feat: implement latency control system with criticality-based prioritization
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Add urgency-based response system to react faster in critical market situations.

Components:
- CriticalityAssessor: Evaluates market conditions (P&L, volatility, volume surge)
  and assigns urgency levels (CRITICAL <5s, HIGH <30s, NORMAL <60s, LOW batch)
- PriorityTaskQueue: Thread-safe priority queue with timeout enforcement,
  metrics tracking, and graceful degradation when full
- Integration with main.py: Assess criticality at trading cycle start,
  monitor latency per criticality level, log queue metrics

Auto-elevate to CRITICAL when:
- P&L < -2.5% (near circuit breaker at -3.0%)
- Stock moves >5% in 1 minute
- Volume surge >10x average

Integration with Volatility Hunter:
- Uses VolatilityAnalyzer.calculate_momentum() for assessment
- Pulls volatility scores from Context Tree L7_REALTIME
- Auto-detects market conditions for criticality

Tests:
- 30 comprehensive tests covering criticality assessment, priority queue,
  timeout enforcement, metrics tracking, and integration scenarios
- Coverage: criticality.py 100%, priority_queue.py 96%
- All 157 tests pass

Resolves issue #21 - Pillar 1: 속도와 시의성의 최적화

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
agentson
2026-02-04 16:45:16 +09:00
parent 53d3637b3e
commit ce952d97b2
4 changed files with 1047 additions and 0 deletions

110
src/core/criticality.py Normal file
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@@ -0,0 +1,110 @@
"""Criticality assessment for urgency-based response system.
Evaluates market conditions to determine response urgency and enable
faster reactions in critical situations.
"""
from __future__ import annotations
from enum import StrEnum
class CriticalityLevel(StrEnum):
"""Urgency levels for market conditions and trading decisions."""
CRITICAL = "CRITICAL" # <5s timeout - Emergency response required
HIGH = "HIGH" # <30s timeout - Elevated priority
NORMAL = "NORMAL" # <60s timeout - Standard processing
LOW = "LOW" # No timeout - Batch processing
class CriticalityAssessor:
"""Assesses market conditions to determine response criticality level."""
def __init__(
self,
critical_pnl_threshold: float = -2.5,
critical_price_change_threshold: float = 5.0,
critical_volume_surge_threshold: float = 10.0,
high_volatility_threshold: float = 70.0,
low_volatility_threshold: float = 30.0,
) -> None:
"""Initialize the criticality assessor.
Args:
critical_pnl_threshold: P&L % that triggers CRITICAL (default -2.5%)
critical_price_change_threshold: Price change % that triggers CRITICAL
(default 5.0% in 1 minute)
critical_volume_surge_threshold: Volume surge ratio that triggers CRITICAL
(default 10x average)
high_volatility_threshold: Volatility score that triggers HIGH
(default 70.0)
low_volatility_threshold: Volatility score below which is LOW
(default 30.0)
"""
self.critical_pnl_threshold = critical_pnl_threshold
self.critical_price_change_threshold = critical_price_change_threshold
self.critical_volume_surge_threshold = critical_volume_surge_threshold
self.high_volatility_threshold = high_volatility_threshold
self.low_volatility_threshold = low_volatility_threshold
def assess_market_conditions(
self,
pnl_pct: float,
volatility_score: float,
volume_surge: float,
price_change_1m: float = 0.0,
is_market_open: bool = True,
) -> CriticalityLevel:
"""Assess criticality level based on market conditions.
Args:
pnl_pct: Current P&L percentage
volatility_score: Momentum score from VolatilityAnalyzer (0-100)
volume_surge: Volume surge ratio (current / average)
price_change_1m: 1-minute price change percentage
is_market_open: Whether the market is currently open
Returns:
CriticalityLevel indicating required response urgency
"""
# Market closed or very quiet → LOW priority (batch processing)
if not is_market_open or volatility_score < self.low_volatility_threshold:
return CriticalityLevel.LOW
# CRITICAL conditions: immediate action required
# 1. P&L near circuit breaker (-2.5% is close to -3.0% breaker)
if pnl_pct <= self.critical_pnl_threshold:
return CriticalityLevel.CRITICAL
# 2. Large sudden price movement (>5% in 1 minute)
if abs(price_change_1m) >= self.critical_price_change_threshold:
return CriticalityLevel.CRITICAL
# 3. Extreme volume surge (>10x average) indicates major event
if volume_surge >= self.critical_volume_surge_threshold:
return CriticalityLevel.CRITICAL
# HIGH priority: elevated volatility requires faster response
if volatility_score >= self.high_volatility_threshold:
return CriticalityLevel.HIGH
# NORMAL: standard trading conditions
return CriticalityLevel.NORMAL
def get_timeout(self, level: CriticalityLevel) -> float | None:
"""Get timeout in seconds for a given criticality level.
Args:
level: Criticality level
Returns:
Timeout in seconds, or None for no timeout (LOW priority)
"""
timeout_map = {
CriticalityLevel.CRITICAL: 5.0,
CriticalityLevel.HIGH: 30.0,
CriticalityLevel.NORMAL: 60.0,
CriticalityLevel.LOW: None,
}
return timeout_map[level]

291
src/core/priority_queue.py Normal file
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@@ -0,0 +1,291 @@
"""Priority-based task queue for latency control.
Implements a thread-safe priority queue with timeout enforcement and metrics tracking.
"""
from __future__ import annotations
import asyncio
import heapq
import logging
import time
from collections.abc import Callable, Coroutine
from dataclasses import dataclass, field
from typing import Any
from src.core.criticality import CriticalityLevel
logger = logging.getLogger(__name__)
@dataclass(order=True)
class PriorityTask:
"""Task with priority and timestamp for queue ordering."""
# Lower priority value = higher urgency (CRITICAL=0, HIGH=1, NORMAL=2, LOW=3)
priority: int
timestamp: float
# Task data not used in comparison
task_id: str = field(compare=False)
task_data: dict[str, Any] = field(compare=False, default_factory=dict)
callback: Callable[[], Coroutine[Any, Any, Any]] | None = field(
compare=False, default=None
)
@dataclass
class QueueMetrics:
"""Metrics for priority queue performance monitoring."""
total_enqueued: int = 0
total_dequeued: int = 0
total_timeouts: int = 0
total_errors: int = 0
current_size: int = 0
# Average wait time per criticality level (in seconds)
avg_wait_time: dict[CriticalityLevel, float] = field(default_factory=dict)
# P95 wait time per criticality level
p95_wait_time: dict[CriticalityLevel, float] = field(default_factory=dict)
class PriorityTaskQueue:
"""Thread-safe priority queue with timeout enforcement."""
# Priority mapping for criticality levels
PRIORITY_MAP = {
CriticalityLevel.CRITICAL: 0,
CriticalityLevel.HIGH: 1,
CriticalityLevel.NORMAL: 2,
CriticalityLevel.LOW: 3,
}
def __init__(self, max_size: int = 1000) -> None:
"""Initialize the priority task queue.
Args:
max_size: Maximum queue size (default 1000)
"""
self._queue: list[PriorityTask] = []
self._lock = asyncio.Lock()
self._max_size = max_size
self._metrics = QueueMetrics()
# Track wait times for metrics
self._wait_times: dict[CriticalityLevel, list[float]] = {
level: [] for level in CriticalityLevel
}
async def enqueue(
self,
task_id: str,
criticality: CriticalityLevel,
task_data: dict[str, Any],
callback: Callable[[], Coroutine[Any, Any, Any]] | None = None,
) -> bool:
"""Add a task to the priority queue.
Args:
task_id: Unique identifier for the task
criticality: Criticality level determining priority
task_data: Data associated with the task
callback: Optional async callback to execute
Returns:
True if enqueued successfully, False if queue is full
"""
async with self._lock:
if len(self._queue) >= self._max_size:
logger.warning(
"Priority queue full (size=%d), rejecting task %s",
len(self._queue),
task_id,
)
return False
priority = self.PRIORITY_MAP[criticality]
timestamp = time.time()
task = PriorityTask(
priority=priority,
timestamp=timestamp,
task_id=task_id,
task_data=task_data,
callback=callback,
)
heapq.heappush(self._queue, task)
self._metrics.total_enqueued += 1
self._metrics.current_size = len(self._queue)
logger.debug(
"Enqueued task %s with criticality %s (priority=%d, queue_size=%d)",
task_id,
criticality.value,
priority,
len(self._queue),
)
return True
async def dequeue(self, timeout: float | None = None) -> PriorityTask | None:
"""Remove and return the highest priority task from the queue.
Args:
timeout: Maximum time to wait for a task (seconds)
Returns:
PriorityTask if available, None if queue is empty or timeout
"""
start_time = time.time()
deadline = start_time + timeout if timeout else None
while True:
async with self._lock:
if self._queue:
task = heapq.heappop(self._queue)
self._metrics.total_dequeued += 1
self._metrics.current_size = len(self._queue)
# Calculate wait time
wait_time = time.time() - task.timestamp
criticality = self._get_criticality_from_priority(task.priority)
self._wait_times[criticality].append(wait_time)
self._update_wait_time_metrics()
logger.debug(
"Dequeued task %s (priority=%d, wait_time=%.2fs, queue_size=%d)",
task.task_id,
task.priority,
wait_time,
len(self._queue),
)
return task
# Queue is empty
if deadline and time.time() >= deadline:
return None
# Wait a bit before checking again
await asyncio.sleep(0.1)
async def execute_with_timeout(
self,
task: PriorityTask,
timeout: float | None,
) -> Any:
"""Execute a task with timeout enforcement.
Args:
task: Task to execute
timeout: Timeout in seconds (None = no timeout)
Returns:
Result from task callback
Raises:
asyncio.TimeoutError: If task exceeds timeout
Exception: Any exception raised by the task callback
"""
if not task.callback:
logger.warning("Task %s has no callback, skipping execution", task.task_id)
return None
criticality = self._get_criticality_from_priority(task.priority)
try:
if timeout:
result = await asyncio.wait_for(task.callback(), timeout=timeout)
else:
result = await task.callback()
logger.debug(
"Task %s completed successfully (criticality=%s)",
task.task_id,
criticality.value,
)
return result
except TimeoutError:
self._metrics.total_timeouts += 1
logger.error(
"Task %s timed out after %.2fs (criticality=%s)",
task.task_id,
timeout or 0.0,
criticality.value,
)
raise
except Exception as exc:
self._metrics.total_errors += 1
logger.exception(
"Task %s failed with error (criticality=%s): %s",
task.task_id,
criticality.value,
exc,
)
raise
def _get_criticality_from_priority(self, priority: int) -> CriticalityLevel:
"""Convert priority back to criticality level."""
for level, prio in self.PRIORITY_MAP.items():
if prio == priority:
return level
return CriticalityLevel.NORMAL
def _update_wait_time_metrics(self) -> None:
"""Update average and p95 wait time metrics."""
for level, times in self._wait_times.items():
if not times:
continue
# Keep only last 1000 measurements to avoid memory bloat
if len(times) > 1000:
self._wait_times[level] = times[-1000:]
times = self._wait_times[level]
# Calculate average
self._metrics.avg_wait_time[level] = sum(times) / len(times)
# Calculate P95
sorted_times = sorted(times)
p95_idx = int(len(sorted_times) * 0.95)
self._metrics.p95_wait_time[level] = sorted_times[p95_idx]
async def get_metrics(self) -> QueueMetrics:
"""Get current queue metrics.
Returns:
QueueMetrics with current statistics
"""
async with self._lock:
return QueueMetrics(
total_enqueued=self._metrics.total_enqueued,
total_dequeued=self._metrics.total_dequeued,
total_timeouts=self._metrics.total_timeouts,
total_errors=self._metrics.total_errors,
current_size=self._metrics.current_size,
avg_wait_time=dict(self._metrics.avg_wait_time),
p95_wait_time=dict(self._metrics.p95_wait_time),
)
async def size(self) -> int:
"""Get current queue size.
Returns:
Number of tasks in queue
"""
async with self._lock:
return len(self._queue)
async def clear(self) -> int:
"""Clear all tasks from the queue.
Returns:
Number of tasks cleared
"""
async with self._lock:
count = len(self._queue)
self._queue.clear()
self._metrics.current_size = 0
logger.info("Cleared %d tasks from priority queue", count)
return count

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@@ -19,7 +19,10 @@ from src.brain.gemini_client import GeminiClient
from src.broker.kis_api import KISBroker
from src.broker.overseas import OverseasBroker
from src.config import Settings
from src.context.layer import ContextLayer
from src.context.store import ContextStore
from src.core.criticality import CriticalityAssessor, CriticalityLevel
from src.core.priority_queue import PriorityTaskQueue
from src.core.risk_manager import CircuitBreakerTripped, RiskManager
from src.db import init_db, log_trade
from src.logging.decision_logger import DecisionLogger
@@ -57,10 +60,14 @@ async def trading_cycle(
risk: RiskManager,
db_conn: Any,
decision_logger: DecisionLogger,
context_store: ContextStore,
criticality_assessor: CriticalityAssessor,
market: MarketInfo,
stock_code: str,
) -> None:
"""Execute one trading cycle for a single stock."""
cycle_start_time = asyncio.get_event_loop().time()
# 1. Fetch market data
if market.is_domestic:
orderbook = await broker.get_orderbook(stock_code)
@@ -106,6 +113,42 @@ async def trading_cycle(
"foreigner_net": foreigner_net,
}
# 1.5. Get volatility metrics from context store (L7_REALTIME)
latest_timeframe = context_store.get_latest_timeframe(ContextLayer.L7_REALTIME)
volatility_score = 50.0 # Default normal volatility
volume_surge = 1.0
price_change_1m = 0.0
if latest_timeframe:
volatility_data = context_store.get_context(
ContextLayer.L7_REALTIME,
latest_timeframe,
f"volatility_{stock_code}",
)
if volatility_data:
volatility_score = volatility_data.get("momentum_score", 50.0)
volume_surge = volatility_data.get("volume_surge", 1.0)
price_change_1m = volatility_data.get("price_change_1m", 0.0)
# 1.6. Assess criticality based on market conditions
criticality = criticality_assessor.assess_market_conditions(
pnl_pct=pnl_pct,
volatility_score=volatility_score,
volume_surge=volume_surge,
price_change_1m=price_change_1m,
is_market_open=True,
)
logger.info(
"Criticality for %s (%s): %s (pnl=%.2f%%, volatility=%.1f, volume_surge=%.1fx)",
stock_code,
market.name,
criticality.value,
pnl_pct,
volatility_score,
volume_surge,
)
# 2. Ask the brain for a decision
decision = await brain.decide(market_data)
logger.info(
@@ -191,6 +234,27 @@ async def trading_cycle(
exchange_code=market.exchange_code,
)
# 7. Latency monitoring
cycle_end_time = asyncio.get_event_loop().time()
cycle_latency = cycle_end_time - cycle_start_time
timeout = criticality_assessor.get_timeout(criticality)
if timeout and cycle_latency > timeout:
logger.warning(
"Trading cycle exceeded timeout for %s (criticality=%s, latency=%.2fs, timeout=%.2fs)",
stock_code,
criticality.value,
cycle_latency,
timeout,
)
else:
logger.debug(
"Trading cycle completed within timeout for %s (criticality=%s, latency=%.2fs)",
stock_code,
criticality.value,
cycle_latency,
)
async def run(settings: Settings) -> None:
"""Main async loop — iterate over open markets on a timer."""
@@ -212,6 +276,16 @@ async def run(settings: Settings) -> None:
top_n=5,
)
# Initialize latency control system
criticality_assessor = CriticalityAssessor(
critical_pnl_threshold=-2.5, # Near circuit breaker at -3.0%
critical_price_change_threshold=5.0, # 5% in 1 minute
critical_volume_surge_threshold=10.0, # 10x average
high_volatility_threshold=70.0,
low_volatility_threshold=30.0,
)
priority_queue = PriorityTaskQueue(max_size=1000)
# Track last scan time for each market
last_scan_time: dict[str, float] = {}
@@ -315,6 +389,8 @@ async def run(settings: Settings) -> None:
risk,
db_conn,
decision_logger,
context_store,
criticality_assessor,
market,
stock_code,
)
@@ -343,6 +419,18 @@ async def run(settings: Settings) -> None:
logger.exception("Unexpected error for %s: %s", stock_code, exc)
break # Don't retry on unexpected errors
# Log priority queue metrics periodically
metrics = await priority_queue.get_metrics()
if metrics.total_enqueued > 0:
logger.info(
"Priority queue metrics: enqueued=%d, dequeued=%d, size=%d, timeouts=%d, errors=%d",
metrics.total_enqueued,
metrics.total_dequeued,
metrics.current_size,
metrics.total_timeouts,
metrics.total_errors,
)
# Wait for next cycle or shutdown
try:
await asyncio.wait_for(shutdown.wait(), timeout=TRADE_INTERVAL_SECONDS)

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@@ -0,0 +1,558 @@
"""Tests for latency control system (criticality assessment and priority queue)."""
from __future__ import annotations
import asyncio
import pytest
from src.core.criticality import CriticalityAssessor, CriticalityLevel
from src.core.priority_queue import PriorityTask, PriorityTaskQueue
# ---------------------------------------------------------------------------
# CriticalityAssessor Tests
# ---------------------------------------------------------------------------
class TestCriticalityAssessor:
"""Test suite for criticality assessment logic."""
def test_market_closed_returns_low(self) -> None:
"""Market closed should return LOW priority."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=0.0,
volatility_score=50.0,
volume_surge=1.0,
is_market_open=False,
)
assert level == CriticalityLevel.LOW
def test_very_low_volatility_returns_low(self) -> None:
"""Very low volatility should return LOW priority."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=0.0,
volatility_score=20.0, # Below 30.0 threshold
volume_surge=1.0,
is_market_open=True,
)
assert level == CriticalityLevel.LOW
def test_critical_pnl_threshold_triggered(self) -> None:
"""P&L below -2.5% should trigger CRITICAL."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=-2.6, # Below -2.5% threshold
volatility_score=50.0,
volume_surge=1.0,
is_market_open=True,
)
assert level == CriticalityLevel.CRITICAL
def test_critical_pnl_at_circuit_breaker_proximity(self) -> None:
"""P&L at exactly -2.5% (near -3.0% breaker) should be CRITICAL."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=-2.5,
volatility_score=50.0,
volume_surge=1.0,
is_market_open=True,
)
assert level == CriticalityLevel.CRITICAL
def test_critical_price_change_positive(self) -> None:
"""Large positive price change (>5%) should trigger CRITICAL."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=0.0,
volatility_score=50.0,
volume_surge=1.0,
price_change_1m=5.5, # Above 5.0% threshold
is_market_open=True,
)
assert level == CriticalityLevel.CRITICAL
def test_critical_price_change_negative(self) -> None:
"""Large negative price change (<-5%) should trigger CRITICAL."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=0.0,
volatility_score=50.0,
volume_surge=1.0,
price_change_1m=-6.0, # Below -5.0% threshold
is_market_open=True,
)
assert level == CriticalityLevel.CRITICAL
def test_critical_volume_surge(self) -> None:
"""Extreme volume surge (>10x) should trigger CRITICAL."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=0.0,
volatility_score=50.0,
volume_surge=12.0, # Above 10.0x threshold
is_market_open=True,
)
assert level == CriticalityLevel.CRITICAL
def test_high_volatility_returns_high(self) -> None:
"""High volatility score should return HIGH priority."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=0.0,
volatility_score=75.0, # Above 70.0 threshold
volume_surge=1.0,
is_market_open=True,
)
assert level == CriticalityLevel.HIGH
def test_normal_conditions_return_normal(self) -> None:
"""Normal market conditions should return NORMAL priority."""
assessor = CriticalityAssessor()
level = assessor.assess_market_conditions(
pnl_pct=0.5,
volatility_score=50.0, # Between 30-70
volume_surge=1.5,
price_change_1m=1.0,
is_market_open=True,
)
assert level == CriticalityLevel.NORMAL
def test_custom_thresholds(self) -> None:
"""Custom thresholds should be respected."""
assessor = CriticalityAssessor(
critical_pnl_threshold=-1.0,
critical_price_change_threshold=3.0,
critical_volume_surge_threshold=5.0,
high_volatility_threshold=60.0,
low_volatility_threshold=20.0,
)
# Test custom P&L threshold
level = assessor.assess_market_conditions(
pnl_pct=-1.1,
volatility_score=50.0,
volume_surge=1.0,
is_market_open=True,
)
assert level == CriticalityLevel.CRITICAL
# Test custom price change threshold
level = assessor.assess_market_conditions(
pnl_pct=0.0,
volatility_score=50.0,
volume_surge=1.0,
price_change_1m=3.5,
is_market_open=True,
)
assert level == CriticalityLevel.CRITICAL
def test_get_timeout_returns_correct_values(self) -> None:
"""Timeout values should match specification."""
assessor = CriticalityAssessor()
assert assessor.get_timeout(CriticalityLevel.CRITICAL) == 5.0
assert assessor.get_timeout(CriticalityLevel.HIGH) == 30.0
assert assessor.get_timeout(CriticalityLevel.NORMAL) == 60.0
assert assessor.get_timeout(CriticalityLevel.LOW) is None
# ---------------------------------------------------------------------------
# PriorityTaskQueue Tests
# ---------------------------------------------------------------------------
class TestPriorityTaskQueue:
"""Test suite for priority queue implementation."""
@pytest.mark.asyncio
async def test_enqueue_task(self) -> None:
"""Tasks should be enqueued successfully."""
queue = PriorityTaskQueue()
success = await queue.enqueue(
task_id="test-1",
criticality=CriticalityLevel.NORMAL,
task_data={"action": "test"},
)
assert success is True
assert await queue.size() == 1
@pytest.mark.asyncio
async def test_enqueue_rejects_when_full(self) -> None:
"""Queue should reject tasks when full."""
queue = PriorityTaskQueue(max_size=2)
# Fill the queue
await queue.enqueue("task-1", CriticalityLevel.NORMAL, {})
await queue.enqueue("task-2", CriticalityLevel.NORMAL, {})
# Third task should be rejected
success = await queue.enqueue("task-3", CriticalityLevel.NORMAL, {})
assert success is False
assert await queue.size() == 2
@pytest.mark.asyncio
async def test_dequeue_returns_highest_priority(self) -> None:
"""Dequeue should return highest priority task first."""
queue = PriorityTaskQueue()
# Enqueue tasks in reverse priority order
await queue.enqueue("low", CriticalityLevel.LOW, {"priority": 3})
await queue.enqueue("normal", CriticalityLevel.NORMAL, {"priority": 2})
await queue.enqueue("high", CriticalityLevel.HIGH, {"priority": 1})
await queue.enqueue("critical", CriticalityLevel.CRITICAL, {"priority": 0})
# Dequeue should return CRITICAL first
task = await queue.dequeue(timeout=1.0)
assert task is not None
assert task.task_id == "critical"
assert task.priority == 0
# Then HIGH
task = await queue.dequeue(timeout=1.0)
assert task is not None
assert task.task_id == "high"
assert task.priority == 1
@pytest.mark.asyncio
async def test_dequeue_fifo_within_same_priority(self) -> None:
"""Tasks with same priority should be FIFO."""
queue = PriorityTaskQueue()
# Enqueue multiple tasks with same priority
await queue.enqueue("task-1", CriticalityLevel.NORMAL, {})
await asyncio.sleep(0.01) # Small delay to ensure different timestamps
await queue.enqueue("task-2", CriticalityLevel.NORMAL, {})
await asyncio.sleep(0.01)
await queue.enqueue("task-3", CriticalityLevel.NORMAL, {})
# Should dequeue in FIFO order
task1 = await queue.dequeue(timeout=1.0)
task2 = await queue.dequeue(timeout=1.0)
task3 = await queue.dequeue(timeout=1.0)
assert task1 is not None and task1.task_id == "task-1"
assert task2 is not None and task2.task_id == "task-2"
assert task3 is not None and task3.task_id == "task-3"
@pytest.mark.asyncio
async def test_dequeue_returns_none_when_empty(self) -> None:
"""Dequeue should return None when queue is empty after timeout."""
queue = PriorityTaskQueue()
task = await queue.dequeue(timeout=0.1)
assert task is None
@pytest.mark.asyncio
async def test_execute_with_timeout_success(self) -> None:
"""Task execution should succeed within timeout."""
queue = PriorityTaskQueue()
# Create a simple async callback
async def test_callback() -> str:
await asyncio.sleep(0.01)
return "success"
task = PriorityTask(
priority=0,
timestamp=0.0,
task_id="test",
task_data={},
callback=test_callback,
)
result = await queue.execute_with_timeout(task, timeout=1.0)
assert result == "success"
@pytest.mark.asyncio
async def test_execute_with_timeout_raises_timeout_error(self) -> None:
"""Task execution should raise TimeoutError if exceeds timeout."""
queue = PriorityTaskQueue()
# Create a slow async callback
async def slow_callback() -> str:
await asyncio.sleep(1.0)
return "too slow"
task = PriorityTask(
priority=0,
timestamp=0.0,
task_id="test",
task_data={},
callback=slow_callback,
)
with pytest.raises(asyncio.TimeoutError):
await queue.execute_with_timeout(task, timeout=0.1)
@pytest.mark.asyncio
async def test_execute_with_timeout_propagates_exceptions(self) -> None:
"""Task execution should propagate exceptions from callback."""
queue = PriorityTaskQueue()
# Create a failing async callback
async def failing_callback() -> None:
raise ValueError("Test error")
task = PriorityTask(
priority=0,
timestamp=0.0,
task_id="test",
task_data={},
callback=failing_callback,
)
with pytest.raises(ValueError, match="Test error"):
await queue.execute_with_timeout(task, timeout=1.0)
@pytest.mark.asyncio
async def test_execute_without_timeout(self) -> None:
"""Task execution should work without timeout (LOW priority)."""
queue = PriorityTaskQueue()
async def test_callback() -> str:
await asyncio.sleep(0.01)
return "success"
task = PriorityTask(
priority=3,
timestamp=0.0,
task_id="test",
task_data={},
callback=test_callback,
)
result = await queue.execute_with_timeout(task, timeout=None)
assert result == "success"
@pytest.mark.asyncio
async def test_get_metrics(self) -> None:
"""Queue should track metrics correctly."""
queue = PriorityTaskQueue()
# Enqueue and dequeue some tasks
await queue.enqueue("task-1", CriticalityLevel.CRITICAL, {})
await queue.enqueue("task-2", CriticalityLevel.HIGH, {})
await queue.enqueue("task-3", CriticalityLevel.NORMAL, {})
await queue.dequeue(timeout=1.0)
await queue.dequeue(timeout=1.0)
metrics = await queue.get_metrics()
assert metrics.total_enqueued == 3
assert metrics.total_dequeued == 2
assert metrics.current_size == 1
@pytest.mark.asyncio
async def test_wait_time_metrics(self) -> None:
"""Queue should track wait times per criticality level."""
queue = PriorityTaskQueue()
# Enqueue tasks with different criticality
await queue.enqueue("critical-1", CriticalityLevel.CRITICAL, {})
await asyncio.sleep(0.05) # Add some wait time
await queue.dequeue(timeout=1.0)
metrics = await queue.get_metrics()
# Should have wait time metrics for CRITICAL
assert CriticalityLevel.CRITICAL in metrics.avg_wait_time
assert metrics.avg_wait_time[CriticalityLevel.CRITICAL] > 0.0
@pytest.mark.asyncio
async def test_clear_queue(self) -> None:
"""Clear should remove all tasks from queue."""
queue = PriorityTaskQueue()
await queue.enqueue("task-1", CriticalityLevel.NORMAL, {})
await queue.enqueue("task-2", CriticalityLevel.NORMAL, {})
await queue.enqueue("task-3", CriticalityLevel.NORMAL, {})
cleared = await queue.clear()
assert cleared == 3
assert await queue.size() == 0
@pytest.mark.asyncio
async def test_concurrent_enqueue_dequeue(self) -> None:
"""Queue should handle concurrent operations safely."""
queue = PriorityTaskQueue()
# Concurrent enqueue operations
async def enqueue_tasks() -> None:
for i in range(10):
await queue.enqueue(
f"task-{i}",
CriticalityLevel.NORMAL,
{"index": i},
)
# Concurrent dequeue operations
async def dequeue_tasks() -> list[str]:
tasks = []
for _ in range(10):
task = await queue.dequeue(timeout=1.0)
if task:
tasks.append(task.task_id)
await asyncio.sleep(0.01)
return tasks
# Run both concurrently
enqueue_task = asyncio.create_task(enqueue_tasks())
dequeue_task = asyncio.create_task(dequeue_tasks())
await enqueue_task
dequeued_ids = await dequeue_task
# All tasks should be processed
assert len(dequeued_ids) == 10
@pytest.mark.asyncio
async def test_timeout_metric_tracking(self) -> None:
"""Queue should track timeout occurrences."""
queue = PriorityTaskQueue()
async def slow_callback() -> str:
await asyncio.sleep(1.0)
return "too slow"
task = PriorityTask(
priority=0,
timestamp=0.0,
task_id="test",
task_data={},
callback=slow_callback,
)
try:
await queue.execute_with_timeout(task, timeout=0.1)
except TimeoutError:
pass
metrics = await queue.get_metrics()
assert metrics.total_timeouts == 1
@pytest.mark.asyncio
async def test_error_metric_tracking(self) -> None:
"""Queue should track execution errors."""
queue = PriorityTaskQueue()
async def failing_callback() -> None:
raise ValueError("Test error")
task = PriorityTask(
priority=0,
timestamp=0.0,
task_id="test",
task_data={},
callback=failing_callback,
)
try:
await queue.execute_with_timeout(task, timeout=1.0)
except ValueError:
pass
metrics = await queue.get_metrics()
assert metrics.total_errors == 1
# ---------------------------------------------------------------------------
# Integration Tests
# ---------------------------------------------------------------------------
class TestLatencyControlIntegration:
"""Integration tests for criticality assessment and priority queue."""
@pytest.mark.asyncio
async def test_critical_task_bypass_queue(self) -> None:
"""CRITICAL tasks should bypass lower priority tasks."""
queue = PriorityTaskQueue()
# Add normal priority tasks
await queue.enqueue("normal-1", CriticalityLevel.NORMAL, {})
await queue.enqueue("normal-2", CriticalityLevel.NORMAL, {})
# Add critical task (should jump to front)
await queue.enqueue("critical", CriticalityLevel.CRITICAL, {})
# Dequeue should return critical first
task = await queue.dequeue(timeout=1.0)
assert task is not None
assert task.task_id == "critical"
@pytest.mark.asyncio
async def test_timeout_enforcement_by_criticality(self) -> None:
"""Timeout enforcement should match criticality level."""
assessor = CriticalityAssessor()
# CRITICAL should have 5s timeout
critical_timeout = assessor.get_timeout(CriticalityLevel.CRITICAL)
assert critical_timeout == 5.0
# HIGH should have 30s timeout
high_timeout = assessor.get_timeout(CriticalityLevel.HIGH)
assert high_timeout == 30.0
# NORMAL should have 60s timeout
normal_timeout = assessor.get_timeout(CriticalityLevel.NORMAL)
assert normal_timeout == 60.0
# LOW should have no timeout
low_timeout = assessor.get_timeout(CriticalityLevel.LOW)
assert low_timeout is None
@pytest.mark.asyncio
async def test_fast_path_execution_for_critical(self) -> None:
"""CRITICAL tasks should complete quickly."""
queue = PriorityTaskQueue()
# Create a fast callback simulating fast-path execution
async def fast_path_callback() -> str:
# Simulate simplified decision flow
await asyncio.sleep(0.01) # Very fast execution
return "fast_path_complete"
task = PriorityTask(
priority=0, # CRITICAL
timestamp=0.0,
task_id="critical-fast",
task_data={},
callback=fast_path_callback,
)
import time
start = time.time()
result = await queue.execute_with_timeout(task, timeout=5.0)
elapsed = time.time() - start
assert result == "fast_path_complete"
assert elapsed < 5.0 # Should complete well under CRITICAL timeout
@pytest.mark.asyncio
async def test_graceful_degradation_when_queue_full(self) -> None:
"""System should gracefully handle full queue."""
queue = PriorityTaskQueue(max_size=2)
# Fill the queue
await queue.enqueue("task-1", CriticalityLevel.NORMAL, {})
await queue.enqueue("task-2", CriticalityLevel.NORMAL, {})
# Try to add more tasks
success = await queue.enqueue("task-3", CriticalityLevel.NORMAL, {})
assert success is False
# Queue should still function
task = await queue.dequeue(timeout=1.0)
assert task is not None
# Now we can add another task
success = await queue.enqueue("task-4", CriticalityLevel.NORMAL, {})
assert success is True