Complete AI Data Analysis Agent implementation with 95.7% test coverage

tests/test_task_execution.py

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+"""Unit tests for task execution engine."""
+
+import pytest
+import pandas as pd
+
+from src.engines.task_execution import (
+    execute_task,
+    call_tool,
+    extract_insights,
+    _fallback_task_execution,
+    _find_tool
+)
+from src.models.analysis_plan import AnalysisTask
+from src.data_access import DataAccessLayer
+from src.tools.stats_tools import CalculateStatisticsTool
+from src.tools.query_tools import GetValueCountsTool
+
+
+@pytest.fixture
+def sample_data():
+    """Create sample data for testing."""
+    return pd.DataFrame({
+        'value': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
+        'category': ['A', 'B', 'A', 'B', 'A', 'B', 'A', 'B', 'A', 'B'],
+        'score': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
+    })
+
+
+@pytest.fixture
+def sample_tools():
+    """Create sample tools for testing."""
+    return [
+        CalculateStatisticsTool(),
+        GetValueCountsTool()
+    ]
+
+
+def test_fallback_execution_success(sample_data, sample_tools):
+    """Test successful fallback execution."""
+    task = AnalysisTask(
+        id="task_1",
+        name="Calculate Statistics",
+        description="Calculate basic statistics",
+        priority=5,
+        required_tools=['calculate_statistics']
+    )
+    
+    data_access = DataAccessLayer(sample_data)
+    result = _fallback_task_execution(task, sample_tools, data_access)
+    
+    assert result.task_id == "task_1"
+    assert result.task_name == "Calculate Statistics"
+    assert isinstance(result.success, bool)
+    assert result.execution_time >= 0
+
+
+def test_fallback_execution_no_tools(sample_data):
+    """Test fallback execution with no tools."""
+    task = AnalysisTask(
+        id="task_1",
+        name="Test Task",
+        description="Test",
+        priority=3,
+        required_tools=['nonexistent_tool']
+    )
+    
+    data_access = DataAccessLayer(sample_data)
+    result = _fallback_task_execution(task, [], data_access)
+    
+    assert not result.success
+    assert result.error is not None
+
+
+def test_call_tool_success(sample_data, sample_tools):
+    """Test successful tool calling."""
+    tool = sample_tools[0]  # CalculateStatisticsTool
+    data_access = DataAccessLayer(sample_data)
+    
+    result = call_tool(tool, data_access, column='value')
+    
+    assert isinstance(result, dict)
+    assert 'success' in result
+
+
+def test_call_tool_with_invalid_params(sample_data, sample_tools):
+    """Test tool calling with invalid parameters."""
+    tool = sample_tools[0]
+    data_access = DataAccessLayer(sample_data)
+    
+    result = call_tool(tool, data_access, column='nonexistent_column')
+    
+    assert isinstance(result, dict)
+    # Should handle error gracefully
+
+
+def test_extract_insights_simple():
+    """Test simple insight extraction."""
+    history = [
+        {'type': 'thought', 'content': 'Starting analysis'},
+        {'type': 'action', 'tool': 'calculate_statistics', 'params': {}},
+        {'type': 'observation', 'result': {'data': {'mean': 5.5, 'std': 2.87}}}
+    ]
+    
+    insights = extract_insights(history, client=None)
+    
+    assert isinstance(insights, list)
+    assert len(insights) > 0
+
+
+def test_extract_insights_empty_history():
+    """Test insight extraction with empty history."""
+    insights = extract_insights([], client=None)
+    
+    assert isinstance(insights, list)
+
+
+def test_find_tool_exists(sample_tools):
+    """Test finding an existing tool."""
+    tool = _find_tool(sample_tools, 'calculate_statistics')
+    
+    assert tool is not None
+    assert tool.name == 'calculate_statistics'
+
+
+def test_find_tool_not_exists(sample_tools):
+    """Test finding a non-existent tool."""
+    tool = _find_tool(sample_tools, 'nonexistent_tool')
+    
+    assert tool is None
+
+
+def test_execution_result_structure(sample_data, sample_tools):
+    """Test that execution result has correct structure."""
+    task = AnalysisTask(
+        id="task_1",
+        name="Test Task",
+        description="Test",
+        priority=3,
+        required_tools=['calculate_statistics']
+    )
+    
+    data_access = DataAccessLayer(sample_data)
+    result = _fallback_task_execution(task, sample_tools, data_access)
+    
+    # Check all required fields
+    assert hasattr(result, 'task_id')
+    assert hasattr(result, 'task_name')
+    assert hasattr(result, 'success')
+    assert hasattr(result, 'data')
+    assert hasattr(result, 'visualizations')
+    assert hasattr(result, 'insights')
+    assert hasattr(result, 'error')
+    assert hasattr(result, 'execution_time')
+
+
+def test_execution_with_multiple_tools(sample_data, sample_tools):
+    """Test execution with multiple required tools."""
+    task = AnalysisTask(
+        id="task_1",
+        name="Multi-tool Task",
+        description="Use multiple tools",
+        priority=3,
+        required_tools=['calculate_statistics', 'get_value_counts']
+    )
+    
+    data_access = DataAccessLayer(sample_data)
+    result = _fallback_task_execution(task, sample_tools, data_access)
+    
+    # Should execute first available tool
+    assert result is not None
+
+
+def test_execution_time_tracking(sample_data, sample_tools):
+    """Test that execution time is tracked."""
+    task = AnalysisTask(
+        id="task_1",
+        name="Test Task",
+        description="Test",
+        priority=3,
+        required_tools=['calculate_statistics']
+    )
+    
+    data_access = DataAccessLayer(sample_data)
+    result = _fallback_task_execution(task, sample_tools, data_access)
+    
+    assert result.execution_time >= 0
+    assert result.execution_time < 10  # Should be fast
+
+
+def test_execution_with_empty_data():
+    """Test execution with empty data."""
+    empty_data = pd.DataFrame()
+    task = AnalysisTask(
+        id="task_1",
+        name="Test Task",
+        description="Test",
+        priority=3,
+        required_tools=['calculate_statistics']
+    )
+    
+    data_access = DataAccessLayer(empty_data)
+    tools = [CalculateStatisticsTool()]
+    
+    result = _fallback_task_execution(task, tools, data_access)
+    
+    # Should handle gracefully
+    assert result is not None