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"""
Comprehensive test suite for the complete Self-Healing ML Pipelines system.
"""
import sys
import os
import json
from pathlib import Path
from datetime import datetime
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
def test_module_imports():
"""Test that all critical modules can be imported."""
print("π§ͺ Testing module imports...")
modules_to_test = [
("utils.config_loader", "ConfigLoader"),
("monitoring.data_drift", "DataDriftDetector"),
("decision_engine.policy_engine", "PolicyEngine"),
("healing.healing_actions", "HealingActions"),
("orchestration.controller", "SelfHealingController"),
("adaptive.adaptive_controller", "AdaptiveHealingController"),
("adaptive_integration", "IntegratedHealingController"),
("orchestration.sla_simulator", "SLASimulator"),
("orchestration.canary_controller", "CanaryController"),
("adaptive.learning.shadow_learner", "ShadowLearner"),
]
all_passed = True
for module_path, class_name in modules_to_test:
try:
module = __import__(module_path, fromlist=[class_name])
getattr(module, class_name)
print(f" β
{module_path}.{class_name}")
except Exception as e:
print(f" β {module_path}.{class_name}: {e}")
all_passed = False
return all_passed
def test_config_files():
"""Test that all configuration files exist and are valid."""
print("\nπ Testing configuration files...")
config_files = [
"configs/pipeline.yaml",
"configs/healing_policies.yaml",
"configs/cost_model.yaml",
"configs/sla_config.yaml",
"configs/canary_config.yaml",
"adaptive/cost_model/action_costs.yaml"
]
all_passed = True
for config_file in config_files:
if os.path.exists(config_file):
try:
# Try to read the file
with open(config_file, 'r') as f:
content = f.read()
if len(content) > 10:
print(f" β
{config_file}")
else:
print(f" β οΈ {config_file}: File too small")
all_passed = False
except Exception as e:
print(f" β {config_file}: Read error - {e}")
all_passed = False
else:
print(f" β {config_file}: Missing")
all_passed = False
return all_passed
def test_data_files():
"""Test that required data files exist."""
print("\nπ Testing data files...")
data_files = [
"adaptive/memory/experiences.json",
"models/current_model.joblib",
"models/current_metadata.json",
"models/fallback/rule_based.joblib"
]
all_passed = True
for data_file in data_files:
if os.path.exists(data_file):
size = os.path.getsize(data_file)
if size > 0:
print(f" β
{data_file} ({size} bytes)")
else:
print(f" β οΈ {data_file}: Empty file")
all_passed = False
else:
print(f" β {data_file}: Missing")
all_passed = False
return all_passed
def test_system_integration():
"""Test the integrated system components."""
print("\nπ Testing system integration...")
from utils.config_loader import ConfigLoader
from monitoring.data_drift import DataDriftDetector
from decision_engine.policy_engine import PolicyEngine
from healing.healing_actions import HealingActions
all_passed = True
try:
# Test ConfigLoader
config = ConfigLoader().load_config()
if config and 'pipeline' in config:
print(" β
ConfigLoader: Loaded configuration")
else:
print(" β ConfigLoader: Failed to load config")
all_passed = False
# Test DataDriftDetector
detector = DataDriftDetector()
drift_result = detector.check_drift([0.1, 0.2, 0.3], [0.15, 0.25, 0.35])
if drift_result is not None:
print(f" β
DataDriftDetector: drift_score={drift_result.get('drift_score', 'N/A')}")
else:
print(" β DataDriftDetector: Failed")
all_passed = False
# Test PolicyEngine
policy_engine = PolicyEngine()
decision = policy_engine.evaluate({'data_drift': 0.25})
if decision:
print(f" β
PolicyEngine: decision={decision.get('action', 'N/A')}")
else:
print(" β PolicyEngine: Failed")
all_passed = False
# Test HealingActions
healing = HealingActions()
print(f" β
HealingActions: Initialized")
except Exception as e:
print(f" β Integration test failed: {e}")
all_passed = False
return all_passed
def test_adaptive_system():
"""Test the adaptive learning components."""
print("\nπ§ Testing adaptive system...")
all_passed = True
try:
# Check experiences
exp_path = "adaptive/memory/experiences.json"
if os.path.exists(exp_path):
with open(exp_path, 'r') as f:
experiences = json.load(f)
print(f" β
Experiences: {len(experiences)} entries")
else:
print(" β οΈ No experiences file")
all_passed = False
# Test Adaptive Controller
from adaptive.adaptive_controller import AdaptiveHealingController
adaptive = AdaptiveHealingController()
context = {'data_drift': 0.15, 'anomaly_rate': 0.05}
decision = adaptive.decide(context)
if decision:
print(f" β
AdaptiveController: decision={decision}")
else:
print(" β AdaptiveController: Failed")
all_passed = False
# Test Integrated Controller
from adaptive_integration import IntegratedHealingController
integrated = IntegratedHealingController()
print(f" β
IntegratedController: mode={integrated.mode}")
except Exception as e:
print(f" β Adaptive test failed: {e}")
all_passed = False
return all_passed
def test_phase3_features():
"""Test Phase 3 enterprise features."""
print("\nπ’ Testing Phase 3 features...")
all_passed = True
try:
# Test SLA Simulator
from orchestration.sla_simulator import SLASimulator
from datetime import datetime, timedelta
sla = SLASimulator()
outcome = {'performance_change': -0.1, 'recovery_time': 150.0}
impact = sla.simulate_sla_impact(
action='retrain',
outcome=outcome,
start_time=datetime.now() - timedelta(minutes=5),
end_time=datetime.now()
)
print(f" β
SLASimulator: {impact.get('action', 'N/A')}")
# Test Canary Controller
from orchestration.canary_controller import CanaryController
canary = CanaryController()
status = canary.get_rollout_status()
print(f" β
CanaryController: stage={status.get('current_stage', 'N/A')}")
# Test Shadow Learner
from adaptive.learning.shadow_learner import ShadowLearner
shadow = ShadowLearner()
context = {'data_drift': 0.25}
shadow_exp = shadow.simulate_decision(context, 'retrain', 'fallback')
print(f" β
ShadowLearner: created experience")
# Test Portfolio Demo
from portfolio.interview_demo import demonstrate_system_capabilities
print(f" β
Portfolio demo: import successful")
except Exception as e:
print(f" β Phase 3 test failed: {e}")
all_passed = False
return all_passed
def run_comprehensive_test():
"""Run all comprehensive tests."""
print("=" * 80)
print("π§ͺ COMPREHENSIVE TEST SUITE - SELF-HEALING ML PIPELINES")
print("=" * 80)
results = {}
# Run all tests
results['imports'] = test_module_imports()
results['configs'] = test_config_files()
results['data'] = test_data_files()
results['integration'] = test_system_integration()
results['adaptive'] = test_adaptive_system()
results['phase3'] = test_phase3_features()
# Summary
print("\n" + "=" * 80)
print("π TEST SUMMARY")
print("=" * 80)
passed = sum(results.values())
total = len(results)
for test_name, result in results.items():
status = "β
PASS" if result else "β FAIL"
print(f"{status} {test_name}")
print(f"\nπ Overall: {passed}/{total} tests passed ({passed/total*100:.1f}%)")
if passed == total:
print("\nπ ALL TESTS PASSED! System is ready for production.")
return True
else:
print(f"\nβ οΈ {total - passed} tests failed. Review issues above.")
return False
if __name__ == "__main__":
success = run_comprehensive_test()
sys.exit(0 if success else 1)
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