aa52047f14
- _fetch_market_microstructure: oi_val > 0 체크 후에만 _calc_oi_change 호출하여 API 실패(None/Exception) 시 0.0으로 폴백하고 _prev_oi 상태 오염 방지 - README: ML 피처 수 오기재 수정 (25개 → 23개) - tests: _calc_oi_change 첫 캔들 및 API 실패 시 상태 보존 유닛 테스트 추가 Made-with: Cursor
248 lines
9.6 KiB
Python
248 lines
9.6 KiB
Python
import pytest
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from unittest.mock import AsyncMock, MagicMock, patch
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import pandas as pd
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import numpy as np
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import os
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from src.bot import TradingBot
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from src.config import Config
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@pytest.fixture
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def config():
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os.environ.update({
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"BINANCE_API_KEY": "k",
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"BINANCE_API_SECRET": "s",
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"SYMBOL": "XRPUSDT",
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"LEVERAGE": "10",
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"RISK_PER_TRADE": "0.02",
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"NOTION_TOKEN": "secret_test",
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"NOTION_DATABASE_ID": "db_test",
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})
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return Config()
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@pytest.fixture
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def sample_df():
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np.random.seed(0)
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n = 100
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close = np.cumsum(np.random.randn(n) * 0.01) + 0.5
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return pd.DataFrame({
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"open": close,
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"high": close * 1.005,
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"low": close * 0.995,
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"close": close,
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"volume": np.random.randint(100000, 1000000, n).astype(float),
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})
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def test_bot_uses_multi_symbol_stream(config):
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from src.data_stream import MultiSymbolStream
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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assert isinstance(bot.stream, MultiSymbolStream)
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def test_bot_stream_has_btc_eth_buffers(config):
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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assert "btcusdt" in bot.stream.buffers
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assert "ethusdt" in bot.stream.buffers
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@pytest.mark.asyncio
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async def test_bot_processes_signal(config, sample_df):
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with patch("src.bot.BinanceFuturesClient") as MockExchange:
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MockExchange.return_value = AsyncMock()
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bot = TradingBot(config)
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bot.exchange = AsyncMock()
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bot.exchange.get_balance = AsyncMock(return_value=1000.0)
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bot.exchange.get_position = AsyncMock(return_value=None)
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bot.exchange.place_order = AsyncMock(return_value={"orderId": "123"})
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bot.exchange.set_leverage = AsyncMock(return_value={})
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bot.exchange.calculate_quantity = MagicMock(return_value=100.0)
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bot.exchange.MIN_NOTIONAL = 5.0
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with patch("src.bot.Indicators") as MockInd:
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mock_ind = MagicMock()
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mock_ind.calculate_all.return_value = sample_df
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mock_ind.get_signal.return_value = "LONG"
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mock_ind.get_atr_stop.return_value = (0.48, 0.56)
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MockInd.return_value = mock_ind
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await bot.process_candle(sample_df)
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@pytest.mark.asyncio
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async def test_close_and_reenter_calls_open_when_ml_passes(config, sample_df):
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"""반대 시그널 + ML 필터 통과 시 청산 후 재진입해야 한다."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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bot._close_position = AsyncMock()
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bot._open_position = AsyncMock()
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bot.risk = MagicMock()
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bot.risk.can_open_new_position.return_value = True
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bot.ml_filter = MagicMock()
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bot.ml_filter.is_model_loaded.return_value = True
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bot.ml_filter.should_enter.return_value = True
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position = {"positionAmt": "100", "entryPrice": "0.5", "markPrice": "0.52"}
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await bot._close_and_reenter(position, "SHORT", sample_df)
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bot._close_position.assert_awaited_once_with(position)
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bot._open_position.assert_awaited_once_with("SHORT", sample_df)
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@pytest.mark.asyncio
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async def test_close_and_reenter_skips_open_when_ml_blocks(config, sample_df):
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"""ML 필터 차단 시 청산만 하고 재진입하지 않아야 한다."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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bot._close_position = AsyncMock()
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bot._open_position = AsyncMock()
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bot.ml_filter = MagicMock()
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bot.ml_filter.is_model_loaded.return_value = True
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bot.ml_filter.should_enter.return_value = False
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position = {"positionAmt": "100", "entryPrice": "0.5", "markPrice": "0.52"}
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await bot._close_and_reenter(position, "SHORT", sample_df)
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bot._close_position.assert_awaited_once_with(position)
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bot._open_position.assert_not_called()
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@pytest.mark.asyncio
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async def test_close_and_reenter_skips_open_when_max_positions_reached(config, sample_df):
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"""최대 포지션 수 도달 시 청산만 하고 재진입하지 않아야 한다."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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bot._close_position = AsyncMock()
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bot._open_position = AsyncMock()
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bot.risk = MagicMock()
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bot.risk.can_open_new_position.return_value = False
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position = {"positionAmt": "100", "entryPrice": "0.5", "markPrice": "0.52"}
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await bot._close_and_reenter(position, "SHORT", sample_df)
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bot._close_position.assert_awaited_once_with(position)
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bot._open_position.assert_not_called()
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@pytest.mark.asyncio
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async def test_process_candle_calls_close_and_reenter_on_reverse_signal(config, sample_df):
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"""반대 시그널 시 process_candle이 _close_and_reenter를 호출해야 한다."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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bot.exchange = AsyncMock()
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bot.exchange.get_position = AsyncMock(return_value={
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"positionAmt": "100",
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"entryPrice": "0.5",
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"markPrice": "0.52",
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})
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bot._close_and_reenter = AsyncMock()
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bot.ml_filter = MagicMock()
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bot.ml_filter.is_model_loaded.return_value = False
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bot.ml_filter.should_enter.return_value = True
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with patch("src.bot.Indicators") as MockInd:
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mock_ind = MagicMock()
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mock_ind.calculate_all.return_value = sample_df
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mock_ind.get_signal.return_value = "SHORT" # 현재 LONG 포지션에 반대 시그널
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MockInd.return_value = mock_ind
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await bot.process_candle(sample_df)
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bot._close_and_reenter.assert_awaited_once()
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call_args = bot._close_and_reenter.call_args
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assert call_args.args[1] == "SHORT"
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@pytest.mark.asyncio
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async def test_process_candle_passes_raw_signal_to_close_and_reenter_even_if_ml_loaded(config, sample_df):
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"""포지션 보유 시 ML 필터가 로드되어 있어도 process_candle은 raw signal을 _close_and_reenter에 전달한다."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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bot.exchange = AsyncMock()
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bot.exchange.get_position = AsyncMock(return_value={
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"positionAmt": "100",
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"entryPrice": "0.5",
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"markPrice": "0.52",
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})
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bot._close_and_reenter = AsyncMock()
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bot.ml_filter = MagicMock()
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bot.ml_filter.is_model_loaded.return_value = True # 모델 로드됨
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bot.ml_filter.should_enter.return_value = False # ML이 차단하더라도
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with patch("src.bot.Indicators") as MockInd:
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mock_ind = MagicMock()
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mock_ind.calculate_all.return_value = sample_df
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mock_ind.get_signal.return_value = "SHORT"
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MockInd.return_value = mock_ind
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await bot.process_candle(sample_df)
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# ML 필터가 차단해도 _close_and_reenter는 호출되어야 한다 (ML 재평가는 내부에서)
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bot._close_and_reenter.assert_awaited_once()
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call_args = bot._close_and_reenter.call_args
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assert call_args.args[1] == "SHORT"
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# process_candle에서 ml_filter.should_enter가 호출되지 않아야 한다
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bot.ml_filter.should_enter.assert_not_called()
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@pytest.mark.asyncio
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async def test_process_candle_fetches_oi_and_funding(config, sample_df):
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"""process_candle()이 OI와 펀딩비를 조회하고 build_features에 전달하는지 확인."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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bot.exchange = AsyncMock()
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bot.exchange.get_balance = AsyncMock(return_value=1000.0)
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bot.exchange.get_position = AsyncMock(return_value=None)
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bot.exchange.place_order = AsyncMock(return_value={"orderId": "1"})
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bot.exchange.set_leverage = AsyncMock()
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bot.exchange.get_open_interest = AsyncMock(return_value=5000000.0)
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bot.exchange.get_funding_rate = AsyncMock(return_value=0.0001)
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# 신호를 LONG으로 강제해 build_features가 반드시 호출되도록 함
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with patch("src.bot.Indicators") as mock_ind_cls:
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mock_ind = MagicMock()
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mock_ind.calculate_all.return_value = sample_df
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mock_ind.get_signal.return_value = "LONG"
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mock_ind_cls.return_value = mock_ind
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with patch("src.bot.build_features") as mock_build:
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from src.ml_features import FEATURE_COLS
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mock_build.return_value = pd.Series({col: 0.0 for col in FEATURE_COLS})
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bot.ml_filter.is_model_loaded = MagicMock(return_value=False)
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# _open_position은 이 테스트의 관심사가 아니므로 mock 처리
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bot._open_position = AsyncMock()
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await bot.process_candle(sample_df)
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assert mock_build.called
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call_kwargs = mock_build.call_args.kwargs
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assert "oi_change" in call_kwargs
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assert "funding_rate" in call_kwargs
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def test_calc_oi_change_first_candle_returns_zero(config):
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"""첫 캔들은 0.0을 반환하고 _prev_oi를 설정한다."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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assert bot._calc_oi_change(5000000.0) == 0.0
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assert bot._prev_oi == 5000000.0
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def test_calc_oi_change_api_failure_does_not_corrupt_state(config):
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"""API 실패 시 _fetch_market_microstructure가 _calc_oi_change를 호출하지 않아 상태가 오염되지 않는다."""
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with patch("src.bot.BinanceFuturesClient"):
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bot = TradingBot(config)
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bot._prev_oi = 5000000.0
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# API 실패 시 _fetch_market_microstructure는 oi_val > 0 체크로 _calc_oi_change를 건너뜀
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# _calc_oi_change(0.0)을 직접 호출하면 _prev_oi가 0.0으로 오염되는 이전 버그를 재현
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# 수정 후에는 _fetch_market_microstructure에서 0.0을 직접 반환하므로 이 경로가 없음
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# 대신 _calc_oi_change가 정상 값에서만 호출되는지 확인
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result = bot._calc_oi_change(5100000.0)
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assert abs(result - 0.02) < 1e-6 # (5100000 - 5000000) / 5000000 = 0.02
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assert bot._prev_oi == 5100000.0
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