shuim
a264561576
- 스윙 체결가 확인 전 executed_price NULL + fill_sweep, 진입가 resolve(ActiveTrade↔Portfolio), 0체결/부분체결 매수 장부 원복 - DT 고아 감지(근거 한정)·0체결 매도 복원·stale 점검 확대, 시간손절 -0.3% 원복 - 폴백 손절 ATR 캐시, 거래량부족-차단 신호 매수 차단, 현금 5% 유보 재적용, MDD peak/reset 수정 - KIS 서킷브레이커 청산 우회·경보, db_worker 재큐잉 순서, heartbeat·health-watch 사이드카 - 실시간 WS 재구독·41건 우선순위·다건 프레임 분할, 차트 샘플 제거·당일봉 합성, WS 서브프로토콜 인증 - 프론트: 미관리 그룹·확인 모달·차트 실시간 반영·예수금 표시 정정 - 전문가 에이전트 6종 추가(.claude/agents) - 유닛 스위트 2667 passed (소켓 차단 하), tsc OK Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Y83Za98XsNw9zuA4FTUytN
480 lines
21 KiB
Python
480 lines
21 KiB
Python
"""2026-10-08 체결가/평단/환율/총자산 정합 회귀.
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1) 체결 확인 전 executed_price 에 주문가를 넣지 않고, 확인 시 체결가×체결수량·순손익으로 갱신
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2) 스윙 손익·손절 진입가 = 스윙 ActiveTrade.entry_price (없으면 Portfolio 평단 폴백, 괴리 시 보수적 max)
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3) 환율 0 → 마지막 성공값/설정값 폴백, 모두 없으면 환산 생략 플래그
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4) 총자산 = 주식평가 + D+2 예수금 분해 필드
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"""
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import asyncio
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from decimal import Decimal
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from types import SimpleNamespace
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from unittest.mock import AsyncMock
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import pytest
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from app.core.config import settings
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import app.services.db_worker as dbw
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import app.services.trade_executor as te
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from app.services.swing import fill_sweep as fs
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from app.services.swing.position_manager import (
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resolve_swing_entry_price_v2,
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SWING_ENTRY_PRICE_MAX_DEVIATION,
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)
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from app.api.endpoints import portfolio as pf
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def _run(coro):
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return asyncio.run(coro)
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# ── 1. 체결 기준 TradeHistory 필드 ────────────────────────────────────────────
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def test_fill_fields_buy_amount_is_fill_price_times_qty():
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f = te._fill_update_fields_v2("BUY", 9, 41200.0, -0.74, None)
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assert f["executed_price"] == Decimal("41200.0")
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assert f["executed_quantity"] == 9
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assert f["total_amount"] == Decimal(str(round(41200.0 * 9, 2)))
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assert "net_profit_loss" not in f
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def test_fill_fields_no_price_never_substitutes_order_price():
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f = te._fill_update_fields_v2("BUY", 9, 0.0, 0.0, None)
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assert "executed_price" not in f
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assert "total_amount" not in f
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assert f["executed_quantity"] == 9
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def test_fill_fields_sell_recomputes_net_from_fill():
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basis = {"entry_price": 10000.0, "market": "KOSPI", "is_domestic": True, "net_rate": False}
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f = te._fill_update_fields_v2("SELL", 10, 11000.0, 0.0, basis)
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from app.services.trade_helpers import calculate_trade_costs
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c = calculate_trade_costs(entry_price=10000.0, exit_price=11000.0, quantity=10,
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is_domestic=True, market="KOSPI")
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assert float(f["net_profit_loss"]) == pytest.approx(10000.0 - float(c["total_cost"]), abs=0.01)
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assert float(f["profit_loss_rate"]) == pytest.approx(10.0, abs=1e-6) # gross 규약
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assert float(f["commission"]) == pytest.approx(float(c["total_cost"]))
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def test_fill_fields_sell_net_rate():
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basis = {"entry_price": 10000.0, "net_rate": True}
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f = te._fill_update_fields_v2("SELL", 10, 11000.0, 0.0, basis)
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assert float(f["profit_loss_rate"]) == pytest.approx(
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float(f["net_profit_loss"]) / 100000.0 * 100, abs=1e-3)
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@pytest.fixture
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def verify_env(monkeypatch):
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calls = {"th": [], "at": []}
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async def _th(order_id, fields):
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calls["th"].append((order_id, dict(fields)))
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async def _at(data):
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calls["at"].append(dict(data))
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monkeypatch.setattr(dbw, "enqueue_update_trade_history_by_order_id", _th)
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monkeypatch.setattr(dbw, "enqueue_active_trade_upsert", _at)
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monkeypatch.setattr(te, "_delayed_sync_portfolio", AsyncMock())
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monkeypatch.setattr(te.asyncio, "sleep", AsyncMock())
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te._entry_fill_adjusted_orders.clear()
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return calls
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def _patch_exec(monkeypatch, result):
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"""체결조회 목 — 테스트 시점에 두 참조(trade_executor 캡처본, 소스 모듈 속성)를 모두 덮는다.
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(다른 테스트 파일이 sys.modules 의 KIS 모듈을 MagicMock 으로 바꿔도 순서 무관하게 동작)
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"""
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import sys
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m = AsyncMock(return_value=result)
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stub = SimpleNamespace(get_order_execution=m)
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monkeypatch.setattr(te, "korea_investment_api", stub)
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mod = sys.modules.get("app.services.korea_investment_api")
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if mod is not None:
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monkeypatch.setattr(mod, "korea_investment_api", stub, raising=False)
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return m
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def test_verify_v3_buy_updates_amount_and_entry(monkeypatch, verify_env):
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_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 9,
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"filled_price": 41200.0, "remaining_qty": 0})
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_run(te._verify_and_sync_execution_v3(
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"0000123", "082740", "한화엔진", 9, 41506.0, "BUY", True, "KRX", 0,
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fill_entry_strategy_name="swing", sell_pnl_basis={"strategy_type": "swing"},
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))
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(oid, fields), = verify_env["th"]
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assert fields["executed_price"] == Decimal("41200.0")
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assert fields["total_amount"] == Decimal(str(41200.0 * 9))
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assert fields["order_type"] == "BUY" and fields["strategy_type"] == "swing"
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(at,) = verify_env["at"]
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assert at["strategy_name"] == "swing"
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assert at["entry_fill_adjust"] == {"order_price": 41506.0, "filled_price": 41200.0, "filled_qty": 9}
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assert te.entry_fill_already_adjusted_v2("123")
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def test_verify_v3_missing_fill_price_no_price_written(monkeypatch, verify_env):
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_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 9,
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"filled_price": 0, "remaining_qty": 0})
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_run(te._verify_and_sync_execution_v3(
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"0000124", "005380", "현대차", 9, 337177.0, "BUY", True, "KRX", 0,
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fill_entry_strategy_name="swing",
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))
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(oid, fields), = verify_env["th"]
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assert "executed_price" not in fields and "total_amount" not in fields
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assert verify_env["at"] == [] # 체결가 모르면 진입가 보정 없음
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def test_verify_v3_sell_net_from_fill(monkeypatch, verify_env):
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_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 5,
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"filled_price": 9500.0, "remaining_qty": 0})
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_run(te._verify_and_sync_execution_v3(
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"0000125", "005930", "삼성", 5, 9600.0, "SELL", True, "KRX", 0,
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sell_pnl_basis={"entry_price": 10000.0, "market": "KOSPI", "strategy_type": "swing"},
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))
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(oid, fields), = verify_env["th"]
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assert float(fields["net_profit_loss"]) < -2500.0 # gross -2500 에서 비용 차감
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assert float(fields["profit_loss_rate"]) == pytest.approx(-5.0)
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# ── 1-b. ActiveTrade 진입가 누적/체결 보정 (db_worker 순수 로직) ──────────────
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def _rec(**kw):
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base = dict(id=7, quantity=10, entry_price=10000.0, highest_since_entry=10500.0, remaining_pct=1.0)
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base.update(kw)
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return SimpleNamespace(**base)
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def test_accumulate_weighted_average_and_pinned_retry():
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r = _rec()
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data = {"accumulate_entry": True, "quantity": 10, "entry_price": 8000.0, "highest_since_entry": 8000.0}
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skip = dbw._apply_entry_price_adjustments_v2(r, data)
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assert {"quantity", "entry_price", "highest_since_entry"} <= skip
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assert r.quantity == 20 and r.entry_price == 9000.0
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assert r.highest_since_entry == 10500.0 # 고점은 낮추지 않는다
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# 같은 payload 재실행(종료 drain) — 두 번 누적하지 않는다
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r2 = _rec()
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dbw._apply_entry_price_adjustments_v2(r2, data)
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assert r2.quantity == 20 and r2.entry_price == 9000.0
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def test_accumulate_after_partial_exit_weights_held_only():
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r = _rec(remaining_pct=0.5) # 10주 중 5주 보유
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dbw._apply_entry_price_adjustments_v2(r, {"accumulate_entry": True, "quantity": 5, "entry_price": 8000.0})
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assert r.entry_price == 9000.0 # (5×10000 + 5×8000)/10
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def test_accumulate_into_empty_row_takes_new_price():
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r = _rec(quantity=0, entry_price=0)
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dbw._apply_entry_price_adjustments_v2(r, {"accumulate_entry": True, "quantity": 3, "entry_price": 5000.0})
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assert r.quantity == 3 and r.entry_price == 5000.0
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def test_fill_adjust_new_entry_becomes_fill_price():
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r = _rec(quantity=9, entry_price=41506.0)
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d = {"entry_fill_adjust": {"order_price": 41506.0, "filled_price": 41200.0, "filled_qty": 9}}
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dbw._apply_entry_price_adjustments_v2(r, d)
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assert r.entry_price == 41200.0
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# 재실행 시 고정값 재사용(두 번 빼지 않음)
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r.entry_price = 41506.0
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dbw._apply_entry_price_adjustments_v2(r, d)
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assert r.entry_price == 41200.0
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def test_fill_adjust_partial_of_accumulated_row():
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r = _rec(quantity=20, entry_price=9000.0) # 10@10000 + 10@8000(주문가)
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dbw._apply_entry_price_adjustments_v2(
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r, {"entry_fill_adjust": {"order_price": 8000.0, "filled_price": 7900.0, "filled_qty": 10}})
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assert r.entry_price == 8950.0
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def test_fill_adjust_bad_input_keeps_price():
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r = _rec()
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dbw._apply_entry_price_adjustments_v2(
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r, {"entry_fill_adjust": {"order_price": 0, "filled_price": 7900.0, "filled_qty": 10}})
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assert r.entry_price == 10000.0
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def test_upsert_handler_skips_fill_adjust_when_no_row():
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class _S:
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async def execute(self, q):
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return SimpleNamespace(scalars=lambda: SimpleNamespace(first=lambda: None))
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def add(self, x): # pragma: no cover
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raise AssertionError("must not create")
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async def commit(self): # pragma: no cover
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raise AssertionError("must not commit")
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_run(dbw._handle_upsert_active_trade(_S(), {
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"stock_code": "005930", "strategy_name": "swing",
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"entry_fill_adjust": {"order_price": 1, "filled_price": 1, "filled_qty": 1},
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}))
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# ── 2. 스윙 진입가 해석 (손절 판정 직결 — 경계값) ────────────────────────────
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def test_entry_price_prefers_active_trade_within_band():
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assert resolve_swing_entry_price_v2(68000, 67323.08) == (68000.0, "active_trade")
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def test_entry_price_boundary_exact_deviation_uses_active_trade():
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pa = 10000.0
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at = pa * (1 + SWING_ENTRY_PRICE_MAX_DEVIATION)
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price, basis = resolve_swing_entry_price_v2(at, pa)
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assert basis == "active_trade" and price == pytest.approx(at)
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def test_entry_price_over_deviation_uses_kis_portfolio_avg():
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# [2026-10-09 하드닝 R1] 괴리 > 한도면 유령 행 의심 → KIS 실제 평단(Portfolio).
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# 이전 정책(max)은 유령 고가 entry 로 허위 전량 손절을 냈다.
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pa = 10000.0
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lo = pa * (1 - SWING_ENTRY_PRICE_MAX_DEVIATION - 0.01)
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assert resolve_swing_entry_price_v2(lo, pa) == (pa, "portfolio_avg_deviation")
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hi = pa * (1 + SWING_ENTRY_PRICE_MAX_DEVIATION + 0.01)
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assert resolve_swing_entry_price_v2(hi, pa) == (pa, "portfolio_avg_deviation")
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@pytest.mark.parametrize("at,pa,exp", [
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(None, 5000, (5000.0, "portfolio_avg")),
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(0, 5000, (5000.0, "portfolio_avg")),
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("bad", 5000, (5000.0, "portfolio_avg")),
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(5000, 0, (5000.0, "active_trade")),
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(None, None, (0.0, "none")),
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])
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def test_entry_price_fallbacks(at, pa, exp):
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assert resolve_swing_entry_price_v2(at, pa) == exp
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def test_executor_entry_price_dt_tag_uses_portfolio():
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h = SimpleNamespace(average_price=Decimal("67323.08"))
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assert te._swing_entry_price_for_stock_v2(
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{"strategy_type": "daytrading", "_swing_entry_price": 68000}, h, "103140") == 67323.08
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assert te._swing_entry_price_for_stock_v2(
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{"_swing_entry_price": 68000}, h, "103140") == 68000.0
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assert te._swing_entry_price_for_stock_v2({}, h, "103140") == 67323.08
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def test_mixed_avg_stop_loss_trigger_differs():
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"""혼합 평단(67,323)으로는 -7% 미발동인데 스윙 진입가(68,000)로는 발동 — 스윙 기준이 맞다."""
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stop = -abs(float(settings.STOP_LOSS_PERCENT))
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price = 68000 * (1 + stop / 100) - 1
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swing_pl = (price / 68000 - 1) * 100
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mixed_pl = (price / 67323.08 - 1) * 100
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assert swing_pl <= stop < mixed_pl
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# ── 2-b. API 전략별 분해 필드 ────────────────────────────────────────────────
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def _h(**kw):
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base = dict(stock_code="103140", quantity=13, average_price=Decimal("67323.08"),
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current_price=Decimal("70000"))
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base.update(kw)
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return SimpleNamespace(**base)
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def test_breakdown_swing_with_dt():
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b = pf._strategy_breakdown_v2(_h(), 68000.0, {"quantity": 8, "entry_price": 66900.0})
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assert b["swing_quantity"] == 5 and b["dt_quantity"] == 8
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assert b["swing_avg_price"] == 68000.0 and b["swing_avg_price_basis"] == "active_trade"
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assert b["dt_avg_price"] == 66900.0
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assert b["swing_profit_loss"] == pytest.approx(10000.0)
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assert b["avg_price_mixed"] is True
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def test_breakdown_derived_when_no_active_trade():
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b = pf._strategy_breakdown_v2(_h(), None, {"quantity": 8, "entry_price": 66900.0})
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assert b["swing_avg_price_basis"] == "derived_from_mixed"
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assert b["swing_avg_price"] == pytest.approx(round((67323.08 * 13 - 66900 * 8) / 5, 2))
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def test_breakdown_no_dt_portfolio_fallback_rounded():
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b = pf._strategy_breakdown_v2(_h(quantity=5, average_price=Decimal("67323.0769")), None, None)
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assert b["swing_avg_price"] == 67323.08 and b["swing_avg_price_basis"] == "portfolio_avg"
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assert b["dt_quantity"] == 0 and b["avg_price_mixed"] is False
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def test_breakdown_dt_only():
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b = pf._strategy_breakdown_v2(_h(quantity=8), None, {"quantity": 8, "entry_price": 66900.0})
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assert b["swing_quantity"] == 0 and b["swing_avg_price"] is None
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def test_quantize_price_policy():
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assert pf._quantize_price_v2("67323.0769") == Decimal("67323.08")
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assert pf._quantize_price_v2("1.005") == Decimal("1.01")
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assert pf._quantize_price_v2(None) == Decimal("0.00")
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def test_response_model_has_swing_avg_price():
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assert "swing_avg_price" in pf.PortfolioResponse.model_fields
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# ── 3. 환율 ──────────────────────────────────────────────────────────────────
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@pytest.fixture
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def fx_reset(monkeypatch):
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monkeypatch.setattr(pf, "_last_good_fx_rate", 0.0)
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yield
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def test_fx_from_kis_and_last_good(fx_reset, monkeypatch):
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assert pf._resolve_fx_rate_v2({"output2": [{"bass_exrt": "1395.5"}]}) == (1395.5, "kis")
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assert pf._resolve_fx_rate_v2({"output2": []}) == (1395.5, "last_good")
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def test_fx_out_of_range_ignored_then_config(fx_reset):
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rate, src = pf._resolve_fx_rate_v2({"output2": {"bass_exrt": "3.2"}})
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assert src == "config_default" and rate == float(settings.US_DEFAULT_FX_RATE)
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def test_fx_unavailable_when_all_zero(fx_reset, monkeypatch):
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monkeypatch.setattr(settings, "US_DEFAULT_FX_RATE", 0.0)
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assert pf._resolve_fx_rate_v2(None) == (0.0, "unavailable")
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def test_fx_derived_ratio_no_double_count(fx_reset):
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data = {"output2": {"tot_evlu_amt": "1400000", "frcr_evlu_tota": "1000", "usd_amt": "1000"}}
|
||
assert pf._resolve_fx_rate_v2(data) == (1400.0, "kis")
|
||
|
||
|
||
def test_cache_summary_v2_fx_and_cash_fields(fx_reset, monkeypatch):
|
||
cache = pf.PortfolioCache()
|
||
cache.holdings = [
|
||
SimpleNamespace(stock_code="005930", market="KRX", quantity=10, average_price=Decimal("70000"),
|
||
current_price=Decimal("71000"), strategy_type="swing", profit_loss_rate=None),
|
||
SimpleNamespace(stock_code="AAPL", market="NASD", quantity=2, average_price=Decimal("150"),
|
||
current_price=Decimal("200"), strategy_type="swing", profit_loss_rate=None),
|
||
]
|
||
bal = {"output2": [{"tot_evlu_amt": "1000000", "scts_evlu_amt": "710000",
|
||
"prvs_rcdl_excc_amt": "290000", "_ord_psbl_cash": "264854",
|
||
"dnca_tot_amt": "290000"}]}
|
||
_run(cache.cache_summary_v2(bal, {"output2": []}))
|
||
s = cache.summary
|
||
# [R1 2026-10-09] 설정 기본값 환율은 추정치 — 총자산·원화 환산에 합산하지 않고 별도 노출
|
||
assert s["exchange_rate"] == 0.0
|
||
assert s["exchange_rate_estimate"] == float(settings.US_DEFAULT_FX_RATE)
|
||
assert s["exchange_rate_source"] == "config_default" and s["exchange_rate_unavailable"] is True
|
||
assert s["overseas_value_usd"] == 400.0
|
||
assert s["overseas_value_krw"] == 0.0
|
||
assert s["available_cash"] == 264854.0 # 주문가능현금(매매 사이징 입력) — 의미 불변
|
||
assert s["settlement_cash"] == 290000.0
|
||
assert s["cash_basis_gap"] == pytest.approx(25146.0)
|
||
assert s["cash_for_total_assets"] == 290000.0
|
||
assert s["total_assets_residual"] == 0.0
|
||
|
||
|
||
def test_cache_summary_v2_fx_unavailable_flag(fx_reset, monkeypatch):
|
||
monkeypatch.setattr(settings, "US_DEFAULT_FX_RATE", 0.0)
|
||
cache = pf.PortfolioCache()
|
||
cache.holdings = [SimpleNamespace(stock_code="AAPL", market="NASD", quantity=2,
|
||
average_price=Decimal("150"), current_price=Decimal("200"),
|
||
strategy_type="swing", profit_loss_rate=None)]
|
||
_run(cache.cache_summary_v2(None, None))
|
||
s = cache.summary
|
||
assert s["exchange_rate"] == 0.0 and s["exchange_rate_unavailable"] is True
|
||
assert s["fx_conversion_skipped"] is True and s["overseas_value_krw"] == 0.0
|
||
|
||
|
||
# ── 1-c. 후속 체결 보정(fill_sweep) ──────────────────────────────────────────
|
||
def test_derive_sell_entry_price():
|
||
row = SimpleNamespace(order_quantity=10, total_amount=Decimal("110000"),
|
||
net_profit_loss=Decimal("9790"), commission=Decimal("210"))
|
||
assert fs.derive_sell_entry_price_v2(row) == pytest.approx(10000.0)
|
||
row2 = SimpleNamespace(order_quantity=10, total_amount=110000, net_profit_loss=None, commission=None)
|
||
assert fs.derive_sell_entry_price_v2(row2) is None
|
||
|
||
|
||
class _FakeDB:
|
||
"""1번째 execute = TradeHistory 후보, 이후 = ActiveTrade 조회(진입가 보정 대상 확정)."""
|
||
def __init__(self, rows, active_rows=None):
|
||
self.rows = rows
|
||
self.active_rows = list(active_rows or [])
|
||
self.calls = 0
|
||
|
||
async def execute(self, q):
|
||
self.calls += 1
|
||
rows = self.rows if self.calls == 1 else self.active_rows
|
||
return SimpleNamespace(scalars=lambda: SimpleNamespace(all=lambda: rows))
|
||
|
||
|
||
def _th_row(**kw):
|
||
base = dict(id=448, stock_code="082740", order_type="BUY", order_id="0000777",
|
||
order_quantity=9, order_price=Decimal("41506"), total_amount=Decimal("373554"),
|
||
net_profit_loss=None, commission=None, strategy_type="swing",
|
||
entry_reason="RSI 과매도 반등")
|
||
base.update(kw)
|
||
return SimpleNamespace(**base)
|
||
|
||
|
||
@pytest.fixture
|
||
def sweep_env(monkeypatch):
|
||
calls = {"th": [], "at": []}
|
||
|
||
async def _th(tid, fields):
|
||
calls["th"].append((tid, dict(fields)))
|
||
|
||
async def _at(data):
|
||
calls["at"].append(dict(data))
|
||
|
||
monkeypatch.setattr(dbw, "enqueue_update_trade_history", _th)
|
||
monkeypatch.setattr(dbw, "enqueue_active_trade_upsert", _at)
|
||
fs._attempts.clear()
|
||
fs._queued_ids.clear()
|
||
te._entry_fill_adjusted_orders.clear()
|
||
return calls
|
||
|
||
|
||
def test_sweep_buy_updates_price_amount_and_entry(monkeypatch, sweep_env):
|
||
_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 9,
|
||
"filled_price": 41200.0, "remaining_qty": 0})
|
||
active = [SimpleNamespace(id=225, strategy_name="swing", entry_reason="RSI 과매도 반등")]
|
||
n = _run(fs.sweep_unconfirmed_fills_v2(_FakeDB([_th_row()], active)))
|
||
assert n == 1
|
||
(tid, f), = sweep_env["th"]
|
||
assert tid == 448 and f["executed_price"] == Decimal("41200.0")
|
||
assert f["total_amount"] == Decimal(str(41200.0 * 9))
|
||
assert "executed_at" not in f
|
||
(at,) = sweep_env["at"]
|
||
# [하드닝 R1 2026-10-09] '최신 비-DT 행'이 아니라 이 매수의 전략명으로 정확히 지정
|
||
assert at["strategy_name"] == "swing" and "strategy_name_not" not in at
|
||
assert at["entry_fill_adjust"]["filled_price"] == 41200.0
|
||
|
||
|
||
def test_sweep_buy_skips_entry_adjust_if_already_done(monkeypatch, sweep_env):
|
||
te.note_entry_fill_adjusted_v2("777")
|
||
_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 9,
|
||
"filled_price": 41200.0, "remaining_qty": 0})
|
||
_run(fs.sweep_unconfirmed_fills_v2(_FakeDB([_th_row()])))
|
||
assert len(sweep_env["th"]) == 1 and sweep_env["at"] == []
|
||
|
||
|
||
def test_sweep_no_fill_price_no_update_and_attempts_capped(monkeypatch, sweep_env):
|
||
_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 9,
|
||
"filled_price": 0, "remaining_qty": 0})
|
||
monkeypatch.setattr(fs, "FILL_SWEEP_RETRY_INTERVAL_SEC", 0)
|
||
for _ in range(fs.FILL_SWEEP_MAX_ATTEMPTS + 2):
|
||
_run(fs.sweep_unconfirmed_fills_v2(_FakeDB([_th_row()])))
|
||
assert sweep_env["th"] == []
|
||
assert fs._attempts[448][0] == fs.FILL_SWEEP_MAX_ATTEMPTS
|
||
assert 448 in fs._exhausted_ids()
|
||
|
||
|
||
def test_sweep_sell_recomputes_net(monkeypatch, sweep_env):
|
||
row = _th_row(id=500, order_type="SELL", order_quantity=10, order_price=Decimal("11000"),
|
||
total_amount=Decimal("110000"), net_profit_loss=Decimal("10000"), commission=None)
|
||
_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 10,
|
||
"filled_price": 10900.0, "remaining_qty": 0})
|
||
_run(fs.sweep_unconfirmed_fills_v2(_FakeDB([row])))
|
||
(tid, f), = sweep_env["th"]
|
||
assert f["total_amount"] == Decimal("109000.0")
|
||
assert float(f["net_profit_loss"]) < 9000.0 # (10900-10000)×10 − 비용
|
||
assert float(f["profit_loss_rate"]) == pytest.approx(9.0)
|
||
assert sweep_env["at"] == []
|
||
|
||
|
||
def test_sweep_partial_unsettled_skipped(monkeypatch, sweep_env):
|
||
_patch_exec(monkeypatch, {"ok": True, "found": True, "filled_qty": 4,
|
||
"filled_price": 41200.0, "remaining_qty": 5})
|
||
_run(fs.sweep_unconfirmed_fills_v2(_FakeDB([_th_row()])))
|
||
assert sweep_env["th"] == []
|
||
|
||
|
||
def test_sweep_skips_overseas(monkeypatch, sweep_env):
|
||
m = _patch_exec(monkeypatch, {"ok": True})
|
||
_run(fs.sweep_unconfirmed_fills_v2(_FakeDB([_th_row(stock_code="AAPL")])))
|
||
m.assert_not_called()
|