vitor-aignosi
67942c45e0
Refactor MinioDataFramePayload usage across activities - Updated instances of MinioDataFramePayload initialization in Gates, MLFlow, and Storage classes to use the new from_dict method for better data reconstruction from dictionaries. - Enhanced the PredictionProcess workflow to utilize the updated payload handling. - Added passthrough fixtures in tests to accommodate the new from_dict method for consistent testing behavior.
961 lines
29 KiB
Python
961 lines
29 KiB
Python
from unittest.mock import ANY, AsyncMock, MagicMock, call, patch
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from pandas import DataFrame
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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(autouse=True)
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def _passthrough_from_dict():
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with patch(
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'laborious.activities.gates.MinioDataFramePayload.from_dict', side_effect=lambda x: x
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):
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yield
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def _minio_payload(retrieve_return, status=None):
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"""
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Build a MinioDataFramePayload-like test double with async retrieve.
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Args:
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retrieve_return: Value returned from await retrieve(minio_repo, metadata).
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status: Optional status dict for MLflow response gate (payload.status).
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Return:
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MagicMock: Object with async retrieve and optional status.
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"""
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p = MagicMock()
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p.retrieve = AsyncMock(return_value=retrieve_return)
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p.status = status
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return p
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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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metrics_controller=AsyncMock(),
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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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gates.send_notification_async = AsyncMock()
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gates.emit_metric = AsyncMock()
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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': _minio_payload(DataFrame({'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': _minio_payload(DataFrame({'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_async.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': _minio_payload(DataFrame({'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': _minio_payload(DataFrame({'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': _minio_payload(DataFrame({'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': _minio_payload(
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{'content': {'message': 'success'}},
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status={'success': True},
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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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@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': _minio_payload(
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{'content': {'message': 'success'}},
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status={'success': True},
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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.send_notification_async.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': _minio_payload(
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{'content': {'message': 'success'}},
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status={'success': True},
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),
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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': _minio_payload(
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{'content': {'message': 'API error occurred', 'traceback': 'error trace'}},
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status={'success': False, 'message': 'API error occurred'},
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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_async.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': _minio_payload(
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{'content': {'message': 'success'}},
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status={'success': True},
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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': _minio_payload(DataFrame({'value': [1, 2, 3]})),
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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': _minio_payload(DataFrame({'value': [1, 2, 3]})),
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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_async.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': _minio_payload(DataFrame({'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': _minio_payload(DataFrame({'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_async.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': _minio_payload(DataFrame({'value': [1, 2, 3]})),
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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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@mark.asyncio
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async def test_mlflow_content_gate_filter_returns_false(gates_activity):
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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': _minio_payload(DataFrame({'value': [1, 2, 3]})),
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'type': 'test',
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'path_priority': ['STOP', 'CONTINUE', 'REPEAT'],
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}
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result = await gates_activity.mlflow_content_gate(input_data)
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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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|
|
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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': _minio_payload(
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DataFrame(
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{
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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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)
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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': _minio_payload(
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DataFrame(
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{
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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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)
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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}
|
|
assert result['response_time'] == {0: 0.2, 1: 0.1}
|
|
assert result['timestamp'] == {0: '2023-05-26 11:12:28', 1: '2023-05-26 11:12:27'}
|
|
assert result['model_id'] == {0: 'test_model', 1: 'test_model'}
|
|
assert result['prediction_confidence'] == {0: 0.9, 1: 0.9}
|
|
assert result['prediction_status'] == {0: 'Good', 1: 'Good'}
|
|
assert result['comments'] == {0: '', 1: ''}
|
|
|
|
|
|
@mark.asyncio
|
|
async def test_format_prediction_with_timestamp_lts(gates_activity):
|
|
# Arrange
|
|
input_data = {
|
|
**metadata,
|
|
'data': _minio_payload(
|
|
DataFrame(
|
|
{
|
|
'prediction': {
|
|
'2023-05-26 11:12:27': 1,
|
|
'2023-05-26 11:12:28': 2,
|
|
'2023-05-26 11:12:29': 3,
|
|
},
|
|
'response_time': {
|
|
'2023-05-26 11:12:27': 0.1,
|
|
'2023-05-26 11:12:28': 0.2,
|
|
'2023-05-26 11:12:29': 0.3,
|
|
},
|
|
}
|
|
)
|
|
),
|
|
'model_id': 'test_model',
|
|
'prediction_confidence': 0.9,
|
|
'prediction_store_policy': 'lts:2',
|
|
}
|
|
|
|
# Act
|
|
result = await gates_activity.format_prediction(input_data)
|
|
|
|
# Assert
|
|
assert result['prediction'] == {0: 3, 1: 2}
|
|
assert result['response_time'] == {0: 0.3, 1: 0.2}
|
|
assert result['timestamp'] == {0: '2023-05-26 11:12:29', 1: '2023-05-26 11:12:28'}
|
|
assert result['model_id'] == {0: 'test_model', 1: 'test_model'}
|
|
assert result['prediction_confidence'] == {0: 0.9, 1: 0.9}
|
|
assert result['prediction_status'] == {0: 'Good', 1: 'Good'}
|
|
assert result['comments'] == {0: '', 1: ''}
|
|
|
|
|
|
@mark.asyncio
|
|
async def test_format_prediction_with_timestamp_invalid_policy(gates_activity):
|
|
# Arrange
|
|
input_data = {
|
|
**metadata,
|
|
'data': _minio_payload(
|
|
DataFrame(
|
|
{
|
|
'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
|
|
@patch('laborious.activities.gates.MinioDataFramePayload.from_dataframe', new_callable=AsyncMock)
|
|
async def test_format_transformed_data_single_row(mock_from_dataframe, gates_activity):
|
|
# Arrange
|
|
payload_result = MagicMock()
|
|
mock_from_dataframe.return_value = payload_result
|
|
input_data = {
|
|
**metadata,
|
|
'data': _minio_payload(
|
|
DataFrame(
|
|
{
|
|
'var1': {'2023-05-26 11:12:27': 1.0},
|
|
'var2': {'2023-05-26 11:12:27': 2.0},
|
|
}
|
|
)
|
|
),
|
|
'model_id': 'test_model',
|
|
'model_name': 'test_model',
|
|
}
|
|
|
|
# Act
|
|
result = await gates_activity.format_transformed_data(input_data)
|
|
|
|
# Assert
|
|
assert result is payload_result
|
|
mock_from_dataframe.assert_called_once()
|
|
kwargs = mock_from_dataframe.call_args.kwargs
|
|
assert kwargs['model_name'] == 'test_model'
|
|
assert kwargs['operation'] == 'transform'
|
|
assert kwargs['workflow_metadata'] == metadata['metadata']
|
|
assert kwargs['minio_repo'] is gates_activity.minio_repository
|
|
assert 'dataframe' in kwargs
|
|
gates_activity.info.assert_called()
|
|
|
|
|
|
@mark.asyncio
|
|
@patch('laborious.activities.gates.MinioDataFramePayload.from_dataframe', new_callable=AsyncMock)
|
|
async def test_format_transformed_data_multiple_rows(mock_from_dataframe, gates_activity):
|
|
# Arrange
|
|
payload_result = MagicMock()
|
|
mock_from_dataframe.return_value = payload_result
|
|
input_data = {
|
|
**metadata,
|
|
'data': _minio_payload(
|
|
DataFrame(
|
|
{
|
|
'var1': {
|
|
'2023-05-26 11:12:27': 1.0,
|
|
'2023-05-26 11:12:28': 2.0,
|
|
},
|
|
'var2': {
|
|
'2023-05-26 11:12:27': 3.0,
|
|
'2023-05-26 11:12:28': 4.0,
|
|
},
|
|
}
|
|
)
|
|
),
|
|
'model_id': 'test_model',
|
|
'model_name': 'test_model',
|
|
}
|
|
|
|
# Act
|
|
result = await gates_activity.format_transformed_data(input_data)
|
|
|
|
# Assert
|
|
assert result is payload_result
|
|
mock_from_dataframe.assert_called_once()
|
|
kwargs = mock_from_dataframe.call_args.kwargs
|
|
assert kwargs['model_name'] == 'test_model'
|
|
assert kwargs['operation'] == 'transform'
|
|
assert kwargs['workflow_metadata'] == metadata['metadata']
|
|
assert kwargs['minio_repo'] is gates_activity.minio_repository
|
|
assert 'dataframe' in kwargs
|
|
gates_activity.info.assert_called()
|
|
|
|
|
|
@mark.asyncio
|
|
@patch('laborious.activities.gates.MinioDataFramePayload.from_dataframe', new_callable=AsyncMock)
|
|
async def test_format_transformed_data_empty_data(mock_from_dataframe, gates_activity):
|
|
# Arrange
|
|
payload_result = MagicMock()
|
|
mock_from_dataframe.return_value = payload_result
|
|
input_data = {
|
|
**metadata,
|
|
'data': _minio_payload(DataFrame()),
|
|
'model_id': 'test_model',
|
|
'model_name': 'test_model',
|
|
}
|
|
|
|
# Act
|
|
result = await gates_activity.format_transformed_data(input_data)
|
|
|
|
# Assert
|
|
assert result is payload_result
|
|
mock_from_dataframe.assert_called_once()
|
|
kwargs = mock_from_dataframe.call_args.kwargs
|
|
assert kwargs['model_name'] == 'test_model'
|
|
assert kwargs['operation'] == 'transform'
|
|
assert kwargs['workflow_metadata'] == metadata['metadata']
|
|
assert kwargs['minio_repo'] is gates_activity.minio_repository
|
|
assert 'dataframe' in kwargs
|
|
gates_activity.info.assert_called()
|
|
|
|
|
|
@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_format_retrain_report_failure(gates_activity):
|
|
# Arrange
|
|
input_data = {
|
|
**metadata,
|
|
'experiment_response': {
|
|
'success': False,
|
|
'timestamp': '2023-05-26 11:12:27',
|
|
'message': 'failure',
|
|
},
|
|
'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: 'failure'}
|
|
assert 'version' not in result
|
|
assert 'mlflow_run_id' not in result
|
|
assert 'mlflow_experiment_id' not in result
|
|
gates_activity.info.assert_called()
|
|
gates_activity.debug.assert_called()
|
|
|
|
|
|
@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],
|
|
},
|
|
'opc_metrics': {'server1': {'tag1': 0.1, 'tag2': 0.2}},
|
|
}
|
|
await gates_activity.write_metrics(input_data)
|
|
gates_activity.emit_metric.assert_has_calls(
|
|
[
|
|
call(
|
|
metric_object=mock_metrics.PREDICTIONS_WRITTEN_COUNT,
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
},
|
|
),
|
|
]
|
|
)
|
|
gates_activity.emit_metric.assert_has_calls(
|
|
[
|
|
call(
|
|
metric_object=mock_metrics.PREDICTION_CONFIDENCE_MONITOR,
|
|
method='set',
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
},
|
|
value=0.9,
|
|
),
|
|
]
|
|
)
|
|
gates_activity.emit_metric.assert_has_calls(
|
|
[
|
|
call(
|
|
metric_object=mock_metrics.PREDICTION_RESPONSE_TIME_MONITOR,
|
|
method='observe',
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
},
|
|
value=0.1,
|
|
),
|
|
]
|
|
)
|
|
gates_activity.emit_metric.assert_has_calls(
|
|
[
|
|
call(
|
|
metric_object=mock_metrics.PREDICTION_OPC_WRITING_COUNT,
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
'opc_server_id': 'server1',
|
|
'tag': 'tag1',
|
|
},
|
|
),
|
|
]
|
|
)
|
|
gates_activity.emit_metric.assert_has_calls(
|
|
[
|
|
call(
|
|
metric_object=mock_metrics.PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR,
|
|
method='observe',
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
'opc_server_id': 'server1',
|
|
'tag': 'tag1',
|
|
},
|
|
value=0.1,
|
|
),
|
|
]
|
|
)
|
|
gates_activity.emit_metric.assert_has_calls(
|
|
[
|
|
call(
|
|
metric_object=mock_metrics.PREDICTION_OPC_WRITING_COUNT,
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
'opc_server_id': 'server1',
|
|
'tag': 'tag2',
|
|
},
|
|
),
|
|
]
|
|
)
|
|
gates_activity.emit_metric.assert_has_calls(
|
|
[
|
|
call(
|
|
metric_object=mock_metrics.PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR,
|
|
method='observe',
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
'opc_server_id': 'server1',
|
|
'tag': 'tag2',
|
|
},
|
|
value=0.2,
|
|
),
|
|
]
|
|
)
|
|
|
|
|
|
@mark.asyncio
|
|
@patch('laborious.activities.gates.metrics')
|
|
async def test_write_metrics_with_none_opc_response_time(mock_metrics, gates_activity):
|
|
"""Test write_metrics method with None response_time in opc_metrics."""
|
|
input_data = {
|
|
**metadata,
|
|
'prediction': {
|
|
'prediction': [1],
|
|
'prediction_confidence': [0.9],
|
|
'response_time': [0.1],
|
|
},
|
|
'opc_metrics': {'server1': {'tag1': 0.1, 'tag2': None}},
|
|
}
|
|
await gates_activity.write_metrics(input_data)
|
|
|
|
# Verify that metrics for tag1 are emitted
|
|
gates_activity.emit_metric.assert_any_call(
|
|
metric_object=mock_metrics.PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR,
|
|
method='observe',
|
|
tags={
|
|
'pod_id': gates_activity.pod_id,
|
|
'model_name': metadata['metadata']['model_name'],
|
|
'workflow_name': metadata['metadata']['workflow_name'],
|
|
'opc_server_id': 'server1',
|
|
'tag': 'tag1',
|
|
},
|
|
value=0.1,
|
|
)
|
|
|
|
# Verify that metrics for tag2 (with None response_time) are NOT emitted
|
|
calls = [
|
|
c
|
|
for c in gates_activity.emit_metric.call_args_list
|
|
if len(c[1].get('tags', {})) > 0 and c[1]['tags'].get('tag') == 'tag2'
|
|
]
|
|
assert len(calls) == 0, 'Metrics should not be emitted for None response_time'
|