#!/usr/bin/env python3
"""
š PARALLEL ORCHESTRATION TESTING SUITE
Test the competition-grade parallel orchestration engine
"""
import asyncio
import json
import sys
import uuid
from datetime import datetime, timezone
def test_parallel_orchestration():
"""Test the new parallel orchestration capabilities"""
print("š Testing Parallel Orchestration Engine")
print("=" * 60)
try:
# Test 1: Basic Fan-Out Fan-In Strategy
print("\nš Test 1: Fan-Out Fan-In Strategy")
task_definitions = [
{
"id": "task_01_frontend",
"type": "code_generation",
"agent_type": "frontend",
"requirements": {
"project_type": "react_app",
"components": ["dashboard", "auth", "profile"]
},
"dependencies": [],
"priority": 8,
"timeout": 120
},
{
"id": "task_02_backend",
"type": "code_generation",
"agent_type": "backend",
"requirements": {
"project_type": "api_server",
"endpoints": ["auth", "users", "data"]
},
"dependencies": [],
"priority": 9,
"timeout": 180
},
{
"id": "task_03_analysis",
"type": "architecture_analysis",
"agent_type": "backend",
"requirements": {
"analysis_type": "scalability",
"target_rps": 10000
},
"dependencies": ["task_01_frontend", "task_02_backend"],
"priority": 7,
"timeout": 90
}
]
# Initialize orchestrator and test
from src.agents.orchestrator import AgentOrchestrator
async def run_test():
orchestrator = AgentOrchestrator(correlation_id="test-parallel-orchestration")
result = await orchestrator.orchestrate_parallel_tasks(
task_definitions=task_definitions,
execution_strategy="dependency_aware"
)
return result
result = asyncio.run(run_test())
# Validate results
print(f" ā
Execution ID: {result['execution_id']}")
print(f" š Strategy: {result['strategy']}")
summary = result['execution_summary']
print(f" š Tasks: {summary['successful_tasks']}/{summary['total_tasks']} successful")
print(f" ā±ļø Total time: {summary['total_execution_time']:.2f}s")
print(f" š Efficiency: {summary['parallelization_efficiency']:.2f}x")
print(f" šÆ Success rate: {summary['success_rate']:.1f}%")
# Performance insights
insights = result['performance_insights']
print(f" šÆ Agent utilization: {insights['agent_utilization']}")
if insights['bottleneck_analysis']:
print(f" ā ļø Bottlenecks: {len(insights['bottleneck_analysis'])} identified")
else:
print(f" ā
No bottlenecks detected")
print(f" š” Recommendations: {len(insights['optimization_recommendations'])}")
# Test 2: Priority-Weighted Strategy
print("\nā” Test 2: Priority-Weighted Strategy")
priority_tasks = [
{
"id": "urgent_fix",
"type": "error_fixing",
"agent_type": "healing",
"requirements": {
"error_context": "Critical production bug",
"code_context": "Authentication service failure"
},
"dependencies": [],
"priority": 10, # Highest priority
"timeout": 60
},
{
"id": "testing_suite",
"type": "testing",
"agent_type": "reviewer",
"requirements": {
"test_type": "integration",
"coverage_target": 85
},
"dependencies": ["urgent_fix"],
"priority": 6,
"timeout": 120
},
{
"id": "deployment_prep",
"type": "deployment",
"agent_type": "devops",
"requirements": {
"environment": "staging",
"rollback_plan": True
},
"dependencies": ["testing_suite"],
"priority": 8,
"timeout": 90
}
]
async def run_priority_test():
orchestrator = AgentOrchestrator(correlation_id="test-priority-orchestration")
result = await orchestrator.orchestrate_parallel_tasks(
task_definitions=priority_tasks,
execution_strategy="priority_weighted"
)
return result
priority_result = asyncio.run(run_priority_test())
print(f" ā
Priority execution completed")
print(f" š Tasks completed: {priority_result['execution_summary']['successful_tasks']}")
print(f" ā±ļø Execution time: {priority_result['execution_summary']['total_execution_time']:.2f}s")
# Test 3: Resource-Optimized Strategy
print("\nš§ Test 3: Resource-Optimized Strategy")
resource_tasks = [
{
"id": f"parallel_task_{i}",
"type": "generic",
"agent_type": ["frontend", "backend", "reviewer", "devops"][i % 4],
"requirements": {"workload": "medium"},
"dependencies": [],
"priority": 5,
"timeout": 30
}
for i in range(8) # 8 parallel tasks to test load balancing
]
async def run_resource_test():
orchestrator = AgentOrchestrator(correlation_id="test-resource-orchestration")
result = await orchestrator.orchestrate_parallel_tasks(
task_definitions=resource_tasks,
execution_strategy="resource_optimized"
)
return result
resource_result = asyncio.run(run_resource_test())
print(f" ā
Resource optimization completed")
print(f" š Tasks: {resource_result['execution_summary']['successful_tasks']}/8")
print(f" šÆ Agent distribution: {resource_result['performance_insights']['agent_utilization']}")
print(f" š Parallelization efficiency: {resource_result['execution_summary']['parallelization_efficiency']:.2f}x")
# Overall assessment
print("\n" + "=" * 60)
print("š PARALLEL ORCHESTRATION TEST SUMMARY")
print(f" ā
Fan-Out Fan-In: {summary['success_rate']:.1f}% success rate")
print(f" ā” Priority-Weighted: {priority_result['execution_summary']['success_rate']:.1f}% success rate")
print(f" š§ Resource-Optimized: {resource_result['execution_summary']['success_rate']:.1f}% success rate")
avg_efficiency = (
summary['parallelization_efficiency'] +
priority_result['execution_summary']['parallelization_efficiency'] +
resource_result['execution_summary']['parallelization_efficiency']
) / 3
print(f" š Average parallelization efficiency: {avg_efficiency:.2f}x")
print(f" šÆ Overall system performance: EXCELLENT")
if avg_efficiency > 2.0:
print(" š COMPETITION-GRADE PERFORMANCE ACHIEVED!")
else:
print(" ā ļø Performance optimization recommended")
return True
except Exception as e:
print(f" ā Test failed: {str(e)}")
import traceback
traceback.print_exc()
return False
if __name__ == "__main__":
print("š COMPETITION-GRADE MCP SERVER")
print("Parallel Orchestration Engine Testing")
print("=" * 60)
success = test_parallel_orchestration()
if success:
print("\nš ALL PARALLEL ORCHESTRATION TESTS PASSED!")
print("š Ready for competition deployment!")
sys.exit(0)
else:
print("\nā PARALLEL ORCHESTRATION TESTS FAILED!")
print("š§ Fix issues before deployment")
sys.exit(1)
