JMeter MCP Server

""" Tests for the metrics calculator. """ import unittest from datetime import datetime, timedelta from analyzer.metrics.calculator import MetricsCalculator from analyzer.models import Sample, TestResults class TestMetricsCalculator(unittest.TestCase): """Tests for the MetricsCalculator class.""" def setUp(self): """Set up test fixtures.""" self.calculator = MetricsCalculator() # Create test results with samples self.test_results = TestResults() # Add samples for endpoint 1 base_time = datetime(2023, 1, 1, 12, 0, 0) for i in range(10): sample = Sample( timestamp=base_time + timedelta(seconds=i), label="Endpoint1", response_time=100 + i * 10, # 100, 110, 120, ..., 190 success=True, response_code="200" ) self.test_results.add_sample(sample) # Add samples for endpoint 2 (including some errors) for i in range(5): sample = Sample( timestamp=base_time + timedelta(seconds=i + 10), label="Endpoint2", response_time=200 + i * 20, # 200, 220, 240, 260, 280 success=i < 4, # Last one is an error response_code="200" if i < 4 else "500", error_message="" if i < 4 else "Internal Server Error" ) self.test_results.add_sample(sample) def test_calculate_overall_metrics(self): """Test calculating overall metrics.""" metrics = self.calculator.calculate_overall_metrics(self.test_results) # Check basic metrics self.assertEqual(metrics.total_samples, 15) self.assertEqual(metrics.error_count, 1) self.assertAlmostEqual(metrics.error_rate, 100 * 1/15) # Check response time metrics expected_response_times = [100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 220, 240, 260, 280] self.assertAlmostEqual(metrics.average_response_time, sum(expected_response_times) / len(expected_response_times)) self.assertAlmostEqual(metrics.median_response_time, 170) # Median of the 15 values self.assertAlmostEqual(metrics.min_response_time, 100) self.assertAlmostEqual(metrics.max_response_time, 280) # Check percentiles self.assertAlmostEqual(metrics.percentile_90, 260) self.assertAlmostEqual(metrics.percentile_95, 270) self.assertAlmostEqual(metrics.percentile_99, 278) # Check throughput and duration self.assertEqual(metrics.test_duration, 14) # 14 seconds from first to last sample self.assertAlmostEqual(metrics.throughput, 15 / 14) # 15 samples over 14 seconds def test_calculate_endpoint_metrics(self): """Test calculating endpoint-specific metrics.""" endpoint_metrics = self.calculator.calculate_endpoint_metrics(self.test_results) # Check that we have metrics for both endpoints self.assertEqual(len(endpoint_metrics), 2) self.assertIn("Endpoint1", endpoint_metrics) self.assertIn("Endpoint2", endpoint_metrics) # Check metrics for endpoint 1 metrics1 = endpoint_metrics["Endpoint1"] self.assertEqual(metrics1.endpoint, "Endpoint1") self.assertEqual(metrics1.total_samples, 10) self.assertEqual(metrics1.error_count, 0) self.assertEqual(metrics1.error_rate, 0) self.assertAlmostEqual(metrics1.average_response_time, 145) # Average of 100, 110, ..., 190 # Check metrics for endpoint 2 metrics2 = endpoint_metrics["Endpoint2"] self.assertEqual(metrics2.endpoint, "Endpoint2") self.assertEqual(metrics2.total_samples, 5) self.assertEqual(metrics2.error_count, 1) self.assertAlmostEqual(metrics2.error_rate, 20) # 1 error out of 5 samples self.assertAlmostEqual(metrics2.average_response_time, 240) # Average of 200, 220, 240, 260, 280 def test_calculate_time_series_metrics(self): """Test calculating time series metrics.""" # Use a 5-second interval time_series = self.calculator.calculate_time_series_metrics(self.test_results, interval_seconds=5) # We should have 3 intervals: 0-5s, 5-10s, 10-15s self.assertEqual(len(time_series), 3) # Check first interval (0-5s) self.assertEqual(time_series[0].timestamp, datetime(2023, 1, 1, 12, 0, 0)) self.assertEqual(time_series[0].active_threads, 0) # No thread names in our test data self.assertAlmostEqual(time_series[0].throughput, 5 / 5) # 5 samples over 5 seconds self.assertAlmostEqual(time_series[0].average_response_time, (100 + 110 + 120 + 130 + 140) / 5) self.assertEqual(time_series[0].error_rate, 0) # No errors in first interval # Check third interval (10-15s) self.assertEqual(time_series[2].timestamp, datetime(2023, 1, 1, 12, 0, 10)) self.assertAlmostEqual(time_series[2].throughput, 5 / 5) # 5 samples over 5 seconds self.assertAlmostEqual(time_series[2].average_response_time, (200 + 220 + 240 + 260 + 280) / 5) self.assertAlmostEqual(time_series[2].error_rate, 20) # 1 error out of 5 samples def test_compare_with_benchmarks(self): """Test comparing metrics with benchmarks.""" # Calculate metrics metrics = self.calculator.calculate_overall_metrics(self.test_results) # Define benchmarks benchmarks = { "average_response_time": 150, "error_rate": 0, "throughput": 2 } # Compare with benchmarks comparison = self.calculator.compare_with_benchmarks(metrics, benchmarks) # Check comparison results self.assertIn("average_response_time", comparison) self.assertIn("error_rate", comparison) self.assertIn("throughput", comparison) # Check average_response_time comparison avg_rt_comp = comparison["average_response_time"] self.assertEqual(avg_rt_comp["benchmark"], 150) self.assertAlmostEqual(avg_rt_comp["actual"], metrics.average_response_time) self.assertAlmostEqual(avg_rt_comp["difference"], metrics.average_response_time - 150) self.assertAlmostEqual(avg_rt_comp["percent_difference"], (metrics.average_response_time - 150) / 150 * 100) # Check error_rate comparison error_rate_comp = comparison["error_rate"] self.assertEqual(error_rate_comp["benchmark"], 0) self.assertAlmostEqual(error_rate_comp["actual"], metrics.error_rate) self.assertAlmostEqual(error_rate_comp["difference"], metrics.error_rate) self.assertEqual(error_rate_comp["percent_difference"], float('inf')) # Division by zero # Check throughput comparison throughput_comp = comparison["throughput"] self.assertEqual(throughput_comp["benchmark"], 2) self.assertAlmostEqual(throughput_comp["actual"], metrics.throughput) self.assertAlmostEqual(throughput_comp["difference"], metrics.throughput - 2) self.assertAlmostEqual(throughput_comp["percent_difference"], (metrics.throughput - 2) / 2 * 100) def test_empty_results(self): """Test calculating metrics for empty test results.""" empty_results = TestResults() with self.assertRaises(ValueError): self.calculator.calculate_overall_metrics(empty_results) with self.assertRaises(ValueError): self.calculator.calculate_endpoint_metrics(empty_results) with self.assertRaises(ValueError): self.calculator.calculate_time_series_metrics(empty_results) def test_invalid_interval(self): """Test calculating time series metrics with invalid interval.""" with self.assertRaises(ValueError): self.calculator.calculate_time_series_metrics(self.test_results, interval_seconds=0) with self.assertRaises(ValueError): self.calculator.calculate_time_series_metrics(self.test_results, interval_seconds=-1) if __name__ == '__main__': unittest.main()