#!/usr/bin/env python3
"""
実際のオブジェクトを使用するE2Eテスト
モックではなく実際のStockDataを作成してserver.pyの処理をテスト
"""
import pytest
import asyncio
from unittest.mock import patch
from src.server import server
from src.models import StockData
from src.finviz_client.screener import FinvizScreener
class TestE2EWithRealObjects:
"""実際のオブジェクトを使用するE2Eテスト"""
def setup_method(self):
"""完全なStockDataオブジェクトを作成"""
self.real_stock_data = StockData(
ticker="AAPL",
company_name="Apple Inc.",
sector="Technology",
industry="Consumer Electronics",
price=180.50,
price_change=2.35,
price_change_percent=1.32,
volume=45000000,
avg_volume=55000000,
market_cap=2800000000000,
pe_ratio=28.5,
eps=6.12,
eps_next_y=6.50,
eps_surprise=0.12,
revenue_surprise=0.08,
dividend_yield=0.48,
beta=1.23,
volatility=0.25,
# パフォーマンス属性
performance_1w=1.8,
performance_1m=4.5, # performance_4w の代替
performance_3m=8.2,
performance_6m=12.7,
performance_ytd=18.9,
performance_1y=22.1,
# テクニカル分析
sma_20=175.80,
sma_50=170.20,
sma_200=165.10,
rsi=58.5,
# 成長指標
eps_qoq_growth=15.2,
sales_qoq_growth=8.7,
target_price=195.0,
# その他の財務指標
debt_to_equity=1.45,
current_ratio=1.05,
roe=28.5,
roa=15.2,
gross_margin=0.38,
operating_margin=0.30,
profit_margin=0.25,
# 所有権情報
insider_ownership=0.07,
institutional_ownership=0.59,
shares_outstanding=15500000000,
shares_float=15400000000,
# 決算関連
earnings_date="2024-01-25",
# 追加のパフォーマンス指標
performance_1min=0.05,
performance_5min=0.12,
performance_30min=0.35,
performance_1h=0.58,
performance_4h=1.25
)
# 複数銘柄のテストデータ（server.pyが期待する形式）
self.mock_results_with_real_objects = [self.real_stock_data]
@pytest.mark.asyncio
async def test_earnings_trading_screener_with_real_stockdata(self):
"""earnings_trading_screenerが実際のStockDataで動作することを確認"""
with patch.object(FinvizScreener, "earnings_trading_screener") as mock_screener:
mock_screener.return_value = self.mock_results_with_real_objects
# 実際にserver.pyが呼び出される
result = await server.call_tool("earnings_trading_screener", {
"earnings_window": "yesterday_after_today_before",
"market_cap": "large",
"min_price": 10.0,
"min_avg_volume": 1000000,
"earnings_revision": "eps_revenue_positive",
"price_trend": "positive_change"
})
# 結果が正常に返されることを確認
assert result is not None
# server.pyでの文字列フォーマットが正常に動作することを確認
assert "AAPL" in str(result)
mock_screener.assert_called_once()
@pytest.mark.asyncio
async def test_earnings_premarket_screener_real_data(self):
"""earnings_premarket_screenerでの実際データ処理テスト"""
with patch.object(FinvizScreener, "earnings_premarket_screener") as mock_screener:
mock_screener.return_value = self.mock_results_with_real_objects
result = await server.call_tool("earnings_premarket_screener", {
"earnings_timing": "today_before",
"market_cap": "large",
"min_price": 50.0,
"min_price_change": 2.0
})
assert result is not None
# 実際のStockDataの属性アクセスが成功することを確認
mock_screener.assert_called_once()
@pytest.mark.asyncio
async def test_volume_surge_screener_comprehensive_attributes(self):
"""volume_surge_screenerでの包括的属性テスト"""
# より多くの属性を持つテストデータ
enhanced_stock = StockData(
ticker="NVDA",
company_name="NVIDIA Corporation",
sector="Technology",
industry="Semiconductors",
price=450.75,
price_change=15.25,
price_change_percent=3.50,
volume=85000000,
avg_volume=45000000,
relative_volume=1.89,
market_cap=1100000000000,
pe_ratio=65.2,
eps=12.45,
performance_1w=8.5,
performance_1m=12.8,
performance_3m=25.7,
volatility=0.45,
rsi=72.3,
sma_20=435.80,
sma_50=420.15,
sma_200=385.90
)
enhanced_results = [enhanced_stock]
with patch.object(FinvizScreener, "volume_surge_screener") as mock_screener:
mock_screener.return_value = enhanced_results
result = await server.call_tool("volume_surge_screener", {
"market_cap": "large",
"min_price": 100.0,
"min_relative_volume": 1.5,
"min_price_change": 3.0,
"sma_filter": "above_sma200"
})
assert result is not None
# 高度な属性アクセスをテスト
assert enhanced_stock.relative_volume == 1.89
assert enhanced_stock.sma_200 == 385.90
mock_screener.assert_called_once()
def test_stockdata_attribute_access_patterns(self):
"""server.pyで使用される属性アクセスパターンを直接テスト"""
stock = self.real_stock_data
# server.pyで実際に行われる処理をシミュレート
try:
# 基本情報のフォーマット
basic_info = [
f"Ticker: {stock.ticker}",
f"Company: {stock.company_name}",
f"Sector: {stock.sector}",
f"Price: ${stock.price:.2f}" if stock.price else "Price: N/A"
]
# パフォーマンス情報のフォーマット
performance_info = [
f"1W Performance: {stock.performance_1w:.2f}%" if stock.performance_1w else "1W Performance: N/A",
f"1M Performance: {stock.performance_1m:.2f}%" if stock.performance_1m else "1M Performance: N/A",
f"3M Performance: {stock.performance_3m:.2f}%" if stock.performance_3m else "3M Performance: N/A"
]
# 決算関連情報のフォーマット
earnings_info = [
f"EPS Surprise: {stock.eps_surprise:.2f}%" if stock.eps_surprise else "EPS Surprise: N/A",
f"Revenue Surprise: {stock.revenue_surprise:.2f}%" if stock.revenue_surprise else "Revenue Surprise: N/A",
f"EPS QoQ Growth: {stock.eps_qoq_growth:.2f}%" if stock.eps_qoq_growth else "EPS QoQ Growth: N/A"
]
# テクニカル情報のフォーマット
technical_info = [
f"RSI: {stock.rsi:.1f}" if stock.rsi else "RSI: N/A",
f"Volatility: {stock.volatility:.2f}" if stock.volatility else "Volatility: N/A",
f"Beta: {stock.beta:.2f}" if stock.beta else "Beta: N/A"
]
# 全ての情報が正常にフォーマットされることを確認
all_info = basic_info + performance_info + earnings_info + technical_info
for info_line in all_info:
assert isinstance(info_line, str)
assert len(info_line) > 0
assert "None" not in info_line # Noneが文字列に含まれていないことを確認
except AttributeError as e:
pytest.fail(f"AttributeError in server.py simulation: {e}")
def test_all_performance_attributes_exist(self):
"""すべてのパフォーマンス属性が存在することを確認"""
stock = self.real_stock_data
# server.pyで参照される可能性のある全パフォーマンス属性
performance_attrs = [
'performance_1min', 'performance_5min', 'performance_30min', 'performance_1h',
'performance_4h', 'performance_1w', 'performance_1m', 'performance_3m',
'performance_6m', 'performance_ytd', 'performance_1y'
]
missing_attrs = []
for attr in performance_attrs:
if not hasattr(stock, attr):
missing_attrs.append(attr)
if missing_attrs:
pytest.fail(f"Missing performance attributes: {missing_attrs}")
# 各属性の値が適切な型であることを確認
for attr in performance_attrs:
value = getattr(stock, attr)
if value is not None:
assert isinstance(value, (int, float)), f"{attr} has invalid type: {type(value)}"
def test_error_prone_attribute_combinations(self):
"""エラーが発生しやすい属性の組み合わせをテスト"""
# 一部の属性がNoneの場合のテスト
partial_stock = StockData(
ticker="PARTIAL",
company_name="Partial Data Corp",
sector="Test",
industry="Test",
# 意図的に一部の属性を設定しない
price=None,
performance_1w=None,
performance_1m=None,
eps_surprise=None,
revenue_surprise=None
)
# Noneの属性に対する安全なアクセスパターンをテスト
try:
price_text = f"Price: ${partial_stock.price:.2f}" if partial_stock.price else "Price: N/A"
perf_1w_text = f"1W Performance: {partial_stock.performance_1w:.2f}%" if partial_stock.performance_1w else "1W Performance: N/A"
perf_1m_text = f"1M Performance: {partial_stock.performance_1m:.2f}%" if partial_stock.performance_1m else "1M Performance: N/A"
eps_text = f"EPS Surprise: {partial_stock.eps_surprise:.2f}%" if partial_stock.eps_surprise else "EPS Surprise: N/A"
# "N/A"が適切に設定されることを確認
assert price_text == "Price: N/A"
assert perf_1w_text == "1W Performance: N/A"
assert perf_1m_text == "1M Performance: N/A"
assert eps_text == "EPS Surprise: N/A"
except (AttributeError, TypeError) as e:
pytest.fail(f"Error handling None attributes: {e}")
if __name__ == "__main__":
pytest.main([__file__, "-v"])
