652990082d
The combined summary (PF, MDD, win_rate) was indirectly reconstructed from per-symbol averages using round(win_rate * n), which introduced rounding errors. MDD was max() of individual symbol MDDs, ignoring simultaneous drawdowns across the correlated crypto portfolio. Now computes all combined metrics directly from the trade list: - PF: sum(wins) / sum(losses) from actual trade PnLs - MDD: portfolio equity curve from time-sorted trades - Win rate: direct count from trade PnLs Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
342 lines
13 KiB
Python
342 lines
13 KiB
Python
import pytest
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from unittest.mock import patch, MagicMock
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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def test_fetch_latest_data_calls_subprocess():
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"""fetch_latest_data가 심볼별로 fetch_history.py를 호출하는지 확인."""
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from scripts.weekly_report import fetch_latest_data
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with patch("subprocess.run") as mock_run:
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mock_run.return_value = MagicMock(returncode=0)
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fetch_latest_data(["XRPUSDT", "TRXUSDT"], days=35)
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assert mock_run.call_count == 2
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args_0 = mock_run.call_args_list[0][0][0]
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assert "--symbol" in args_0
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assert "XRPUSDT" in args_0
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assert "--days" in args_0
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assert "35" in args_0
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def test_run_backtest_returns_summary():
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"""run_backtest가 WF 백테스트를 실행하고 결과를 반환하는지 확인."""
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from scripts.weekly_report import run_backtest
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mock_result = {
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"summary": {
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"total_trades": 27, "total_pnl": 217.0, "return_pct": 21.7,
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"win_rate": 66.7, "profit_factor": 1.57, "max_drawdown_pct": 12.0,
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"sharpe_ratio": 33.3, "avg_win": 20.0, "avg_loss": -10.0,
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"total_fees": 5.0, "close_reasons": {},
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},
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"folds": [], "trades": [],
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}
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with patch("scripts.weekly_report.WalkForwardBacktester") as MockWF:
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MockWF.return_value.run.return_value = mock_result
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result = run_backtest(
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symbols=["XRPUSDT"], train_months=3, test_months=1,
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params={"atr_sl_mult": 2.0, "atr_tp_mult": 2.0,
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"signal_threshold": 3, "adx_threshold": 25,
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"volume_multiplier": 2.5},
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)
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assert result["summary"]["profit_factor"] == 1.57
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assert result["summary"]["total_trades"] == 27
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def test_fetch_live_trades_from_api():
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"""대시보드 API에서 청산 트레이드를 가져오는지 확인."""
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from scripts.weekly_report import fetch_live_trades
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mock_response = MagicMock()
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mock_response.json.return_value = {
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"trades": [
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{"symbol": "XRPUSDT", "direction": "LONG", "net_pnl": 19.568,
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"commission": 0.216, "status": "CLOSED"},
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],
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"total": 1,
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}
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mock_response.raise_for_status = MagicMock()
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with patch("scripts.weekly_report.httpx.get", return_value=mock_response):
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trades = fetch_live_trades("http://test:8000")
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assert len(trades) == 1
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assert trades[0]["symbol"] == "XRPUSDT"
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assert trades[0]["net_pnl"] == pytest.approx(19.568)
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def test_fetch_live_trades_api_failure():
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"""API 실패 시 빈 리스트 반환."""
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from scripts.weekly_report import fetch_live_trades
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with patch("scripts.weekly_report.httpx.get", side_effect=Exception("connection refused")):
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trades = fetch_live_trades("http://unreachable:8000")
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assert trades == []
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def test_fetch_live_stats_from_api():
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"""대시보드 API에서 전체 통계를 가져오는지 확인."""
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from scripts.weekly_report import fetch_live_stats
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mock_response = MagicMock()
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mock_response.json.return_value = {
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"total_trades": 15, "wins": 9, "losses": 6,
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"total_pnl": 42.5, "total_fees": 3.2,
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}
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mock_response.raise_for_status = MagicMock()
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with patch("scripts.weekly_report.httpx.get", return_value=mock_response):
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stats = fetch_live_stats("http://test:8000")
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assert stats["total_trades"] == 15
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assert stats["wins"] == 9
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import json
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from datetime import date, timedelta
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def test_load_trend_reads_previous_reports(tmp_path):
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"""이전 주간 리포트를 읽어 PF/승률/MDD 추이를 반환."""
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from scripts.weekly_report import load_trend
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for i, (pf, wr, mdd) in enumerate([
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(1.31, 48.0, 9.0), (1.24, 45.0, 11.0),
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(1.20, 44.0, 12.0), (1.18, 43.0, 14.0),
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]):
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d = date(2026, 3, 7) - timedelta(weeks=3 - i)
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report = {
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"date": d.isoformat(),
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"backtest": {"summary": {
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"profit_factor": pf, "win_rate": wr, "max_drawdown_pct": mdd,
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"total_trades": 20,
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}},
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}
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(tmp_path / f"report_{d.isoformat()}.json").write_text(json.dumps(report))
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trend = load_trend(str(tmp_path), weeks=4)
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assert len(trend["pf"]) == 4
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assert trend["pf"] == [1.31, 1.24, 1.20, 1.18]
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assert trend["pf_declining_3w"] is True
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def test_load_trend_empty_dir(tmp_path):
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"""리포트가 없으면 빈 추이 반환."""
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from scripts.weekly_report import load_trend
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trend = load_trend(str(tmp_path), weeks=4)
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assert trend["pf"] == []
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assert trend["pf_declining_3w"] is False
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def test_check_ml_trigger_all_met():
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"""3개 조건 모두 충족 시 recommend=True."""
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from scripts.weekly_report import check_ml_trigger
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result = check_ml_trigger(
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cumulative_trades=200, current_pf=0.85, pf_declining_3w=True,
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)
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assert result["recommend"] is True
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assert result["met_count"] == 3
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def test_check_ml_trigger_none_met():
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"""조건 미충족 시 recommend=False."""
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from scripts.weekly_report import check_ml_trigger
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result = check_ml_trigger(
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cumulative_trades=50, current_pf=1.5, pf_declining_3w=False,
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)
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assert result["recommend"] is False
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assert result["met_count"] == 0
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def test_run_degradation_sweep_returns_top_n():
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"""스윕을 실행하고 PF 상위 N개 대안을 반환."""
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from scripts.weekly_report import run_degradation_sweep
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from unittest.mock import patch
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fake_summaries = [
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{"profit_factor": 1.15, "total_trades": 30, "total_pnl": 50, "return_pct": 5,
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"win_rate": 55, "avg_win": 10, "avg_loss": -8, "max_drawdown_pct": 10,
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"sharpe_ratio": 2.0, "total_fees": 1, "close_reasons": {}},
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{"profit_factor": 1.08, "total_trades": 25, "total_pnl": 30, "return_pct": 3,
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"win_rate": 50, "avg_win": 8, "avg_loss": -7, "max_drawdown_pct": 12,
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"sharpe_ratio": 1.5, "total_fees": 1, "close_reasons": {}},
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{"profit_factor": 0.95, "total_trades": 20, "total_pnl": -10, "return_pct": -1,
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"win_rate": 40, "avg_win": 6, "avg_loss": -9, "max_drawdown_pct": 15,
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"sharpe_ratio": 0.5, "total_fees": 1, "close_reasons": {}},
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]
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fake_combos = [
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{"atr_sl_mult": 1.5}, {"atr_sl_mult": 1.0}, {"atr_sl_mult": 2.0},
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]
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with patch("scripts.weekly_report.run_single_backtest") as mock_bt:
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mock_bt.side_effect = fake_summaries
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with patch("scripts.weekly_report.generate_combinations", return_value=fake_combos):
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alternatives = run_degradation_sweep(
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symbols=["XRPUSDT"], train_months=3, test_months=1, top_n=3,
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)
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assert len(alternatives) <= 3
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assert alternatives[0]["summary"]["profit_factor"] >= alternatives[1]["summary"]["profit_factor"]
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def test_format_report_normal():
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"""정상 상태(PF >= 1.0) 리포트 포맷."""
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from scripts.weekly_report import format_report
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report_data = {
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"date": "2026-03-07",
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"backtest": {
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"summary": {
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"profit_factor": 1.24, "win_rate": 45.0,
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"max_drawdown_pct": 12.0, "total_trades": 88,
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},
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"per_symbol": {
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"XRPUSDT": {"profit_factor": 1.57, "total_trades": 27, "win_rate": 66.7},
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"TRXUSDT": {"profit_factor": 1.29, "total_trades": 25, "win_rate": 52.0},
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"DOGEUSDT": {"profit_factor": 1.09, "total_trades": 36, "win_rate": 44.4},
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},
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},
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"live_trades": {"count": 8, "net_pnl": 12.34, "win_rate": 62.5},
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"trend": {"pf": [1.31, 1.24], "win_rate": [48.0, 45.0], "mdd": [9.0, 12.0], "pf_declining_3w": False},
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"ml_trigger": {"recommend": False, "met_count": 0, "conditions": {
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"cumulative_trades_enough": False, "pf_below_1": False, "pf_declining_3w": False,
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}, "cumulative_trades": 47, "threshold": 150},
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"sweep": None,
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}
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text = format_report(report_data)
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assert "\uc8fc\uac04 \uc804\ub7b5 \ub9ac\ud3ec\ud2b8" in text
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assert "1.24" in text
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assert "XRPUSDT" in text or "XRP" in text
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def test_format_report_degraded():
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"""PF < 1.0일 때 스윕 결과 + ML 권장이 포함되는지 확인."""
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from scripts.weekly_report import format_report
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report_data = {
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"date": "2026-06-07",
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"backtest": {
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"summary": {"profit_factor": 0.87, "win_rate": 38.0, "max_drawdown_pct": 22.0, "total_trades": 90},
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"per_symbol": {},
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},
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"live_trades": {"count": 0, "net_pnl": 0, "win_rate": 0},
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"trend": {"pf": [1.1, 1.0, 0.87], "win_rate": [], "mdd": [], "pf_declining_3w": True},
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"ml_trigger": {"recommend": True, "met_count": 3, "conditions": {
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"cumulative_trades_enough": True, "pf_below_1": True, "pf_declining_3w": True,
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}, "cumulative_trades": 182, "threshold": 150},
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"sweep": [
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{"params": {"atr_sl_mult": 2.0, "atr_tp_mult": 2.5, "adx_threshold": 30, "volume_multiplier": 2.5, "signal_threshold": 3},
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"summary": {"profit_factor": 1.15, "total_trades": 30}},
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],
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}
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text = format_report(report_data)
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assert "0.87" in text
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assert "ML" in text
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assert "1.15" in text
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def test_send_report_uses_notifier():
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"""Discord 웹훅으로 리포트를 전송."""
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from scripts.weekly_report import send_report
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from unittest.mock import patch
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with patch("scripts.weekly_report.DiscordNotifier") as MockNotifier:
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instance = MockNotifier.return_value
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send_report("test report content", webhook_url="https://example.com/webhook")
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instance._send.assert_called_once_with("test report content")
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def test_generate_report_orchestration(tmp_path):
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"""generate_report가 모든 단계를 조합하여 리포트 dict를 반환."""
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from scripts.weekly_report import generate_report
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from unittest.mock import patch
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# 합산 지표는 개별 트레이드에서 직접 계산되므로 mock에 트레이드 포함
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mock_trades = [
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{"net_pnl": 20.0, "entry_fee": 1.0, "exit_fee": 1.0, "exit_time": "2025-06-10 12:00:00"},
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{"net_pnl": 15.0, "entry_fee": 1.0, "exit_fee": 1.0, "exit_time": "2025-06-11 12:00:00"},
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{"net_pnl": -10.0, "entry_fee": 1.0, "exit_fee": 1.0, "exit_time": "2025-06-12 12:00:00"},
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]
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mock_bt_result = {
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"summary": {
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"profit_factor": 1.24, "win_rate": 45.0,
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"max_drawdown_pct": 12.0, "total_trades": 3,
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"total_pnl": 25.0, "return_pct": 2.5,
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"avg_win": 17.5, "avg_loss": -10.0,
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"sharpe_ratio": 33.0, "total_fees": 6.0,
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"close_reasons": {},
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},
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"folds": [], "trades": mock_trades,
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}
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with patch("scripts.weekly_report.run_backtest", return_value=mock_bt_result):
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with patch("scripts.weekly_report.fetch_live_stats", return_value={"total_trades": 0, "wins": 0, "total_pnl": 0}):
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with patch("scripts.weekly_report.fetch_live_trades", return_value=[]):
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with patch("scripts.weekly_report.load_trend", return_value={
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"pf": [1.31], "win_rate": [48.0], "mdd": [9.0], "pf_declining_3w": False,
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}):
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report = generate_report(
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symbols=["XRPUSDT"],
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report_dir=str(tmp_path),
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report_date=date(2026, 3, 7),
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)
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assert report["date"] == "2026-03-07"
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# PF는 개별 트레이드에서 직접 계산: GP=35, GL=10 → 3.5
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assert report["backtest"]["summary"]["profit_factor"] == 3.5
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assert report["backtest"]["summary"]["total_trades"] == 3
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assert report["sweep"] is None # PF >= 1.0이면 스윕 안 함
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def test_save_report_creates_json(tmp_path):
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"""리포트를 JSON으로 저장."""
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from scripts.weekly_report import save_report
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report = {"date": "2026-03-07", "test": True}
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save_report(report, str(tmp_path))
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saved = list(tmp_path.glob("report_*.json"))
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assert len(saved) == 1
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loaded = json.loads(saved[0].read_text())
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assert loaded["date"] == "2026-03-07"
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def test_generate_quantstats_report_creates_html(tmp_path):
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"""트레이드 데이터로 quantstats HTML 리포트를 생성."""
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from scripts.weekly_report import generate_quantstats_report
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trades = [
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{"exit_time": "2026-03-01 12:00:00", "net_pnl": 5.0},
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{"exit_time": "2026-03-02 15:00:00", "net_pnl": -2.0},
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{"exit_time": "2026-03-03 09:00:00", "net_pnl": 8.0},
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{"exit_time": "2026-03-04 18:00:00", "net_pnl": -1.5},
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{"exit_time": "2026-03-05 10:00:00", "net_pnl": 3.0},
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]
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output = str(tmp_path / "test_report.html")
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result = generate_quantstats_report(trades, output)
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assert result is not None
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assert Path(result).exists()
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content = Path(result).read_text()
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assert "CoinTrader" in content
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def test_generate_quantstats_report_empty_trades(tmp_path):
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"""트레이드가 없으면 None 반환."""
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from scripts.weekly_report import generate_quantstats_report
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output = str(tmp_path / "empty.html")
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result = generate_quantstats_report([], output)
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assert result is None
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