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"""
Initialization Performance Profiler
===================================
Profiles the Epic 2 demo initialization process to identify bottlenecks
and optimize for <5s target.
"""
import time
import logging
from contextlib import contextmanager
from typing import Dict, Any, List
from dataclasses import dataclass, field
logger = logging.getLogger(__name__)
@dataclass
class InitializationStep:
"""Represents a timed initialization step"""
name: str
start_time: float
duration: float
metadata: Dict[str, Any] = field(default_factory=dict)
@property
def duration_ms(self) -> float:
return self.duration * 1000
class InitializationProfiler:
"""Profiles initialization steps for performance optimization"""
def __init__(self):
self.steps: List[InitializationStep] = []
self.start_time: float = 0
self.total_duration: float = 0
def start_profiling(self):
"""Start the initialization profiling"""
self.start_time = time.time()
self.steps.clear()
logger.info("Starting initialization profiling")
def finish_profiling(self):
"""Finish profiling and calculate total time"""
self.total_duration = time.time() - self.start_time
logger.info(f"Initialization profiling completed in {self.total_duration:.2f}s")
@contextmanager
def profile_step(self, step_name: str, metadata: Dict[str, Any] = None):
"""Context manager to profile an initialization step"""
start_time = time.time()
logger.info(f"Starting step: {step_name}")
try:
yield
finally:
duration = time.time() - start_time
step = InitializationStep(
name=step_name,
start_time=start_time,
duration=duration,
metadata=metadata or {}
)
self.steps.append(step)
logger.info(f"Completed step: {step_name} in {duration:.2f}s")
def get_summary(self) -> Dict[str, Any]:
"""Get a summary of initialization performance"""
return {
"total_time_s": self.total_duration,
"target_time_s": 5.0,
"over_target_s": max(0, self.total_duration - 5.0),
"steps": [
{
"name": step.name,
"duration_s": step.duration,
"duration_ms": step.duration_ms,
"percentage": (step.duration / self.total_duration) * 100 if self.total_duration > 0 else 0,
"metadata": step.metadata
}
for step in self.steps
]
}
def print_report(self):
"""Print a detailed profiling report"""
print("\n" + "="*80)
print("INITIALIZATION PERFORMANCE REPORT")
print("="*80)
print(f"Total Time: {self.total_duration:.2f}s (target: 5.0s)")
if self.total_duration <= 5.0:
print("✅ Target achieved!")
else:
print(f"❌ Need to optimize by {self.total_duration - 5.0:.2f}s")
print("\nStep Breakdown:")
print("-" * 80)
print(f"{'Step':<35} {'Time':<10} {'%':<8} {'Details'}")
print("-" * 80)
for step in sorted(self.steps, key=lambda s: s.duration, reverse=True):
percentage = (step.duration / self.total_duration) * 100 if self.total_duration > 0 else 0
details = ", ".join(f"{k}={v}" for k, v in step.metadata.items())
print(f"{step.name:<35} {step.duration:.2f}s{'':<4} {percentage:.1f}%{'':<3} {details}")
print("-" * 80)
print(f"{'TOTAL':<35} {self.total_duration:.2f}s{'':<4} {'100.0%':<8}")
print("="*80)
# Optimization recommendations
print("\nOPTIMIZATION RECOMMENDATIONS:")
print("-" * 80)
slowest_steps = sorted(self.steps, key=lambda s: s.duration, reverse=True)[:3]
for i, step in enumerate(slowest_steps, 1):
print(f"{i}. Optimize '{step.name}' ({step.duration:.2f}s)")
print("\n")
# Global profiler instance
profiler = InitializationProfiler() |