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"""Profile BSBLAN initialization to identify performance bottlenecks.
This script profiles the initialization process of the BSBLAN library
to help identify slow operations that affect Home Assistant startup time.
Usage:
# Basic profiling with auto-discovery or BSBLAN_HOST env var
uv run python examples/profile_init.py
# With explicit host
uv run python examples/profile_init.py --host YOUR_BSBLAN_IP
# With cProfile output
uv run python examples/profile_init.py --cprofile
# Save cProfile stats to file for analysis
uv run python examples/profile_init.py --cprofile --output stats.prof
"""
from __future__ import annotations
import argparse
import asyncio
import cProfile
import pstats
import sys
import time
from contextlib import asynccontextmanager
from pathlib import Path
from typing import TYPE_CHECKING, Any
import aiohttp
if TYPE_CHECKING:
from collections.abc import AsyncIterator
# Add src to path for development
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from bsblan import BSBLAN, BSBLANConfig
from bsblan.exceptions import BSBLANError
from bsblan.utility import APIValidator
from discovery import get_bsblan_host, get_config_from_env
class TimingStats:
"""Collect timing statistics for operations."""
def __init__(self) -> None:
"""Initialize timing stats."""
self.timings: dict[str, float] = {}
self.start_times: dict[str, float] = {}
def start(self, name: str) -> None:
"""Start timing an operation."""
self.start_times[name] = time.perf_counter()
def stop(self, name: str) -> float:
"""Stop timing and return elapsed time."""
elapsed = time.perf_counter() - self.start_times[name]
self.timings[name] = elapsed
return elapsed
@asynccontextmanager
async def measure(self, name: str) -> AsyncIterator[None]:
"""Context manager to measure async operation time."""
self.start(name)
try:
yield
finally:
self.stop(name)
def report(self) -> str:
"""Generate a timing report."""
lines = [
"",
"=" * 60,
"TIMING BREAKDOWN",
"=" * 60,
]
total = sum(self.timings.values())
# Sort by duration, longest first
sorted_timings = sorted(self.timings.items(), key=lambda x: x[1], reverse=True)
for name, duration in sorted_timings:
pct = (duration / total * 100) if total > 0 else 0
bar = "█" * int(pct / 2)
lines.append(f"{name:40} {duration:8.3f}s ({pct:5.1f}%) {bar}")
lines.extend(
[
"-" * 60,
f"{'TOTAL':40} {total:8.3f}s",
"=" * 60,
]
)
return "\n".join(lines)
async def profile_detailed(
config: BSBLANConfig,
) -> tuple[BSBLAN, TimingStats]:
"""Profile initialization with detailed timing of each step.
This profiles the NEW lazy loading approach where sections are
validated on-demand when first accessed.
Note: Caller is responsible for closing client.session on success.
"""
stats = TimingStats()
async with stats.measure("1. Create aiohttp session"):
session = aiohttp.ClientSession()
client = BSBLAN(config=config, session=session)
success = False
try:
# Profile lazy loading initialization (minimal upfront work)
# Access private methods for profiling (pylint: disable=protected-access)
async with stats.measure("2. Initialize (lazy - firmware only)"):
# This now only fetches firmware + sets up validator
await client.initialize()
# Now profile what happens when we actually use sections
# This is where lazy loading kicks in
async with stats.measure("3. First state() call (triggers heating validation)"):
await client.state()
async with stats.measure("4. First sensor() call (triggers sensor validation)"):
await client.sensor()
async with stats.measure("5. First static_values() (triggers staticValues)"):
await client.static_values()
async with stats.measure("6. First hot_water_state() (triggers hot_water)"):
await client.hot_water_state()
success = True
return client, stats
finally:
if not success:
await session.close()
async def profile_hot_water_granular(config: BSBLANConfig) -> TimingStats:
"""Profile granular hot water parameter loading.
This shows the benefit of only loading specific parameter groups
(essential: 5 params, config: 16 params, schedule: 8 params)
instead of all 29 hot water parameters at once.
"""
stats = TimingStats()
async with stats.measure("Create session"):
session = aiohttp.ClientSession()
try:
client = BSBLAN(config=config, session=session)
# Initialize (lazy - firmware only)
async with stats.measure("Initialize (lazy)"):
await client.initialize()
# Profile each hot water method - each validates only its param group
async with stats.measure("hot_water_state (5 essential params)"):
await client.hot_water_state()
async with stats.measure("hot_water_config (16 config params)"):
await client.hot_water_config()
async with stats.measure("hot_water_schedule (8 schedule params)"):
await client.hot_water_schedule()
# Second calls should be instant (already validated)
async with stats.measure("hot_water_state (cached - no validation)"):
await client.hot_water_state()
finally:
await session.close()
return stats
async def profile_sections(config: BSBLANConfig) -> TimingStats:
"""Profile each section validation individually."""
stats = TimingStats()
async with stats.measure("Create session"):
session = aiohttp.ClientSession()
try:
client = BSBLAN(config=config, session=session)
# Get firmware version first (pylint: disable=protected-access)
async with stats.measure("Fetch firmware version"):
await client._fetch_firmware_version() # noqa: SLF001
# Initialize API data before validation
client._api_data = client._copy_api_config() # noqa: SLF001
client._api_validator = APIValidator(client._api_data) # noqa: SLF001
# Profile each section individually
sections = ["heating", "sensor", "staticValues", "device", "hot_water"]
for section in sections:
async with stats.measure(f"Validate section: {section}"):
try:
await client._validate_api_section(section) # type: ignore[arg-type] # noqa: SLF001
except BSBLANError as err:
print(f"Warning: Section {section} validation failed: {err}")
finally:
await session.close()
return stats
async def profile_standard(config: BSBLANConfig) -> tuple[float, BSBLAN]:
"""Profile standard initialization using context manager."""
start = time.perf_counter()
client = BSBLAN(config=config)
await client.__aenter__()
elapsed = time.perf_counter() - start
return elapsed, client
def run_cprofile(config: BSBLANConfig) -> tuple[pstats.Stats, float]:
"""Run cProfile on the initialization."""
profiler = cProfile.Profile()
async def _init() -> tuple[float, Any]:
return await profile_standard(config)
profiler.enable()
elapsed, client = asyncio.run(_init())
profiler.disable()
# Cleanup
asyncio.run(client.__aexit__(None, None, None))
stats = pstats.Stats(profiler)
return stats, elapsed
def parse_args() -> argparse.Namespace:
"""Parse command line arguments."""
parser = argparse.ArgumentParser(
description="Profile BSBLAN initialization performance"
)
parser.add_argument(
"--host",
help="BSBLAN device IP (uses BSBLAN_HOST env or mDNS discovery if not set)",
)
parser.add_argument("--port", type=int, default=80, help="BSBLAN device port")
parser.add_argument("--username", help="Username for authentication")
parser.add_argument("--password", help="Password for authentication")
parser.add_argument("--passkey", help="Passkey for authentication")
parser.add_argument(
"--cprofile", action="store_true", help="Enable cProfile output"
)
parser.add_argument(
"--output", help="Save cProfile stats to file (use with --cprofile)"
)
parser.add_argument(
"--sections",
action="store_true",
help="Profile each section validation individually",
)
parser.add_argument(
"--hot-water",
action="store_true",
help="Profile granular hot water parameter loading",
)
parser.add_argument(
"--repeat",
type=int,
default=1,
help="Number of times to repeat profiling (for averaging)",
)
return parser.parse_args()
def run_cprofile_mode(config: BSBLANConfig, output: str | None) -> None:
"""Run cProfile mode."""
print("\nRunning with cProfile...")
stats, elapsed = run_cprofile(config)
print(f"\nTotal initialization time: {elapsed:.3f}s")
print("\n" + "=" * 60)
print("cProfile Results (top 30 by cumulative time):")
print("=" * 60)
# Print stats to stdout
stats.sort_stats("cumulative")
stats.print_stats(30)
if output:
stats.dump_stats(output)
print(f"\nStats saved to: {output}")
print(f"Analyze with: python -m pstats {output}")
async def run_sections_mode(config: BSBLANConfig) -> None:
"""Run sections profiling mode."""
print("\nProfiling individual section validations...")
stats = await profile_sections(config)
print(stats.report())
async def run_detailed_mode(config: BSBLANConfig, repeat: int) -> None:
"""Run detailed timing mode."""
print("\nRunning detailed timing analysis...")
times: list[float] = []
for i in range(repeat):
if repeat > 1:
print(f"\nRun {i + 1}/{repeat}")
client, stats = await profile_detailed(config)
times.append(sum(stats.timings.values()))
print(stats.report())
# Cleanup
if client.session:
await client.session.close()
if repeat > 1:
avg = sum(times) / len(times)
min_t = min(times)
max_t = max(times)
print("\n" + "=" * 60)
print("SUMMARY ACROSS RUNS")
print("=" * 60)
print(f"Average: {avg:.3f}s")
print(f"Min: {min_t:.3f}s")
print(f"Max: {max_t:.3f}s")
def print_recommendations() -> None:
"""Print optimization recommendations."""
print("\n" + "=" * 60)
print("RECOMMENDATIONS")
print("=" * 60)
print("""
If network requests are slow:
- Check network latency to your BSB-LAN device
- Consider if some validation can be cached/skipped
If section validation is slow:
- The library validates 5 sections sequentially
- Each section requires a network round-trip
- Consider parallel validation or lazy loading
For Home Assistant specifically:
- The integration may benefit from caching device info
- Consider using config entry caching for static data
""")
async def run_hot_water_mode(config: BSBLANConfig) -> None:
"""Run hot water granular profiling mode."""
print("\nProfiling granular hot water parameter loading...")
print("This shows the benefit of only loading specific param groups.\n")
stats = await profile_hot_water_granular(config)
print(stats.report())
async def async_main() -> None:
"""Async main for profiling."""
args = parse_args()
# Get host from args, env, or discovery
if args.host:
host = args.host
port = args.port
else:
host, port = await get_bsblan_host()
# Get credentials from args or env
env_config = get_config_from_env()
username = args.username or env_config.get("username")
password = args.password or env_config.get("password")
passkey = args.passkey or env_config.get("passkey")
config = BSBLANConfig(
host=host,
port=port,
username=username, # type: ignore[arg-type]
password=password, # type: ignore[arg-type]
passkey=passkey, # type: ignore[arg-type]
)
print(f"Profiling BSBLAN initialization for {host}:{port}")
print("=" * 60)
if args.cprofile:
run_cprofile_mode(config, args.output)
elif args.sections:
await run_sections_mode(config)
elif args.hot_water:
await run_hot_water_mode(config)
else:
await run_detailed_mode(config, args.repeat)
print_recommendations()
def main() -> None:
"""Run profiling with command line arguments."""
asyncio.run(async_main())
if __name__ == "__main__":
main()
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