debug.assert_called()
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gates_activity.send_notification.assert_called_once_with(
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metadata=metadata['metadata'],
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notification_id='MLFLOW_GATE_CONTENT_FILTER__API_ERROR',
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message="Error in filter API_ERROR:{'POLICY': 'STOP'}: \n Test error",
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block='mlflow_gate',
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level=NotificationLevel.ERROR,
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attachment_content=ANY,
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)
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@mark.asyncio
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async def test_mlflow_content_gate_no_filters(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {},
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'data': {'value': [1, 2, 3]},
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'type': 'test',
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'path_priority': ['CONTINUE', 'STOP', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_content_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.debug.assert_called()
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@mark.asyncio
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async def test_mlflow_content_gate_with_filter(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'NAN_VALUES': {'policy': 'STOP', 'config': {}}},
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'data': {'value': [None, None, None]},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_content_gate(input_data)
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# Assert
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assert result == ('STOP', -1, 'Transformed data not passed the content filter')
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gates_activity.debug.assert_called()
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gates_activity.send_notification.assert_called()
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@mark.asyncio
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async def test_mlflow_content_gate_with_filter_not_caught(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'filters': {'API_ERROR': {'POLICY': 'STOP'}},
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'data': {'content': {'message': 'success'}},
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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# Act
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result = await gates_activity.mlflow_content_gate(input_data)
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# Assert
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assert result == (None, 0, '')
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gates_activity.debug.assert_called()
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def test_get_prediction_store_policy_invalid_policy(gates_activity):
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# Arrange
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prediction_store_policy = 'INVALID_POLICY'
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# Act
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policy_type, policy_value = gates_activity.get_prediction_store_policy(
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prediction_store_policy, metadata
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)
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# Assert
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assert policy_type == 'lts'
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assert policy_value == 1
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def test_get_prediction_store_policy_invalid_policy_value(gates_activity):
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# Arrange
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prediction_store_policy = 'abc:INVALID_VALUE'
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# Act
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policy_type, policy_value = gates_activity.get_prediction_store_policy(
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prediction_store_policy, metadata
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)
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# Assert
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assert policy_type == 'lts'
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assert policy_value == 1
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def test_get_prediction_store_policy_valid_policy_type(gates_activity):
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# Arrange
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prediction_store_policy = 'abc:1'
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# Act
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policy_type, policy_value = gates_activity.get_prediction_store_policy(
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prediction_store_policy, metadata
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)
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# Assert
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assert policy_type == 'lts'
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assert policy_value == 1
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def test_get_prediction_store_policy_valid_policy(gates_activity):
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# Arrange
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prediction_store_policy = 'erl:1'
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# Act
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policy_type, policy_value = gates_activity.get_prediction_store_policy(
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prediction_store_policy, metadata
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)
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# Assert
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assert policy_type == 'erl'
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assert policy_value == 1
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@mark.asyncio
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async def test_format_prediction_no_timestamp(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'data': {
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'prediction': {'2023-05-26 11:12:27': 1},
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'response_time': {'2023-05-26 11:12:27': 0.1},
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},
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'model_id': 'test_model',
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'prediction_confidence': 0.9,
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'prediction_store_policy': 'lts:1',
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}
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# Act
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result = await gates_activity.format_prediction(input_data)
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# Assert
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assert result['prediction'] == {0: 1}
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assert result['response_time'] == {0: ANY}
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assert result['timestamp'] == {0: '2023-05-26 11:12:27'}
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assert result['model_id'] == {0: 'test_model'}
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assert result['prediction_confidence'] == {0: 0.9}
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assert result['prediction_status'] == {0: 'Good'}
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assert result['comments'] == {0: ''}
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@mark.asyncio
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async def test_format_prediction_with_timestamp_erl(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'data': {
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'prediction': {
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'2023-05-26 11:12:27': 1,
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'2023-05-26 11:12:28': 2,
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'2023-05-26 11:12:29': 3,
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},
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'response_time': {
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'2023-05-26 11:12:27': 0.1,
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'2023-05-26 11:12:28': 0.2,
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'2023-05-26 11:12:29': 0.3,
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},
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},
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'model_id': 'test_model',
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'prediction_confidence': 0.9,
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'prediction_store_policy': 'erl:2',
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}
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# Act
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result = await gates_activity.format_prediction(input_data)
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# Assert
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assert result['prediction'] == {0: 2, 1: 1}
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assert result['response_time'] == {0: 0.2, 1: 0.1}
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assert result['timestamp'] == {0: '2023-05-26 11:12:28', 1: '2023-05-26 11:12:27'}
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assert result['model_id'] == {0: 'test_model', 1: 'test_model'}
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assert result['prediction_confidence'] == {0: 0.9, 1: 0.9}
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assert result['prediction_status'] == {0: 'Good', 1: 'Good'}
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assert result['comments'] == {0: '', 1: ''}
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@mark.asyncio
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async def test_format_prediction_with_timestamp_lts(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'data': {
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'prediction': {
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'2023-05-26 11:12:27': 1,
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'2023-05-26 11:12:28': 2,
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'2023-05-26 11:12:29': 3,
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},
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'response_time': {
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'2023-05-26 11:12:27': 0.1,
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'2023-05-26 11:12:28': 0.2,
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'2023-05-26 11:12:29': 0.3,
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},
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},
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'model_id': 'test_model',
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'prediction_confidence': 0.9,
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'prediction_store_policy': 'lts:2',
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}
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# Act
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result = await gates_activity.format_prediction(input_data)
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# Assert
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assert result['prediction'] == {0: 3, 1: 2}
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assert result['response_time'] == {0: 0.3, 1: 0.2}
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assert result['timestamp'] == {0: '2023-05-26 11:12:29', 1: '2023-05-26 11:12:28'}
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assert result['model_id'] == {0: 'test_model', 1: 'test_model'}
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assert result['prediction_confidence'] == {0: 0.9, 1: 0.9}
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assert result['prediction_status'] == {0: 'Good', 1: 'Good'}
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assert result['comments'] == {0: '', 1: ''}
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@mark.asyncio
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async def test_format_prediction_with_timestamp_invalid_policy(gates_activity):
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# Arrange
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input_data = {
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**metadata,
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'data': {
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'prediction': [1, 2, 3],
|
|
'response_time': [0.1, 0.2, 0.3],
|
|
'timestamp': ['2023-05-26 11:12:27', '2023-05-26 11:12:28', '2023-05-26 11:12:29'],
|
|
},
|
|
'model_id': 'test_model',
|
|
'prediction_confidence': 0.9,
|
|
'prediction_store_policy': 'lts:2',
|
|
}
|
|
gates_activity.get_prediction_store_policy = MagicMock(return_value=('invalid', 1))
|
|
|
|
try:
|
|
await gates_activity.format_prediction(input_data)
|
|
except ValueError as e:
|
|
assert str(e) == 'Invalid policy type: invalid'
|
|
else:
|
|
raise AssertionError('Expected ValueError')
|
|
|
|
|
|
@mark.asyncio
|
|
async def test_format_default_prediction(gates_activity):
|
|
# Arrange
|
|
input_data = {
|
|
**metadata,
|
|
'timestamp': '2023-05-26 11:12:27',
|
|
'model_id': 'test_model',
|
|
'prediction_confidence': 0.1,
|
|
'comment': 'Test comment',
|
|
}
|
|
|
|
# Act
|
|
result = await gates_activity.format_default_prediction(input_data)
|
|
|
|
# Assert
|
|
assert result['prediction'] == {0: 0}
|
|
assert result['response_time'] == {0: 0}
|
|
assert result['timestamp'] == {0: '2023-05-26 11:12:27'}
|
|
assert result['model_id'] == {0: 'test_model'}
|
|
assert result['prediction_confidence'] == {0: 0.1}
|
|
assert result['prediction_status'] == {0: 'Bad'}
|
|
assert result['comments'] == {0: 'Test comment'}
|
|
gates_activity.debug.assert_called()
|
|
|
|
|
|
@mark.asyncio
|
|
async def test_format_retrain_report(gates_activity):
|
|
# Arrange
|
|
input_data = {
|
|
**metadata,
|
|
'experiment_response': {
|
|
'success': True,
|
|
'timestamp': '2023-05-26 11:12:27',
|
|
'message': 'success',
|
|
},
|
|
'update_report': {
|
|
'version': '1.0.0',
|
|
'mlflow_run_id': 'test_mlflow_run_id',
|
|
'mlflow_experiment_id': 'test_mlflow_experiment_id',
|
|
},
|
|
'model_id': 'test_model',
|
|
'model_name': 'test_model',
|
|
}
|
|
|
|
# Act
|
|
result = await gates_activity.format_retrain_report(input_data)
|
|
|
|
# Assert
|
|
assert result['model_id'] == {0: 'test_model'}
|
|
assert result['model_name'] == {0: 'test_model'}
|
|
assert result['timestamp'] == {0: '2023-05-26 11:12:27'}
|
|
assert result['status'] == {0: 'success'}
|
|
assert result['version'] == {0: '1.0.0'}
|
|
assert result['mlflow_run_id'] == {0: 'test_mlflow_run_id'}
|
|
assert result['mlflow_experiment_id'] == {0: 'test_mlflow_experiment_id'}
|
|
|
|
|
|
@mark.asyncio
|
|
async def test_get_last_timestamp_with_data(gates_activity):
|
|
# Arrange
|
|
input_data = {**metadata, 'data': {'timestamp': ['2023-05-26 11:12:27', '2023-05-26 11:12:28']}}
|
|
|
|
# Act
|
|
result = await gates_activity.get_last_timestamp(input_data)
|
|
|
|
# Assert
|
|
assert result == '2023-05-26 11:12:28'
|
|
|
|
|
|
@mark.asyncio
|
|
async def test_get_last_timestamp_no_data(gates_activity):
|
|
# Arrange
|
|
input_data = {'data': {}, **metadata}
|
|
|
|
# Act
|
|
result = await gates_activity.get_last_timestamp(input_data)
|
|
|
|
# Assert
|
|
assert isinstance(result, str) # Should be a timestamp string
|
|
assert len(result) > 0
|
|
|
|
|
|
@mark.asyncio
|
|
@patch('laborious.activities.gates.metrics')
|
|
async def test_write_metrics(mock_metrics, gates_activity):
|
|
"""Test write_metrics method."""
|
|
input_data = {
|
|
**metadata,
|
|
'prediction': {
|
|
'prediction': [1, 2, 3],
|
|
'prediction_confidence': [0.9, 0.8, 0.7],
|
|
'response_time': [0.1, 0.2, 0.3],
|
|
},
|
|
}
|
|
await gates_activity.write_metrics(input_data)
|
|
mock_metrics.PREDICTIONS_WRITTEN_COUNT.labels.assert_called_once_with(
|
|
pod_id=gates_activity.pod_id,
|
|
model_name=metadata['metadata']['model_name'],
|
|
pipeline_name=metadata['metadata']['workflow_name'],
|
|
)
|
|
mock_metrics.PREDICTIONS_WRITTEN_COUNT.labels.return_value.inc.assert_called_once_with()
|
|
|
|
mock_metrics.PREDICTION_CONFIDENCE_MONITOR.labels.assert_called_once_with(
|
|
pod_id=gates_activity.pod_id,
|
|
model_name=metadata['metadata']['model_name'],
|
|
pipeline_name=metadata['metadata']['workflow_name'],
|
|
)
|
|
mock_metrics.PREDICTION_CONFIDENCE_MONITOR.labels.return_value.set.assert_called_once_with(0.9)
|
|
|
|
mock_metrics.PREDICTION_RESPONSE_TIME_MONITOR.labels.assert_called_once_with(
|
|
pod_id=gates_activity.pod_id,
|
|
model_name=metadata['metadata']['model_name'],
|
|
pipeline_name=metadata['metadata']['workflow_name'],
|
|
)
|
|
mock_metrics.PREDICTION_RESPONSE_TIME_MONITOR.labels.return_value.observe.assert_called_once_with(
|
|
0.1
|
|
)
|