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The-Ouroboros/tests/test_smart_scanner.py

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16 KiB
Python

"""Tests for SmartVolatilityScanner."""
from __future__ import annotations
import pytest
from unittest.mock import AsyncMock, MagicMock
from src.analysis.smart_scanner import ScanCandidate, SmartVolatilityScanner
from src.analysis.volatility import VolatilityAnalyzer
from src.broker.kis_api import KISBroker
from src.broker.overseas import OverseasBroker
from src.config import Settings
@pytest.fixture
def mock_settings() -> Settings:
"""Create test settings."""
return Settings(
KIS_APP_KEY="test",
KIS_APP_SECRET="test",
KIS_ACCOUNT_NO="12345678-01",
GEMINI_API_KEY="test",
RSI_OVERSOLD_THRESHOLD=30,
RSI_MOMENTUM_THRESHOLD=70,
VOL_MULTIPLIER=2.0,
SCANNER_TOP_N=3,
DB_PATH=":memory:",
)
@pytest.fixture
def mock_broker(mock_settings: Settings) -> MagicMock:
"""Create mock broker."""
broker = MagicMock(spec=KISBroker)
broker._settings = mock_settings
broker.fetch_market_rankings = AsyncMock()
broker.get_daily_prices = AsyncMock()
return broker
@pytest.fixture
def scanner(mock_broker: MagicMock, mock_settings: Settings) -> SmartVolatilityScanner:
"""Create smart scanner instance."""
analyzer = VolatilityAnalyzer()
return SmartVolatilityScanner(
broker=mock_broker,
overseas_broker=None,
volatility_analyzer=analyzer,
settings=mock_settings,
)
@pytest.fixture
def mock_overseas_broker() -> MagicMock:
"""Create mock overseas broker."""
broker = MagicMock(spec=OverseasBroker)
broker.get_overseas_price = AsyncMock()
broker.fetch_overseas_rankings = AsyncMock(return_value=[])
return broker
class TestSmartVolatilityScanner:
"""Test suite for SmartVolatilityScanner."""
@pytest.mark.asyncio
async def test_scan_finds_oversold_candidates(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that scanner identifies oversold stocks with high volume."""
# Mock rankings
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "005930",
"name": "Samsung",
"price": 70000,
"volume": 5000000,
"change_rate": -3.5,
"volume_increase_rate": 250,
},
]
# Mock daily prices - trending down (oversold)
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 75000 - i * 200,
"high": 75500 - i * 200,
"low": 74500 - i * 200,
"close": 75000 - i * 250, # Steady decline
"volume": 2000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
# Should find at least one candidate (depending on exact RSI calculation)
mock_broker.fetch_market_rankings.assert_called_once()
mock_broker.get_daily_prices.assert_called_once_with("005930", days=20)
# If qualified, should have oversold signal
if candidates:
assert candidates[0].signal in ["oversold", "momentum"]
assert candidates[0].volume_ratio >= scanner.vol_multiplier
@pytest.mark.asyncio
async def test_scan_finds_momentum_candidates(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that scanner identifies momentum stocks with high volume."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "035420",
"name": "NAVER",
"price": 250000,
"volume": 3000000,
"change_rate": 5.0,
"volume_increase_rate": 300,
},
]
# Mock daily prices - trending up (momentum)
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 230000 + i * 500,
"high": 231000 + i * 500,
"low": 229000 + i * 500,
"close": 230500 + i * 500, # Steady rise
"volume": 1000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
mock_broker.fetch_market_rankings.assert_called_once()
@pytest.mark.asyncio
async def test_scan_filters_low_volume(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that stocks with low volume ratio are filtered out."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "000660",
"name": "SK Hynix",
"price": 150000,
"volume": 500000,
"change_rate": -5.0,
"volume_increase_rate": 50, # Only 50% increase (< 200%)
},
]
# Low volume
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 150000 - i * 100,
"high": 151000 - i * 100,
"low": 149000 - i * 100,
"close": 150000 - i * 150, # Declining (would be oversold)
"volume": 1000000, # Current 500k < 2x prev day 1M
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
# Should be filtered out due to low volume ratio
assert len(candidates) == 0
@pytest.mark.asyncio
async def test_scan_filters_neutral_rsi(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that stocks with neutral RSI are filtered out."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "051910",
"name": "LG Chem",
"price": 500000,
"volume": 3000000,
"change_rate": 0.5,
"volume_increase_rate": 300, # High volume
},
]
# Flat prices (neutral RSI ~50)
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 500000 + (i % 2) * 100, # Small oscillation
"high": 500500,
"low": 499500,
"close": 500000 + (i % 2) * 50,
"volume": 1000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
# Should be filtered out (RSI ~50, not < 30 or > 70)
assert len(candidates) == 0
@pytest.mark.asyncio
async def test_scan_uses_fallback_on_api_error(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test fallback to static list when ranking API fails."""
mock_broker.fetch_market_rankings.side_effect = ConnectionError("API unavailable")
# Fallback stocks should still be analyzed
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 50000 - i * 50,
"high": 51000 - i * 50,
"low": 49000 - i * 50,
"close": 50000 - i * 75, # Declining
"volume": 1000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan(fallback_stocks=["005930", "000660"])
# Should not crash
assert isinstance(candidates, list)
@pytest.mark.asyncio
async def test_scan_returns_top_n_only(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that scan returns at most top_n candidates."""
# Return many stocks
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": f"00{i}000",
"name": f"Stock{i}",
"price": 10000 * i,
"volume": 5000000,
"change_rate": -10,
"volume_increase_rate": 500,
}
for i in range(1, 10)
]
# All oversold with high volume
def make_prices(code: str) -> list[dict]:
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 10000 - i * 100,
"high": 10500 - i * 100,
"low": 9500 - i * 100,
"close": 10000 - i * 150,
"volume": 1000000,
})
return prices
mock_broker.get_daily_prices.side_effect = make_prices
candidates = await scanner.scan()
# Should respect top_n limit (3)
assert len(candidates) <= scanner.top_n
@pytest.mark.asyncio
async def test_scan_skips_insufficient_price_history(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that stocks with insufficient history are skipped."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "005930",
"name": "Samsung",
"price": 70000,
"volume": 5000000,
"change_rate": -5.0,
"volume_increase_rate": 300,
},
]
# Only 5 days of data (need 15+ for RSI)
mock_broker.get_daily_prices.return_value = [
{
"date": f"2026020{i:02d}",
"open": 70000,
"high": 71000,
"low": 69000,
"close": 70000,
"volume": 2000000,
}
for i in range(5)
]
candidates = await scanner.scan()
# Should skip due to insufficient data
assert len(candidates) == 0
@pytest.mark.asyncio
async def test_get_stock_codes(
self, scanner: SmartVolatilityScanner
) -> None:
"""Test extraction of stock codes from candidates."""
candidates = [
ScanCandidate(
stock_code="005930",
name="Samsung",
price=70000,
volume=5000000,
volume_ratio=2.5,
rsi=28,
signal="oversold",
score=85.0,
),
ScanCandidate(
stock_code="035420",
name="NAVER",
price=250000,
volume=3000000,
volume_ratio=3.0,
rsi=75,
signal="momentum",
score=88.0,
),
]
codes = scanner.get_stock_codes(candidates)
assert codes == ["005930", "035420"]
@pytest.mark.asyncio
async def test_scan_overseas_uses_dynamic_symbols(
self, mock_broker: MagicMock, mock_overseas_broker: MagicMock, mock_settings: Settings
) -> None:
"""Overseas scan should use provided dynamic universe symbols."""
analyzer = VolatilityAnalyzer()
scanner = SmartVolatilityScanner(
broker=mock_broker,
overseas_broker=mock_overseas_broker,
volatility_analyzer=analyzer,
settings=mock_settings,
)
market = MagicMock()
market.name = "NASDAQ"
market.code = "US_NASDAQ"
market.exchange_code = "NASD"
market.is_domestic = False
mock_overseas_broker.get_overseas_price.side_effect = [
{"output": {"last": "210.5", "rate": "1.6", "tvol": "1500000"}},
{"output": {"last": "330.1", "rate": "0.2", "tvol": "900000"}},
]
candidates = await scanner.scan(
market=market,
fallback_stocks=["AAPL", "MSFT"],
)
assert [c.stock_code for c in candidates] == ["AAPL"]
assert candidates[0].signal == "momentum"
assert candidates[0].price == 210.5
@pytest.mark.asyncio
async def test_scan_overseas_uses_ranking_api_first(
self, mock_broker: MagicMock, mock_overseas_broker: MagicMock, mock_settings: Settings
) -> None:
"""Overseas scan should prioritize ranking API when available."""
analyzer = VolatilityAnalyzer()
scanner = SmartVolatilityScanner(
broker=mock_broker,
overseas_broker=mock_overseas_broker,
volatility_analyzer=analyzer,
settings=mock_settings,
)
market = MagicMock()
market.name = "NASDAQ"
market.code = "US_NASDAQ"
market.exchange_code = "NASD"
market.is_domestic = False
mock_overseas_broker.fetch_overseas_rankings.return_value = [
{"symb": "NVDA", "last": "780.2", "rate": "2.4", "tvol": "1200000"},
{"symb": "MSFT", "last": "420.0", "rate": "0.3", "tvol": "900000"},
]
candidates = await scanner.scan(market=market, fallback_stocks=["AAPL", "TSLA"])
mock_overseas_broker.fetch_overseas_rankings.assert_called_once()
mock_overseas_broker.get_overseas_price.assert_not_called()
assert [c.stock_code for c in candidates] == ["NVDA"]
@pytest.mark.asyncio
async def test_scan_overseas_without_symbols_returns_empty(
self, mock_broker: MagicMock, mock_overseas_broker: MagicMock, mock_settings: Settings
) -> None:
"""Overseas scan should return empty list when no symbol universe exists."""
analyzer = VolatilityAnalyzer()
scanner = SmartVolatilityScanner(
broker=mock_broker,
overseas_broker=mock_overseas_broker,
volatility_analyzer=analyzer,
settings=mock_settings,
)
market = MagicMock()
market.name = "NASDAQ"
market.code = "US_NASDAQ"
market.exchange_code = "NASD"
market.is_domestic = False
candidates = await scanner.scan(market=market, fallback_stocks=[])
assert candidates == []
class TestRSICalculation:
"""Test RSI calculation in VolatilityAnalyzer."""
def test_rsi_oversold(self) -> None:
"""Test RSI calculation for downtrending prices."""
analyzer = VolatilityAnalyzer()
# Steadily declining prices
prices = [100 - i * 0.5 for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi < 50 # Should be oversold territory
def test_rsi_overbought(self) -> None:
"""Test RSI calculation for uptrending prices."""
analyzer = VolatilityAnalyzer()
# Steadily rising prices
prices = [100 + i * 0.5 for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi > 50 # Should be overbought territory
def test_rsi_neutral(self) -> None:
"""Test RSI calculation for flat prices."""
analyzer = VolatilityAnalyzer()
# Flat prices with small oscillation
prices = [100 + (i % 2) * 0.1 for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert 40 < rsi < 60 # Should be near neutral
def test_rsi_insufficient_data(self) -> None:
"""Test RSI returns neutral when insufficient data."""
analyzer = VolatilityAnalyzer()
prices = [100, 101, 102] # Only 3 prices, need 15+
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi == 50.0 # Default neutral
def test_rsi_all_gains(self) -> None:
"""Test RSI returns 100 when all gains (no losses)."""
analyzer = VolatilityAnalyzer()
# Monotonic increase
prices = [100 + i for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi == 100.0 # Maximum RSI