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feature/is
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feature/is
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| 425218c3be | |||
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b4b09a6d4c | ||
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66c35da7f1 |
@@ -322,36 +322,3 @@ Order result: 모의투자 매수주문이 완료 되었습니다. ✓
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- `TestHandleDomesticPendingOrders` (4), `TestDomesticLimitOrderPrice` (2)
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**이슈/PR:** #232, PR #233
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---
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## 2026-02-24
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### 해외잔고 ghost position 수정 — '모의투자 잔고내역이 없습니다' 반복 방지 (#235)
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**배경:**
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- 모의투자 실행 시 MLECW, KNRX, NBY, SNSE 등 만료/정지된 종목에 대해
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`모의투자 잔고내역이 없습니다` 오류가 매 사이클 반복됨
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**근본 원인:**
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1. `ovrs_cblc_qty` (해외잔고수량, 총 보유) vs `ord_psbl_qty` (주문가능수량, 실제 매도 가능)
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- 기존 코드: `ovrs_cblc_qty` 우선 사용 → 만료 Warrant가 `ovrs_cblc_qty=289456`이지만 실제 `ord_psbl_qty=0`
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- startup sync / build_overseas_symbol_universe가 이 종목들을 포지션으로 기록
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2. SELL 실패 시 DB 포지션이 닫히지 않아 다음 사이클에서도 재시도 (무한 반복)
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**구현 내용:**
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1. `src/main.py` — `_extract_held_codes_from_balance`, `_extract_held_qty_from_balance`
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- 해외 잔고 필드 우선순위 변경: `ord_psbl_qty` → `ovrs_cblc_qty` → `hldg_qty` (fallback 유지)
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- KIS 공식 문서(VTTS3012R) 기준: `ord_psbl_qty`가 실제 매도 가능 수량
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2. `src/main.py` — `trading_cycle` ghost-close 처리
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- 해외 SELL이 `잔고내역이 없습니다`로 실패 시 DB 포지션을 `[ghost-close]` SELL로 종료
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- exchange code 불일치 등 예외 상황에서 무한 반복 방지
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3. 테스트 7개 추가:
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- `TestExtractHeldQtyFromBalance` 3개: ord_psbl_qty 우선, 0이면 0 반환, fallback
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- `TestExtractHeldCodesFromBalance` 2개: ord_psbl_qty=0인 종목 제외, fallback
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- `TestOverseasGhostPositionClose` 2개: ghost-close 로그 확인, 일반 오류 무시
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**이슈/PR:** #235, PR #236
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@@ -346,10 +346,8 @@ class GeminiClient:
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# Validate required fields
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if not all(k in data for k in ("action", "confidence", "rationale")):
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logger.warning("Missing fields in Gemini response — defaulting to HOLD")
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# Preserve raw text in rationale so prompt_override callers (e.g. pre_market_planner)
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# can extract their own JSON format from decision.rationale (#245)
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return TradeDecision(
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action="HOLD", confidence=0, rationale=raw
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action="HOLD", confidence=0, rationale="Missing required fields"
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)
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action = str(data["action"]).upper()
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@@ -441,18 +439,6 @@ class GeminiClient:
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action="HOLD", confidence=0, rationale=f"API error: {exc}", token_count=token_count
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)
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# prompt_override callers (e.g. pre_market_planner) expect raw text back,
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# not a parsed TradeDecision. Skip parse_response to avoid spurious
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# "Missing fields" warnings and return the raw response directly. (#247)
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if "prompt_override" in market_data:
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logger.info(
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"Gemini raw response received (prompt_override, tokens=%d)", token_count
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)
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# Not a trade decision — don't inflate _total_decisions metrics
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return TradeDecision(
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action="HOLD", confidence=0, rationale=raw, token_count=token_count
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)
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decision = self.parse_response(raw)
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self._total_decisions += 1
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@@ -179,8 +179,8 @@ class PromptOptimizer:
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# Minimal instructions
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prompt = (
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f"{market_name} trader. Analyze:\n{data_str}\n\n"
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'Return JSON: {"action":"BUY"|"SELL"|"HOLD","confidence":<0-100>,"rationale":"<text>"}\n'
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"Rules: action=BUY/SELL/HOLD, confidence=0-100, rationale=concise. No markdown."
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'Return JSON: {"act":"BUY"|"SELL"|"HOLD","conf":<0-100>,"reason":"<text>"}\n'
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"Rules: act=BUY/SELL/HOLD, conf=0-100, reason=concise. No markdown."
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)
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else:
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# Data only (for cached contexts where instructions are known)
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@@ -430,7 +430,7 @@ class KISBroker:
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"fid_cond_mrkt_div_code": "J",
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"fid_cond_scr_div_code": "20170",
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"fid_input_iscd": "0000",
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"fid_rank_sort_cls_code": "0",
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"fid_rank_sort_cls_code": "0000",
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"fid_input_cnt_1": str(limit),
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"fid_prc_cls_code": "0",
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"fid_input_price_1": "0",
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@@ -466,7 +466,7 @@ class KISBroker:
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rankings = []
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for item in data.get("output", [])[:limit]:
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rankings.append({
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"stock_code": item.get("stck_shrn_iscd") or item.get("mksc_shrn_iscd", ""),
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"stock_code": item.get("mksc_shrn_iscd", ""),
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"name": item.get("hts_kor_isnm", ""),
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"price": _safe_float(item.get("stck_prpr", "0")),
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"volume": _safe_float(item.get("acml_vol", "0")),
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@@ -133,7 +133,7 @@ class OverseasBroker:
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"AUTH": "",
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"EXCD": ranking_excd,
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"NDAY": "0",
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"GUBN": "0", # 0=전체(상승+하락), 1=상승만 — 변동성 스캐너는 전체 필요
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"GUBN": "1",
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"VOL_RANG": "0",
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}
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@@ -13,11 +13,10 @@ from fastapi import FastAPI, HTTPException, Query
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from fastapi.responses import FileResponse
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def create_dashboard_app(db_path: str, mode: str = "paper") -> FastAPI:
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def create_dashboard_app(db_path: str) -> FastAPI:
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"""Create dashboard FastAPI app bound to a SQLite database path."""
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app = FastAPI(title="The Ouroboros Dashboard", version="1.0.0")
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app.state.db_path = db_path
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app.state.mode = mode
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@app.get("/")
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def index() -> FileResponse:
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@@ -112,7 +111,6 @@ def create_dashboard_app(db_path: str, mode: str = "paper") -> FastAPI:
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return {
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"date": today,
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"mode": mode,
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"markets": market_status,
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"totals": {
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"trade_count": total_trades,
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@@ -43,19 +43,6 @@
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font-size: 12px; transition: border-color 0.2s;
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}
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.refresh-btn:hover { border-color: var(--accent); color: var(--accent); }
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.mode-badge {
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padding: 3px 10px; border-radius: 5px; font-size: 12px; font-weight: 700;
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letter-spacing: 0.5px;
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}
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.mode-badge.live {
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background: rgba(224, 85, 85, 0.15); color: var(--red);
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border: 1px solid rgba(224, 85, 85, 0.4);
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animation: pulse-warn 2s ease-in-out infinite;
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}
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.mode-badge.paper {
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background: rgba(232, 160, 64, 0.15); color: var(--warn);
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border: 1px solid rgba(232, 160, 64, 0.4);
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}
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/* CB Gauge */
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.cb-gauge-wrap {
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@@ -238,7 +225,6 @@
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<header>
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<h1>🐍 The Ouroboros</h1>
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<div class="header-right">
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<span class="mode-badge" id="mode-badge">--</span>
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<div class="cb-gauge-wrap" id="cb-gauge" title="Circuit Breaker">
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<span class="cb-dot unknown" id="cb-dot"></span>
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<span id="cb-label">CB --</span>
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@@ -526,22 +512,9 @@
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}
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document.getElementById('card-pnl-sub').textContent = `결정 ${t.decision_count ?? 0}건`;
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renderCbGauge(d.circuit_breaker);
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renderModeBadge(d.mode);
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} catch {}
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}
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function renderModeBadge(mode) {
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const el = document.getElementById('mode-badge');
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if (!el) return;
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if (mode === 'live') {
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el.textContent = '🔴 실전투자';
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el.className = 'mode-badge live';
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} else {
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el.textContent = '🟡 모의투자';
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el.className = 'mode-badge paper';
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}
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}
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async function fetchPerformance() {
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try {
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const r = await fetch('/api/performance?market=all');
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99
src/main.py
99
src/main.py
@@ -182,9 +182,6 @@ async def sync_positions_from_broker(
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qty = _extract_held_qty_from_balance(
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balance_data, stock_code, is_domestic=market.is_domestic
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)
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avg_price = _extract_avg_price_from_balance(
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balance_data, stock_code, is_domestic=market.is_domestic
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)
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log_trade(
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conn=db_conn,
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stock_code=stock_code,
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@@ -192,7 +189,7 @@ async def sync_positions_from_broker(
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confidence=0,
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rationale="[startup-sync] Position detected from broker at startup",
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quantity=qty,
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price=avg_price,
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price=0.0,
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market=log_market,
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exchange_code=market.exchange_code,
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mode=settings.MODE,
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@@ -260,15 +257,7 @@ def _extract_held_codes_from_balance(
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if is_domestic:
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qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
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else:
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# ord_psbl_qty (주문가능수량) is the actual sellable quantity.
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# ovrs_cblc_qty (해외잔고수량) includes unsettled/expired holdings
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# that cannot actually be sold (e.g. expired warrants).
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qty = int(
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holding.get("ord_psbl_qty")
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or holding.get("ovrs_cblc_qty")
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or holding.get("hldg_qty")
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or 0
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)
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qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
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if qty > 0:
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codes.append(code)
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return codes
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@@ -291,12 +280,10 @@ def _extract_held_qty_from_balance(
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ord_psbl_qty — 주문가능수량 (preferred: excludes unsettled)
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hldg_qty — 보유수량 (fallback)
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Overseas fields (VTTS3012R / TTTS3012R output1):
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Overseas fields (output1):
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ovrs_pdno — 종목코드
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ord_psbl_qty — 주문가능수량 (preferred: actual sellable qty)
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ovrs_cblc_qty — 해외잔고수량 (fallback: total holding, may include
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unsettled or expired positions with ord_psbl_qty=0)
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hldg_qty — 보유수량 (last-resort fallback)
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ovrs_cblc_qty — 해외잔고수량 (preferred)
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hldg_qty — 보유수량 (fallback)
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"""
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output1 = balance_data.get("output1", [])
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if isinstance(output1, dict):
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@@ -314,47 +301,11 @@ def _extract_held_qty_from_balance(
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if is_domestic:
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qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
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else:
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qty = int(
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holding.get("ord_psbl_qty")
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or holding.get("ovrs_cblc_qty")
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or holding.get("hldg_qty")
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or 0
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)
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qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
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return qty
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return 0
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def _extract_avg_price_from_balance(
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balance_data: dict[str, Any],
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stock_code: str,
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*,
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is_domestic: bool,
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) -> float:
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"""Extract the broker-reported average purchase price for a stock.
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Uses ``pchs_avg_pric`` (매입평균가격) from the balance response (output1).
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Returns 0.0 when absent so callers can use ``if price > 0`` as sentinel.
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Domestic fields (VTTC8434R output1): pdno, pchs_avg_pric
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Overseas fields (VTTS3012R output1): ovrs_pdno, pchs_avg_pric
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"""
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output1 = balance_data.get("output1", [])
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if isinstance(output1, dict):
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output1 = [output1]
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if not isinstance(output1, list):
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return 0.0
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for holding in output1:
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if not isinstance(holding, dict):
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continue
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code_key = "pdno" if is_domestic else "ovrs_pdno"
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held_code = str(holding.get(code_key, "")).strip().upper()
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if held_code != stock_code.strip().upper():
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continue
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return safe_float(holding.get("pchs_avg_pric"), 0.0)
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return 0.0
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def _determine_order_quantity(
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*,
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action: str,
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@@ -730,7 +681,7 @@ async def trading_cycle(
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open_position = get_open_position(db_conn, stock_code, market.code)
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if open_position:
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entry_price = safe_float(open_position.get("price"), 0.0)
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if entry_price > 0 and current_price > 0:
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if entry_price > 0:
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loss_pct = (current_price - entry_price) / entry_price * 100
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stop_loss_threshold = -2.0
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take_profit_threshold = 3.0
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@@ -925,13 +876,10 @@ async def trading_cycle(
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# - SELL: -0.2% below last price — ensures fill even when price dips slightly
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# (placing at exact last price risks no-fill if the bid is just below).
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overseas_price: float
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# KIS requires at most 2 decimal places for prices >= $1 (≥1달러 소수점 2자리 제한).
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# Penny stocks (< $1) keep 4 decimal places to preserve price precision.
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_price_decimals = 2 if current_price >= 1.0 else 4
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if decision.action == "BUY":
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overseas_price = round(current_price * 1.002, _price_decimals)
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overseas_price = round(current_price * 1.002, 4)
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else:
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overseas_price = round(current_price * 0.998, _price_decimals)
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overseas_price = round(current_price * 0.998, 4)
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result = await overseas_broker.send_overseas_order(
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exchange_code=market.exchange_code,
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stock_code=stock_code,
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@@ -960,33 +908,6 @@ async def trading_cycle(
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stock_code,
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_BUY_COOLDOWN_SECONDS,
|
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)
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# Close ghost position when broker has no matching balance.
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# This prevents infinite SELL retry cycles for positions that
|
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# exist in the DB (from startup sync) but are no longer
|
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# sellable at the broker (expired warrants, delisted stocks, etc.)
|
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if decision.action == "SELL" and "잔고내역이 없습니다" in msg1:
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logger.warning(
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"Ghost position detected for %s (%s): broker reports no balance."
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" Closing DB position to prevent infinite retry.",
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stock_code,
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market.exchange_code,
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)
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log_trade(
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conn=db_conn,
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stock_code=stock_code,
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action="SELL",
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confidence=0,
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rationale=(
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"[ghost-close] Broker reported no balance;"
|
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" position closed without fill"
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),
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quantity=0,
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price=0.0,
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pnl=0.0,
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market=market.code,
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exchange_code=market.exchange_code,
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mode=settings.MODE if settings else "paper",
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)
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logger.info("Order result: %s", result.get("msg1", "OK"))
|
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# 5.5. Notify trade execution (only on success)
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@@ -2082,7 +2003,7 @@ def _start_dashboard_server(settings: Settings) -> threading.Thread | None:
|
||||
import uvicorn
|
||||
from src.dashboard import create_dashboard_app
|
||||
|
||||
app = create_dashboard_app(settings.DB_PATH, mode=settings.MODE)
|
||||
app = create_dashboard_app(settings.DB_PATH)
|
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uvicorn.run(
|
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app,
|
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host=settings.DASHBOARD_HOST,
|
||||
|
||||
114
src/strategies/v20260220_210124_evolved.py
Normal file
114
src/strategies/v20260220_210124_evolved.py
Normal file
@@ -0,0 +1,114 @@
|
||||
"""Auto-generated strategy: v20260220_210124
|
||||
|
||||
Generated at: 2026-02-20T21:01:24.706847+00:00
|
||||
Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
from typing import Any
|
||||
from src.strategies.base import BaseStrategy
|
||||
|
||||
|
||||
class Strategy_v20260220_210124(BaseStrategy):
|
||||
"""Strategy: v20260220_210124"""
|
||||
|
||||
def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
|
||||
import datetime
|
||||
|
||||
# --- Strategy Constants ---
|
||||
# Minimum price for a stock to be considered for trading (avoids penny stocks)
|
||||
MIN_PRICE = 5.0
|
||||
|
||||
# Momentum signal thresholds (stricter than previous failures)
|
||||
MOMENTUM_PRICE_CHANGE_THRESHOLD = 7.0 # % price change
|
||||
MOMENTUM_VOLUME_RATIO_THRESHOLD = 4.0 # X times average volume
|
||||
|
||||
# Oversold signal thresholds (more conservative)
|
||||
OVERSOLD_RSI_THRESHOLD = 25.0 # RSI value (lower means more oversold)
|
||||
|
||||
# Confidence levels
|
||||
CONFIDENCE_HOLD = 30
|
||||
CONFIDENCE_BUY_OVERSOLD = 65
|
||||
CONFIDENCE_BUY_MOMENTUM = 85
|
||||
CONFIDENCE_BUY_STRONG_MOMENTUM = 90 # For higher-priced stocks with strong momentum
|
||||
|
||||
# Market hours in UTC (9:30 AM ET to 4:00 PM ET)
|
||||
MARKET_OPEN_UTC = datetime.time(14, 30)
|
||||
MARKET_CLOSE_UTC = datetime.time(21, 0)
|
||||
|
||||
# Volatile periods within market hours (UTC) to avoid
|
||||
# First hour after open (14:30 UTC - 15:30 UTC)
|
||||
VOLATILE_OPEN_END_UTC = datetime.time(15, 30)
|
||||
# Last 30 minutes before close (20:30 UTC - 21:00 UTC)
|
||||
VOLATILE_CLOSE_START_UTC = datetime.time(20, 30)
|
||||
|
||||
current_price = market_data.get('current_price')
|
||||
price_change_pct = market_data.get('price_change_pct')
|
||||
volume_ratio = market_data.get('volume_ratio') # Assumed pre-computed indicator
|
||||
rsi = market_data.get('rsi') # Assumed pre-computed indicator
|
||||
timestamp_str = market_data.get('timestamp')
|
||||
|
||||
action = "HOLD"
|
||||
confidence = CONFIDENCE_HOLD
|
||||
rationale = "Initial HOLD: No clear signal or conditions not met."
|
||||
|
||||
# --- 1. Basic Data Validation ---
|
||||
if current_price is None or price_change_pct is None:
|
||||
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
|
||||
"rationale": "Insufficient core data (price or price change) to evaluate."}
|
||||
|
||||
# --- 2. Price Filter: Avoid low-priced/penny stocks ---
|
||||
if current_price < MIN_PRICE:
|
||||
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
|
||||
"rationale": f"Avoiding low-priced stock (${current_price:.2f} < ${MIN_PRICE:.2f})."}
|
||||
|
||||
# --- 3. Time Filter: Only trade during core market hours ---
|
||||
if timestamp_str:
|
||||
try:
|
||||
dt_object = datetime.datetime.fromisoformat(timestamp_str)
|
||||
current_time_utc = dt_object.time()
|
||||
|
||||
if not (MARKET_OPEN_UTC <= current_time_utc < MARKET_CLOSE_UTC):
|
||||
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
|
||||
"rationale": f"Avoiding trade outside core market hours ({current_time_utc} UTC)."}
|
||||
|
||||
if (MARKET_OPEN_UTC <= current_time_utc < VOLATILE_OPEN_END_UTC) or \
|
||||
(VOLATILE_CLOSE_START_UTC <= current_time_utc < MARKET_CLOSE_UTC):
|
||||
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
|
||||
"rationale": f"Avoiding trade during volatile market open/close periods ({current_time_utc} UTC)."}
|
||||
|
||||
except ValueError:
|
||||
rationale += " (Warning: Malformed timestamp, time filters skipped)"
|
||||
|
||||
# --- Initialize signal states ---
|
||||
has_momentum_buy_signal = False
|
||||
has_oversold_buy_signal = False
|
||||
|
||||
# --- 4. Evaluate Enhanced Buy Signals ---
|
||||
|
||||
# Momentum Buy Signal
|
||||
if volume_ratio is not None and \
|
||||
price_change_pct > MOMENTUM_PRICE_CHANGE_THRESHOLD and \
|
||||
volume_ratio > MOMENTUM_VOLUME_RATIO_THRESHOLD:
|
||||
has_momentum_buy_signal = True
|
||||
rationale = f"Momentum BUY: Price change {price_change_pct:.2f}%, Volume {volume_ratio:.2f}x."
|
||||
confidence = CONFIDENCE_BUY_MOMENTUM
|
||||
if current_price >= 10.0:
|
||||
confidence = CONFIDENCE_BUY_STRONG_MOMENTUM
|
||||
|
||||
# Oversold Buy Signal
|
||||
if rsi is not None and rsi < OVERSOLD_RSI_THRESHOLD:
|
||||
has_oversold_buy_signal = True
|
||||
if not has_momentum_buy_signal:
|
||||
rationale = f"Oversold BUY: RSI {rsi:.2f}."
|
||||
confidence = CONFIDENCE_BUY_OVERSOLD
|
||||
if current_price >= 10.0:
|
||||
confidence = min(CONFIDENCE_BUY_OVERSOLD + 5, 80)
|
||||
|
||||
# --- 5. Decision Logic ---
|
||||
if has_momentum_buy_signal:
|
||||
action = "BUY"
|
||||
elif has_oversold_buy_signal:
|
||||
action = "BUY"
|
||||
|
||||
return {"action": action, "confidence": confidence, "rationale": rationale}
|
||||
97
src/strategies/v20260220_210159_evolved.py
Normal file
97
src/strategies/v20260220_210159_evolved.py
Normal file
@@ -0,0 +1,97 @@
|
||||
"""Auto-generated strategy: v20260220_210159
|
||||
|
||||
Generated at: 2026-02-20T21:01:59.391523+00:00
|
||||
Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
from typing import Any
|
||||
from src.strategies.base import BaseStrategy
|
||||
|
||||
|
||||
class Strategy_v20260220_210159(BaseStrategy):
|
||||
"""Strategy: v20260220_210159"""
|
||||
|
||||
def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
|
||||
import datetime
|
||||
|
||||
current_price = market_data.get('current_price')
|
||||
price_change_pct = market_data.get('price_change_pct')
|
||||
volume_ratio = market_data.get('volume_ratio')
|
||||
rsi = market_data.get('rsi')
|
||||
timestamp_str = market_data.get('timestamp')
|
||||
market_name = market_data.get('market')
|
||||
|
||||
# Default action
|
||||
action = "HOLD"
|
||||
confidence = 0
|
||||
rationale = "No strong signal or conditions not met."
|
||||
|
||||
# --- FAILURE PATTERN AVOIDANCE ---
|
||||
|
||||
# 1. Avoid low-priced/penny stocks
|
||||
MIN_PRICE_THRESHOLD = 5.0 # USD
|
||||
if current_price is not None and current_price < MIN_PRICE_THRESHOLD:
|
||||
rationale = (
|
||||
f"HOLD: Stock price (${current_price:.2f}) is below minimum threshold "
|
||||
f"(${MIN_PRICE_THRESHOLD:.2f}). Past failures consistently involved low-priced stocks."
|
||||
)
|
||||
return {"action": action, "confidence": confidence, "rationale": rationale}
|
||||
|
||||
# 2. Avoid early market hour volatility
|
||||
if timestamp_str:
|
||||
try:
|
||||
dt_obj = datetime.datetime.fromisoformat(timestamp_str)
|
||||
utc_hour = dt_obj.hour
|
||||
utc_minute = dt_obj.minute
|
||||
|
||||
if (utc_hour == 14 and utc_minute < 45) or (utc_hour == 13 and utc_minute >= 30):
|
||||
rationale = (
|
||||
f"HOLD: Trading during early market hours (UTC {utc_hour}:{utc_minute}), "
|
||||
f"a period identified with past failures due to high volatility."
|
||||
)
|
||||
return {"action": action, "confidence": confidence, "rationale": rationale}
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
# --- IMPROVED BUY STRATEGY ---
|
||||
|
||||
# Momentum BUY signal
|
||||
if volume_ratio is not None and price_change_pct is not None:
|
||||
if price_change_pct > 7.0 and volume_ratio > 3.0:
|
||||
action = "BUY"
|
||||
confidence = 70
|
||||
rationale = "Improved BUY: Momentum signal with high volume and above price threshold."
|
||||
|
||||
if market_name == 'US_AMEX':
|
||||
confidence = max(55, confidence - 5)
|
||||
rationale += " (Adjusted lower for AMEX market's higher risk profile)."
|
||||
elif market_name == 'US_NASDAQ' and price_change_pct > 20:
|
||||
confidence = max(50, confidence - 10)
|
||||
rationale += " (Adjusted lower for aggressive NASDAQ momentum volatility)."
|
||||
|
||||
if price_change_pct > 15.0:
|
||||
confidence = max(50, confidence - 5)
|
||||
rationale += " (Caution: Very high daily price change, potential for reversal)."
|
||||
|
||||
return {"action": action, "confidence": confidence, "rationale": rationale}
|
||||
|
||||
# Oversold BUY signal
|
||||
if rsi is not None and price_change_pct is not None:
|
||||
if rsi < 30 and price_change_pct < -3.0:
|
||||
action = "BUY"
|
||||
confidence = 65
|
||||
rationale = "Improved BUY: Oversold signal with recent decline and above price threshold."
|
||||
|
||||
if market_name == 'US_AMEX':
|
||||
confidence = max(50, confidence - 5)
|
||||
rationale += " (Adjusted lower for AMEX market's higher risk on oversold assets)."
|
||||
|
||||
if price_change_pct < -10.0:
|
||||
confidence = max(45, confidence - 10)
|
||||
rationale += " (Caution: Very steep decline, potential falling knife)."
|
||||
|
||||
return {"action": action, "confidence": confidence, "rationale": rationale}
|
||||
|
||||
# If no specific BUY signal, default to HOLD
|
||||
return {"action": action, "confidence": confidence, "rationale": rationale}
|
||||
88
src/strategies/v20260220_210244_evolved.py
Normal file
88
src/strategies/v20260220_210244_evolved.py
Normal file
@@ -0,0 +1,88 @@
|
||||
"""Auto-generated strategy: v20260220_210244
|
||||
|
||||
Generated at: 2026-02-20T21:02:44.387355+00:00
|
||||
Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
from typing import Any
|
||||
from src.strategies.base import BaseStrategy
|
||||
|
||||
|
||||
class Strategy_v20260220_210244(BaseStrategy):
|
||||
"""Strategy: v20260220_210244"""
|
||||
|
||||
def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
|
||||
from datetime import datetime
|
||||
|
||||
# Extract required data points safely
|
||||
current_price = market_data.get("current_price")
|
||||
price_change_pct = market_data.get("price_change_pct")
|
||||
volume_ratio = market_data.get("volume_ratio")
|
||||
rsi = market_data.get("rsi")
|
||||
timestamp_str = market_data.get("timestamp")
|
||||
market_name = market_data.get("market")
|
||||
stock_code = market_data.get("stock_code", "UNKNOWN")
|
||||
|
||||
# Default action is HOLD with conservative confidence and rationale
|
||||
action = "HOLD"
|
||||
confidence = 50
|
||||
rationale = f"No strong BUY signal for {stock_code} or awaiting more favorable conditions after avoiding known failure patterns."
|
||||
|
||||
# --- 1. Failure Pattern Avoidance Filters ---
|
||||
|
||||
# A. Avoid low-priced (penny) stocks
|
||||
if current_price is not None and current_price < 5.0:
|
||||
return {
|
||||
"action": "HOLD",
|
||||
"confidence": 50,
|
||||
"rationale": f"AVOID {stock_code}: Stock price (${current_price:.2f}) is below minimum threshold ($5.00) for BUY action. Identified past failures on highly volatile, low-priced stocks."
|
||||
}
|
||||
|
||||
# B. Avoid initiating BUY trades during identified high-volatility hours
|
||||
if timestamp_str:
|
||||
try:
|
||||
trade_hour = datetime.fromisoformat(timestamp_str).hour
|
||||
if trade_hour in [14, 20]:
|
||||
return {
|
||||
"action": "HOLD",
|
||||
"confidence": 50,
|
||||
"rationale": f"AVOID {stock_code}: Trading during historically volatile hour ({trade_hour} UTC) where previous BUYs resulted in losses. Prefer to observe market stability."
|
||||
}
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
# C. Be cautious with extreme momentum spikes
|
||||
if volume_ratio is not None and price_change_pct is not None:
|
||||
if volume_ratio >= 9.0 and price_change_pct >= 15.0:
|
||||
return {
|
||||
"action": "HOLD",
|
||||
"confidence": 50,
|
||||
"rationale": f"AVOID {stock_code}: Extreme short-term momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Historical failures indicate buying into such rapid spikes often leads to reversals."
|
||||
}
|
||||
|
||||
# D. Be cautious with "oversold" signals without further confirmation
|
||||
if rsi is not None and rsi < 30:
|
||||
return {
|
||||
"action": "HOLD",
|
||||
"confidence": 50,
|
||||
"rationale": f"AVOID {stock_code}: Oversold signal (RSI={rsi:.1f}) detected. While often a BUY signal, historical failures on similar 'oversold' trades suggest waiting for stronger confirmation."
|
||||
}
|
||||
|
||||
# --- 2. Improved BUY Signal Generation ---
|
||||
if volume_ratio is not None and 2.0 <= volume_ratio < 9.0 and \
|
||||
price_change_pct is not None and 2.0 <= price_change_pct < 15.0:
|
||||
|
||||
action = "BUY"
|
||||
confidence = 70
|
||||
rationale = f"BUY {stock_code}: Moderate momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Passed filters for price and extreme momentum, avoiding past failure patterns."
|
||||
|
||||
if market_name in ["US_AMEX", "US_NASDAQ"]:
|
||||
confidence = max(60, confidence - 5)
|
||||
rationale += f" Adjusted confidence for {market_name} market characteristics."
|
||||
elif market_name == "US_NYSE":
|
||||
confidence = max(65, confidence)
|
||||
|
||||
confidence = max(50, min(85, confidence))
|
||||
|
||||
return {"action": action, "confidence": confidence, "rationale": rationale}
|
||||
@@ -93,21 +93,9 @@ class TestMalformedJsonHandling:
|
||||
|
||||
def test_json_with_missing_fields_returns_hold(self, settings):
|
||||
client = GeminiClient(settings)
|
||||
raw = '{"action": "BUY"}'
|
||||
decision = client.parse_response(raw)
|
||||
decision = client.parse_response('{"action": "BUY"}')
|
||||
assert decision.action == "HOLD"
|
||||
assert decision.confidence == 0
|
||||
# rationale preserves raw so prompt_override callers (e.g. pre_market_planner)
|
||||
# can extract non-TradeDecision JSON from decision.rationale (#245)
|
||||
assert decision.rationale == raw
|
||||
|
||||
def test_non_trade_decision_json_preserves_raw_in_rationale(self, settings):
|
||||
"""Playbook JSON (no action/confidence/rationale) must be preserved for planner."""
|
||||
client = GeminiClient(settings)
|
||||
playbook_json = '{"market_outlook": "neutral", "stocks": []}'
|
||||
decision = client.parse_response(playbook_json)
|
||||
assert decision.action == "HOLD"
|
||||
assert decision.rationale == playbook_json
|
||||
|
||||
def test_json_with_invalid_action_returns_hold(self, settings):
|
||||
client = GeminiClient(settings)
|
||||
@@ -302,10 +290,9 @@ class TestPromptOverride:
|
||||
client = GeminiClient(settings)
|
||||
|
||||
custom_prompt = "You are a playbook generator. Return JSON with scenarios."
|
||||
playbook_json = '{"market_outlook": "neutral", "stocks": []}'
|
||||
|
||||
mock_response = MagicMock()
|
||||
mock_response.text = playbook_json
|
||||
mock_response.text = '{"action": "HOLD", "confidence": 50, "rationale": "test"}'
|
||||
|
||||
with patch.object(
|
||||
client._client.aio.models,
|
||||
@@ -318,7 +305,7 @@ class TestPromptOverride:
|
||||
"current_price": 0,
|
||||
"prompt_override": custom_prompt,
|
||||
}
|
||||
decision = await client.decide(market_data)
|
||||
await client.decide(market_data)
|
||||
|
||||
# Verify the custom prompt was sent, not a built prompt
|
||||
mock_generate.assert_called_once()
|
||||
@@ -326,50 +313,17 @@ class TestPromptOverride:
|
||||
"contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
|
||||
)
|
||||
assert actual_prompt == custom_prompt
|
||||
# Raw response preserved in rationale without parse_response (#247)
|
||||
assert decision.rationale == playbook_json
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prompt_override_skips_parse_response(self, settings):
|
||||
"""prompt_override bypasses parse_response — no Missing fields warning, raw preserved."""
|
||||
async def test_prompt_override_skips_optimization(self, settings):
|
||||
"""prompt_override should bypass prompt optimization."""
|
||||
client = GeminiClient(settings)
|
||||
client._enable_optimization = True
|
||||
|
||||
custom_prompt = "Custom playbook prompt"
|
||||
playbook_json = '{"market_outlook": "bullish", "stocks": [{"stock_code": "AAPL"}]}'
|
||||
|
||||
mock_response = MagicMock()
|
||||
mock_response.text = playbook_json
|
||||
|
||||
with patch.object(
|
||||
client._client.aio.models,
|
||||
"generate_content",
|
||||
new_callable=AsyncMock,
|
||||
return_value=mock_response,
|
||||
):
|
||||
with patch.object(client, "parse_response") as mock_parse:
|
||||
market_data = {
|
||||
"stock_code": "PLANNER",
|
||||
"current_price": 0,
|
||||
"prompt_override": custom_prompt,
|
||||
}
|
||||
decision = await client.decide(market_data)
|
||||
|
||||
# parse_response must NOT be called for prompt_override
|
||||
mock_parse.assert_not_called()
|
||||
# Raw playbook JSON preserved in rationale
|
||||
assert decision.rationale == playbook_json
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prompt_override_takes_priority_over_optimization(self, settings):
|
||||
"""prompt_override must win over enable_optimization=True."""
|
||||
client = GeminiClient(settings)
|
||||
client._enable_optimization = True
|
||||
|
||||
custom_prompt = "Explicit playbook prompt"
|
||||
|
||||
mock_response = MagicMock()
|
||||
mock_response.text = '{"market_outlook": "neutral", "stocks": []}'
|
||||
mock_response.text = '{"action": "HOLD", "confidence": 50, "rationale": "ok"}'
|
||||
|
||||
with patch.object(
|
||||
client._client.aio.models,
|
||||
@@ -387,7 +341,6 @@ class TestPromptOverride:
|
||||
actual_prompt = mock_generate.call_args[1].get(
|
||||
"contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
|
||||
)
|
||||
# The custom prompt must be used, not the compressed prompt
|
||||
assert actual_prompt == custom_prompt
|
||||
|
||||
@pytest.mark.asyncio
|
||||
|
||||
@@ -354,8 +354,6 @@ class TestFetchMarketRankings:
|
||||
assert "ranking/fluctuation" in url
|
||||
assert headers.get("tr_id") == "FHPST01700000"
|
||||
assert params.get("fid_cond_scr_div_code") == "20170"
|
||||
# 실전 API는 4자리("0000") 거부 — 1자리("0")여야 한다 (#240)
|
||||
assert params.get("fid_rank_sort_cls_code") == "0"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_volume_returns_parsed_rows(self, broker: KISBroker) -> None:
|
||||
@@ -378,27 +376,6 @@ class TestFetchMarketRankings:
|
||||
assert result[0]["price"] == 75000.0
|
||||
assert result[0]["change_rate"] == 2.5
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fluctuation_parses_stck_shrn_iscd(self, broker: KISBroker) -> None:
|
||||
"""실전 API는 mksc_shrn_iscd 대신 stck_shrn_iscd를 반환한다 (#240)."""
|
||||
items = [
|
||||
{
|
||||
"stck_shrn_iscd": "015260",
|
||||
"hts_kor_isnm": "에이엔피",
|
||||
"stck_prpr": "794",
|
||||
"acml_vol": "4896196",
|
||||
"prdy_ctrt": "29.74",
|
||||
"vol_inrt": "0",
|
||||
}
|
||||
]
|
||||
mock_resp = _make_ranking_mock(items)
|
||||
with patch("aiohttp.ClientSession.get", return_value=mock_resp):
|
||||
result = await broker.fetch_market_rankings(ranking_type="fluctuation")
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["stock_code"] == "015260"
|
||||
assert result[0]["change_rate"] == 29.74
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# KRX tick unit / round-down helpers (issue #157)
|
||||
|
||||
@@ -413,39 +413,3 @@ def test_status_circuit_breaker_unknown_when_no_data(tmp_path: Path) -> None:
|
||||
cb = body["circuit_breaker"]
|
||||
assert cb["status"] == "unknown"
|
||||
assert cb["current_pnl_pct"] is None
|
||||
|
||||
|
||||
def test_status_mode_paper(tmp_path: Path) -> None:
|
||||
"""mode=paper로 생성하면 status 응답에 mode=paper가 포함돼야 한다."""
|
||||
db_path = tmp_path / "dashboard_test.db"
|
||||
conn = init_db(str(db_path))
|
||||
_seed_db(conn)
|
||||
conn.close()
|
||||
app = create_dashboard_app(str(db_path), mode="paper")
|
||||
get_status = _endpoint(app, "/api/status")
|
||||
body = get_status()
|
||||
assert body["mode"] == "paper"
|
||||
|
||||
|
||||
def test_status_mode_live(tmp_path: Path) -> None:
|
||||
"""mode=live로 생성하면 status 응답에 mode=live가 포함돼야 한다."""
|
||||
db_path = tmp_path / "dashboard_test.db"
|
||||
conn = init_db(str(db_path))
|
||||
_seed_db(conn)
|
||||
conn.close()
|
||||
app = create_dashboard_app(str(db_path), mode="live")
|
||||
get_status = _endpoint(app, "/api/status")
|
||||
body = get_status()
|
||||
assert body["mode"] == "live"
|
||||
|
||||
|
||||
def test_status_mode_default_paper(tmp_path: Path) -> None:
|
||||
"""mode 파라미터 미전달 시 기본값은 paper여야 한다."""
|
||||
db_path = tmp_path / "dashboard_test.db"
|
||||
conn = init_db(str(db_path))
|
||||
_seed_db(conn)
|
||||
conn.close()
|
||||
app = create_dashboard_app(str(db_path))
|
||||
get_status = _endpoint(app, "/api/status")
|
||||
body = get_status()
|
||||
assert body["mode"] == "paper"
|
||||
|
||||
@@ -15,7 +15,6 @@ from src.logging.decision_logger import DecisionLogger
|
||||
from src.main import (
|
||||
_apply_dashboard_flag,
|
||||
_determine_order_quantity,
|
||||
_extract_avg_price_from_balance,
|
||||
_extract_held_codes_from_balance,
|
||||
_extract_held_qty_from_balance,
|
||||
_handle_market_close,
|
||||
@@ -77,81 +76,6 @@ def _make_sell_match(stock_code: str = "005930") -> ScenarioMatch:
|
||||
)
|
||||
|
||||
|
||||
class TestExtractAvgPriceFromBalance:
|
||||
"""Tests for _extract_avg_price_from_balance() (issue #249)."""
|
||||
|
||||
def test_domestic_returns_pchs_avg_pric(self) -> None:
|
||||
"""Domestic balance with pchs_avg_pric returns the correct float."""
|
||||
balance = {"output1": [{"pdno": "005930", "pchs_avg_pric": "68000.00"}]}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 68000.0
|
||||
|
||||
def test_overseas_returns_pchs_avg_pric(self) -> None:
|
||||
"""Overseas balance with pchs_avg_pric returns the correct float."""
|
||||
balance = {"output1": [{"ovrs_pdno": "AAPL", "pchs_avg_pric": "170.50"}]}
|
||||
result = _extract_avg_price_from_balance(balance, "AAPL", is_domestic=False)
|
||||
assert result == 170.5
|
||||
|
||||
def test_returns_zero_when_field_absent(self) -> None:
|
||||
"""Returns 0.0 when pchs_avg_pric key is missing entirely."""
|
||||
balance = {"output1": [{"pdno": "005930", "ord_psbl_qty": "5"}]}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 0.0
|
||||
|
||||
def test_returns_zero_when_field_empty_string(self) -> None:
|
||||
"""Returns 0.0 when pchs_avg_pric is an empty string."""
|
||||
balance = {"output1": [{"pdno": "005930", "pchs_avg_pric": ""}]}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 0.0
|
||||
|
||||
def test_returns_zero_when_stock_not_found(self) -> None:
|
||||
"""Returns 0.0 when the requested stock_code is not in output1."""
|
||||
balance = {"output1": [{"pdno": "000660", "pchs_avg_pric": "100000.0"}]}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 0.0
|
||||
|
||||
def test_returns_zero_when_output1_empty(self) -> None:
|
||||
"""Returns 0.0 when output1 is an empty list."""
|
||||
balance = {"output1": []}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 0.0
|
||||
|
||||
def test_returns_zero_when_output1_key_absent(self) -> None:
|
||||
"""Returns 0.0 when output1 key is missing from balance_data."""
|
||||
balance: dict = {}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 0.0
|
||||
|
||||
def test_handles_output1_as_dict(self) -> None:
|
||||
"""Handles the edge case where output1 is a dict instead of a list."""
|
||||
balance = {"output1": {"pdno": "005930", "pchs_avg_pric": "55000.0"}}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 55000.0
|
||||
|
||||
def test_case_insensitive_code_matching(self) -> None:
|
||||
"""Stock code comparison is case-insensitive."""
|
||||
balance = {"output1": [{"ovrs_pdno": "aapl", "pchs_avg_pric": "170.0"}]}
|
||||
result = _extract_avg_price_from_balance(balance, "AAPL", is_domestic=False)
|
||||
assert result == 170.0
|
||||
|
||||
def test_returns_zero_for_non_numeric_string(self) -> None:
|
||||
"""Returns 0.0 when pchs_avg_pric contains a non-numeric value."""
|
||||
balance = {"output1": [{"pdno": "005930", "pchs_avg_pric": "N/A"}]}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 0.0
|
||||
|
||||
def test_returns_correct_stock_among_multiple(self) -> None:
|
||||
"""Returns only the avg price of the requested stock when output1 has multiple holdings."""
|
||||
balance = {
|
||||
"output1": [
|
||||
{"pdno": "000660", "pchs_avg_pric": "150000.0"},
|
||||
{"pdno": "005930", "pchs_avg_pric": "68000.0"},
|
||||
]
|
||||
}
|
||||
result = _extract_avg_price_from_balance(balance, "005930", is_domestic=True)
|
||||
assert result == 68000.0
|
||||
|
||||
|
||||
class TestExtractHeldQtyFromBalance:
|
||||
"""Tests for _extract_held_qty_from_balance()."""
|
||||
|
||||
@@ -177,24 +101,10 @@ class TestExtractHeldQtyFromBalance:
|
||||
balance = {"output1": [], "output2": [{}]}
|
||||
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 0
|
||||
|
||||
def test_overseas_returns_ord_psbl_qty_first(self) -> None:
|
||||
"""ord_psbl_qty (주문가능수량) takes priority over ovrs_cblc_qty."""
|
||||
balance = {
|
||||
"output1": [{"ovrs_pdno": "AAPL", "ord_psbl_qty": "8", "ovrs_cblc_qty": "10"}]
|
||||
}
|
||||
assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 8
|
||||
|
||||
def test_overseas_fallback_to_ovrs_cblc_qty_when_ord_psbl_qty_absent(self) -> None:
|
||||
def test_overseas_returns_ovrs_cblc_qty(self) -> None:
|
||||
balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "10"}]}
|
||||
assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 10
|
||||
|
||||
def test_overseas_returns_zero_when_ord_psbl_qty_zero(self) -> None:
|
||||
"""Expired/delisted securities: ovrs_cblc_qty large but ord_psbl_qty=0."""
|
||||
balance = {
|
||||
"output1": [{"ovrs_pdno": "MLECW", "ord_psbl_qty": "0", "ovrs_cblc_qty": "289456"}]
|
||||
}
|
||||
assert _extract_held_qty_from_balance(balance, "MLECW", is_domestic=False) == 0
|
||||
|
||||
def test_overseas_fallback_to_hldg_qty(self) -> None:
|
||||
balance = {"output1": [{"ovrs_pdno": "AAPL", "hldg_qty": "4"}]}
|
||||
assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 4
|
||||
@@ -237,26 +147,6 @@ class TestExtractHeldCodesFromBalance:
|
||||
result = _extract_held_codes_from_balance(balance, is_domestic=False)
|
||||
assert result == ["AAPL"]
|
||||
|
||||
def test_overseas_uses_ord_psbl_qty_to_filter(self) -> None:
|
||||
"""ord_psbl_qty=0 should exclude stock even if ovrs_cblc_qty is large."""
|
||||
balance = {
|
||||
"output1": [
|
||||
{"ovrs_pdno": "MLECW", "ord_psbl_qty": "0", "ovrs_cblc_qty": "289456"},
|
||||
{"ovrs_pdno": "AAPL", "ord_psbl_qty": "5", "ovrs_cblc_qty": "5"},
|
||||
]
|
||||
}
|
||||
result = _extract_held_codes_from_balance(balance, is_domestic=False)
|
||||
assert "MLECW" not in result
|
||||
assert "AAPL" in result
|
||||
|
||||
def test_overseas_includes_stock_when_ord_psbl_qty_absent_and_ovrs_cblc_qty_positive(
|
||||
self,
|
||||
) -> None:
|
||||
"""Fallback to ovrs_cblc_qty when ord_psbl_qty field is missing."""
|
||||
balance = {"output1": [{"ovrs_pdno": "TSLA", "ovrs_cblc_qty": "3"}]}
|
||||
result = _extract_held_codes_from_balance(balance, is_domestic=False)
|
||||
assert "TSLA" in result
|
||||
|
||||
|
||||
class TestDetermineOrderQuantity:
|
||||
"""Test _determine_order_quantity() — SELL uses broker_held_qty."""
|
||||
@@ -1246,8 +1136,7 @@ class TestOverseasBalanceParsing:
|
||||
mock_overseas_broker_with_buy_scenario.send_overseas_order.assert_called_once()
|
||||
call_kwargs = mock_overseas_broker_with_buy_scenario.send_overseas_order.call_args
|
||||
sent_price = call_kwargs[1].get("price") or call_kwargs[0][4]
|
||||
# KIS requires max 2 decimal places for prices >= $1 (#252)
|
||||
expected_price = round(182.5 * 1.002, 2) # 0.2% premium for BUY limit orders
|
||||
expected_price = round(182.5 * 1.002, 4) # 0.2% premium for BUY limit orders
|
||||
assert sent_price == expected_price, (
|
||||
f"Expected limit price {expected_price} (182.5 * 1.002) but got {sent_price}. "
|
||||
"BUY uses +0.2% to improve fill rate while minimising overpayment (#211)."
|
||||
@@ -1326,133 +1215,12 @@ class TestOverseasBalanceParsing:
|
||||
overseas_broker.send_overseas_order.assert_called_once()
|
||||
call_kwargs = overseas_broker.send_overseas_order.call_args
|
||||
sent_price = call_kwargs[1].get("price") or call_kwargs[0][4]
|
||||
# KIS requires max 2 decimal places for prices >= $1 (#252)
|
||||
expected_price = round(sell_price * 0.998, 2) # -0.2% for SELL limit orders
|
||||
expected_price = round(sell_price * 0.998, 4) # -0.2% for SELL limit orders
|
||||
assert sent_price == expected_price, (
|
||||
f"Expected SELL limit price {expected_price} (182.5 * 0.998) but got {sent_price}. "
|
||||
"SELL uses -0.2% to ensure fill even when price dips slightly (#211)."
|
||||
)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_overseas_buy_price_rounded_to_2_decimals_for_dollar_plus_stock(
|
||||
self,
|
||||
mock_domestic_broker: MagicMock,
|
||||
mock_playbook: DayPlaybook,
|
||||
mock_risk: MagicMock,
|
||||
mock_db: MagicMock,
|
||||
mock_decision_logger: MagicMock,
|
||||
mock_context_store: MagicMock,
|
||||
mock_criticality_assessor: MagicMock,
|
||||
mock_telegram: MagicMock,
|
||||
mock_overseas_market: MagicMock,
|
||||
) -> None:
|
||||
"""BUY price for $1+ stocks is rounded to 2 decimal places (issue #252).
|
||||
|
||||
KIS rejects prices with more than 2 decimal places for stocks priced >= $1.
|
||||
current_price=50.1234 * 1.002 = 50.22... should be sent as 50.22, not 50.2236.
|
||||
"""
|
||||
overseas_broker = MagicMock()
|
||||
overseas_broker.get_overseas_balance = AsyncMock(
|
||||
return_value={
|
||||
"output1": [],
|
||||
"output2": [{"frcr_evlu_tota": "0", "frcr_dncl_amt_2": "10000", "frcr_buy_amt_smtl": "0"}],
|
||||
}
|
||||
)
|
||||
overseas_broker.get_overseas_price = AsyncMock(
|
||||
return_value={"output": {"last": "50.1234", "rate": "0"}}
|
||||
)
|
||||
overseas_broker.send_overseas_order = AsyncMock(
|
||||
return_value={"rt_cd": None, "msg1": "주문접수"}
|
||||
)
|
||||
|
||||
db_conn = init_db(":memory:")
|
||||
decision_logger = DecisionLogger(db_conn)
|
||||
|
||||
engine = MagicMock(spec=ScenarioEngine)
|
||||
engine.evaluate = MagicMock(return_value=_make_buy_match())
|
||||
|
||||
await trading_cycle(
|
||||
broker=mock_domestic_broker,
|
||||
overseas_broker=overseas_broker,
|
||||
scenario_engine=engine,
|
||||
playbook=mock_playbook,
|
||||
risk=mock_risk,
|
||||
db_conn=db_conn,
|
||||
decision_logger=decision_logger,
|
||||
context_store=mock_context_store,
|
||||
criticality_assessor=mock_criticality_assessor,
|
||||
telegram=mock_telegram,
|
||||
market=mock_overseas_market,
|
||||
stock_code="TQQQ",
|
||||
scan_candidates={},
|
||||
)
|
||||
|
||||
overseas_broker.send_overseas_order.assert_called_once()
|
||||
sent_price = overseas_broker.send_overseas_order.call_args[1].get("price") or \
|
||||
overseas_broker.send_overseas_order.call_args[0][4]
|
||||
# 50.1234 * 1.002 = 50.2235... rounded to 2 decimals = 50.22
|
||||
assert sent_price == round(50.1234 * 1.002, 2), (
|
||||
f"Expected 2-decimal price {round(50.1234 * 1.002, 2)} but got {sent_price} (#252)"
|
||||
)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_overseas_penny_stock_price_keeps_4_decimals(
|
||||
self,
|
||||
mock_domestic_broker: MagicMock,
|
||||
mock_playbook: DayPlaybook,
|
||||
mock_risk: MagicMock,
|
||||
mock_db: MagicMock,
|
||||
mock_decision_logger: MagicMock,
|
||||
mock_context_store: MagicMock,
|
||||
mock_criticality_assessor: MagicMock,
|
||||
mock_telegram: MagicMock,
|
||||
mock_overseas_market: MagicMock,
|
||||
) -> None:
|
||||
"""BUY price for penny stocks (< $1) uses 4 decimal places (issue #252)."""
|
||||
overseas_broker = MagicMock()
|
||||
overseas_broker.get_overseas_balance = AsyncMock(
|
||||
return_value={
|
||||
"output1": [],
|
||||
"output2": [{"frcr_evlu_tota": "0", "frcr_dncl_amt_2": "10000", "frcr_buy_amt_smtl": "0"}],
|
||||
}
|
||||
)
|
||||
overseas_broker.get_overseas_price = AsyncMock(
|
||||
return_value={"output": {"last": "0.5678", "rate": "0"}}
|
||||
)
|
||||
overseas_broker.send_overseas_order = AsyncMock(
|
||||
return_value={"rt_cd": None, "msg1": "주문접수"}
|
||||
)
|
||||
|
||||
db_conn = init_db(":memory:")
|
||||
decision_logger = DecisionLogger(db_conn)
|
||||
|
||||
engine = MagicMock(spec=ScenarioEngine)
|
||||
engine.evaluate = MagicMock(return_value=_make_buy_match())
|
||||
|
||||
await trading_cycle(
|
||||
broker=mock_domestic_broker,
|
||||
overseas_broker=overseas_broker,
|
||||
scenario_engine=engine,
|
||||
playbook=mock_playbook,
|
||||
risk=mock_risk,
|
||||
db_conn=db_conn,
|
||||
decision_logger=decision_logger,
|
||||
context_store=mock_context_store,
|
||||
criticality_assessor=mock_criticality_assessor,
|
||||
telegram=mock_telegram,
|
||||
market=mock_overseas_market,
|
||||
stock_code="PENNYX",
|
||||
scan_candidates={},
|
||||
)
|
||||
|
||||
overseas_broker.send_overseas_order.assert_called_once()
|
||||
sent_price = overseas_broker.send_overseas_order.call_args[1].get("price") or \
|
||||
overseas_broker.send_overseas_order.call_args[0][4]
|
||||
# 0.5678 * 1.002 = 0.56893... rounded to 4 decimals = 0.5689
|
||||
assert sent_price == round(0.5678 * 1.002, 4), (
|
||||
f"Expected 4-decimal price {round(0.5678 * 1.002, 4)} but got {sent_price} (#252)"
|
||||
)
|
||||
|
||||
|
||||
class TestScenarioEngineIntegration:
|
||||
"""Test scenario engine integration in trading_cycle."""
|
||||
@@ -2246,92 +2014,6 @@ async def test_hold_not_overridden_when_between_stop_loss_and_take_profit() -> N
|
||||
broker.send_order.assert_not_called()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_stop_loss_not_triggered_when_current_price_is_zero() -> None:
|
||||
"""HOLD must stay HOLD when current_price=0 even if entry_price is set (issue #251).
|
||||
|
||||
A price API failure that returns 0.0 must not cause a false -100% stop-loss.
|
||||
"""
|
||||
db_conn = init_db(":memory:")
|
||||
decision_logger = DecisionLogger(db_conn)
|
||||
|
||||
buy_decision_id = decision_logger.log_decision(
|
||||
stock_code="005930",
|
||||
market="KR",
|
||||
exchange_code="KRX",
|
||||
action="BUY",
|
||||
confidence=90,
|
||||
rationale="entry",
|
||||
context_snapshot={},
|
||||
input_data={},
|
||||
)
|
||||
log_trade(
|
||||
conn=db_conn,
|
||||
stock_code="005930",
|
||||
action="BUY",
|
||||
confidence=90,
|
||||
rationale="entry",
|
||||
quantity=1,
|
||||
price=100.0, # valid entry price
|
||||
market="KR",
|
||||
exchange_code="KRX",
|
||||
decision_id=buy_decision_id,
|
||||
)
|
||||
|
||||
broker = MagicMock()
|
||||
# Price API returns 0.0 — simulates API failure or pre-market unavailability
|
||||
broker.get_current_price = AsyncMock(return_value=(0.0, 0.0, 0.0))
|
||||
broker.get_balance = AsyncMock(
|
||||
return_value={
|
||||
"output2": [
|
||||
{
|
||||
"tot_evlu_amt": "100000",
|
||||
"dnca_tot_amt": "10000",
|
||||
"pchs_amt_smtl_amt": "90000",
|
||||
}
|
||||
]
|
||||
}
|
||||
)
|
||||
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
||||
|
||||
market = MagicMock()
|
||||
market.name = "Korea"
|
||||
market.code = "KR"
|
||||
market.exchange_code = "KRX"
|
||||
market.is_domestic = True
|
||||
|
||||
telegram = MagicMock()
|
||||
telegram.notify_trade_execution = AsyncMock()
|
||||
telegram.notify_fat_finger = AsyncMock()
|
||||
telegram.notify_circuit_breaker = AsyncMock()
|
||||
telegram.notify_scenario_matched = AsyncMock()
|
||||
|
||||
await trading_cycle(
|
||||
broker=broker,
|
||||
overseas_broker=MagicMock(),
|
||||
scenario_engine=MagicMock(evaluate=MagicMock(return_value=_make_hold_match())),
|
||||
playbook=_make_playbook("KR"),
|
||||
risk=MagicMock(),
|
||||
db_conn=db_conn,
|
||||
decision_logger=decision_logger,
|
||||
context_store=MagicMock(
|
||||
get_latest_timeframe=MagicMock(return_value=None),
|
||||
set_context=MagicMock(),
|
||||
),
|
||||
criticality_assessor=MagicMock(
|
||||
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
|
||||
get_timeout=MagicMock(return_value=5.0),
|
||||
),
|
||||
telegram=telegram,
|
||||
market=market,
|
||||
stock_code="005930",
|
||||
scan_candidates={},
|
||||
)
|
||||
|
||||
# No SELL order must be placed — current_price=0 must suppress stop-loss
|
||||
broker.send_order.assert_not_called()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_sell_order_uses_broker_balance_qty_not_db() -> None:
|
||||
"""SELL quantity must come from broker balance output1, not DB.
|
||||
@@ -4102,70 +3784,6 @@ class TestSyncPositionsFromBroker:
|
||||
# Two distinct exchange codes (NASD, NYSE) → 2 calls
|
||||
assert overseas_broker.get_overseas_balance.call_count == 2
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_syncs_domestic_position_with_correct_avg_price(self) -> None:
|
||||
"""Domestic position is stored with pchs_avg_pric as price (issue #249)."""
|
||||
settings = self._make_settings("KR")
|
||||
db_conn = init_db(":memory:")
|
||||
|
||||
balance = {
|
||||
"output1": [{"pdno": "005930", "ord_psbl_qty": "5", "pchs_avg_pric": "68000.0"}],
|
||||
"output2": [{"tot_evlu_amt": "1000000", "dnca_tot_amt": "500000", "pchs_amt_smtl_amt": "500000"}],
|
||||
}
|
||||
broker = MagicMock()
|
||||
broker.get_balance = AsyncMock(return_value=balance)
|
||||
overseas_broker = MagicMock()
|
||||
|
||||
await sync_positions_from_broker(broker, overseas_broker, db_conn, settings)
|
||||
|
||||
from src.db import get_open_position
|
||||
pos = get_open_position(db_conn, "005930", "KR")
|
||||
assert pos is not None
|
||||
assert pos["price"] == 68000.0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_syncs_overseas_position_with_correct_avg_price(self) -> None:
|
||||
"""Overseas position is stored with pchs_avg_pric as price (issue #249)."""
|
||||
settings = self._make_settings("US_NASDAQ")
|
||||
db_conn = init_db(":memory:")
|
||||
|
||||
balance = {
|
||||
"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "10", "pchs_avg_pric": "170.0"}],
|
||||
"output2": [{"frcr_evlu_tota": "50000", "frcr_dncl_amt_2": "10000", "frcr_buy_amt_smtl": "40000"}],
|
||||
}
|
||||
broker = MagicMock()
|
||||
overseas_broker = MagicMock()
|
||||
overseas_broker.get_overseas_balance = AsyncMock(return_value=balance)
|
||||
|
||||
await sync_positions_from_broker(broker, overseas_broker, db_conn, settings)
|
||||
|
||||
from src.db import get_open_position
|
||||
pos = get_open_position(db_conn, "AAPL", "US_NASDAQ")
|
||||
assert pos is not None
|
||||
assert pos["price"] == 170.0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_syncs_position_with_zero_price_when_pchs_avg_pric_absent(self) -> None:
|
||||
"""Fallback to price=0.0 when pchs_avg_pric is absent (issue #249)."""
|
||||
settings = self._make_settings("KR")
|
||||
db_conn = init_db(":memory:")
|
||||
|
||||
# No pchs_avg_pric in output1
|
||||
balance = {
|
||||
"output1": [{"pdno": "005930", "ord_psbl_qty": "5"}],
|
||||
"output2": [{"tot_evlu_amt": "1000000", "dnca_tot_amt": "500000", "pchs_amt_smtl_amt": "500000"}],
|
||||
}
|
||||
broker = MagicMock()
|
||||
broker.get_balance = AsyncMock(return_value=balance)
|
||||
overseas_broker = MagicMock()
|
||||
|
||||
await sync_positions_from_broker(broker, overseas_broker, db_conn, settings)
|
||||
|
||||
from src.db import get_open_position
|
||||
pos = get_open_position(db_conn, "005930", "KR")
|
||||
assert pos is not None
|
||||
assert pos["price"] == 0.0
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Domestic BUY double-prevention (issue #206) — trading_cycle integration
|
||||
@@ -4760,189 +4378,3 @@ class TestDomesticLimitOrderPrice:
|
||||
expected_price = kr_round_down(current_price * 0.998)
|
||||
assert call_kwargs["price"] == expected_price
|
||||
assert call_kwargs["order_type"] == "SELL"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Ghost position — overseas SELL "잔고내역이 없습니다" handling
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class TestOverseasGhostPositionClose:
|
||||
"""trading_cycle must close ghost DB position when broker returns 잔고없음."""
|
||||
|
||||
def _make_overseas_market(self) -> MagicMock:
|
||||
market = MagicMock()
|
||||
market.name = "NASDAQ"
|
||||
market.code = "US_NASDAQ"
|
||||
market.exchange_code = "NASD"
|
||||
market.is_domestic = False
|
||||
return market
|
||||
|
||||
def _make_overseas_broker(
|
||||
self,
|
||||
current_price: float,
|
||||
balance_data: dict,
|
||||
sell_result: dict,
|
||||
) -> MagicMock:
|
||||
ob = MagicMock()
|
||||
ob.get_overseas_price = AsyncMock(
|
||||
return_value={"output": {"last": str(current_price), "rate": "0.0"}}
|
||||
)
|
||||
ob.get_overseas_balance = AsyncMock(return_value=balance_data)
|
||||
ob.send_overseas_order = AsyncMock(return_value=sell_result)
|
||||
return ob
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_ghost_position_closes_db_on_no_balance_error(self) -> None:
|
||||
"""When SELL fails with '잔고내역이 없습니다', log_trade is called to close the ghost.
|
||||
|
||||
This can happen when exchange code recorded at startup differs from the
|
||||
exchange code used in the SELL cycle (e.g. KNRX recorded as NASD but
|
||||
actually traded on AMEX), causing the broker to see no matching balance.
|
||||
The position has ord_psbl_qty > 0 (so a SELL is attempted), but KIS
|
||||
rejects it with '잔고내역이 없습니다'.
|
||||
"""
|
||||
from src.strategy.models import ScenarioAction
|
||||
|
||||
stock_code = "KNRX"
|
||||
current_price = 1.5
|
||||
# ord_psbl_qty=5 means the code passes the qty check and a SELL is sent
|
||||
balance_data = {
|
||||
"output1": [
|
||||
{"ovrs_pdno": stock_code, "ord_psbl_qty": "5", "ovrs_cblc_qty": "5"}
|
||||
],
|
||||
"output2": [{"tot_evlu_amt": "10000", "frcr_dncl_amt_2": "10000"}],
|
||||
}
|
||||
sell_result = {"rt_cd": "1", "msg1": "모의투자 잔고내역이 없습니다"}
|
||||
|
||||
domestic_broker = MagicMock()
|
||||
domestic_broker.get_balance = AsyncMock(return_value={"output1": [], "output2": [{}]})
|
||||
overseas_broker = self._make_overseas_broker(current_price, balance_data, sell_result)
|
||||
market = self._make_overseas_market()
|
||||
|
||||
sell_match = ScenarioMatch(
|
||||
stock_code=stock_code,
|
||||
matched_scenario=None,
|
||||
action=ScenarioAction.SELL,
|
||||
confidence=85,
|
||||
rationale="test ghost KNRX",
|
||||
)
|
||||
engine = MagicMock(spec=ScenarioEngine)
|
||||
engine.evaluate = MagicMock(return_value=sell_match)
|
||||
|
||||
risk = MagicMock()
|
||||
risk.validate_order = MagicMock()
|
||||
risk.check_circuit_breaker = MagicMock()
|
||||
telegram = MagicMock()
|
||||
telegram.notify_trade_execution = AsyncMock()
|
||||
telegram.notify_fat_finger = AsyncMock()
|
||||
telegram.notify_circuit_breaker = AsyncMock()
|
||||
telegram.notify_scenario_matched = AsyncMock()
|
||||
|
||||
db_conn = MagicMock()
|
||||
|
||||
settings = MagicMock(spec=Settings)
|
||||
settings.MODE = "paper"
|
||||
settings.POSITION_SIZING_ENABLED = False
|
||||
settings.PAPER_OVERSEAS_CASH = 0
|
||||
|
||||
with patch("src.main.log_trade") as mock_log_trade, patch(
|
||||
"src.main.get_open_position", return_value=None
|
||||
), patch("src.main.get_latest_buy_trade", return_value=None):
|
||||
await trading_cycle(
|
||||
broker=domestic_broker,
|
||||
overseas_broker=overseas_broker,
|
||||
scenario_engine=engine,
|
||||
playbook=_make_playbook(market="US_NASDAQ"),
|
||||
risk=risk,
|
||||
db_conn=db_conn,
|
||||
decision_logger=MagicMock(),
|
||||
context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
|
||||
criticality_assessor=MagicMock(
|
||||
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
|
||||
get_timeout=MagicMock(return_value=5.0),
|
||||
),
|
||||
telegram=telegram,
|
||||
market=market,
|
||||
stock_code=stock_code,
|
||||
scan_candidates={},
|
||||
settings=settings,
|
||||
)
|
||||
|
||||
# log_trade must be called with action="SELL" to close the ghost position
|
||||
ghost_close_calls = [
|
||||
c
|
||||
for c in mock_log_trade.call_args_list
|
||||
if c.kwargs.get("action") == "SELL"
|
||||
and "[ghost-close]" in (c.kwargs.get("rationale") or "")
|
||||
]
|
||||
assert ghost_close_calls, "Expected ghost-close log_trade call was not made"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_normal_sell_failure_does_not_close_db(self) -> None:
|
||||
"""Non-잔고없음 SELL failures must NOT close the DB position."""
|
||||
from src.strategy.models import ScenarioAction
|
||||
|
||||
stock_code = "TSLA"
|
||||
current_price = 250.0
|
||||
balance_data = {
|
||||
"output1": [{"ovrs_pdno": stock_code, "ord_psbl_qty": "5", "ovrs_cblc_qty": "5"}],
|
||||
"output2": [{"tot_evlu_amt": "100000", "frcr_dncl_amt_2": "100000"}],
|
||||
}
|
||||
sell_result = {"rt_cd": "1", "msg1": "일시적 오류가 발생했습니다"}
|
||||
|
||||
domestic_broker = MagicMock()
|
||||
domestic_broker.get_balance = AsyncMock(return_value={"output1": [], "output2": [{}]})
|
||||
overseas_broker = self._make_overseas_broker(current_price, balance_data, sell_result)
|
||||
market = self._make_overseas_market()
|
||||
|
||||
sell_match = ScenarioMatch(
|
||||
stock_code=stock_code,
|
||||
matched_scenario=None,
|
||||
action=ScenarioAction.SELL,
|
||||
confidence=85,
|
||||
rationale="test",
|
||||
)
|
||||
engine = MagicMock(spec=ScenarioEngine)
|
||||
engine.evaluate = MagicMock(return_value=sell_match)
|
||||
|
||||
risk = MagicMock()
|
||||
risk.validate_order = MagicMock()
|
||||
risk.check_circuit_breaker = MagicMock()
|
||||
telegram = MagicMock()
|
||||
telegram.notify_trade_execution = AsyncMock()
|
||||
telegram.notify_fat_finger = AsyncMock()
|
||||
telegram.notify_circuit_breaker = AsyncMock()
|
||||
telegram.notify_scenario_matched = AsyncMock()
|
||||
|
||||
db_conn = MagicMock()
|
||||
|
||||
with patch("src.main.log_trade") as mock_log_trade, patch(
|
||||
"src.main.get_open_position", return_value=None
|
||||
):
|
||||
await trading_cycle(
|
||||
broker=domestic_broker,
|
||||
overseas_broker=overseas_broker,
|
||||
scenario_engine=engine,
|
||||
playbook=_make_playbook(market="US_NASDAQ"),
|
||||
risk=risk,
|
||||
db_conn=db_conn,
|
||||
decision_logger=MagicMock(),
|
||||
context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
|
||||
criticality_assessor=MagicMock(
|
||||
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
|
||||
get_timeout=MagicMock(return_value=5.0),
|
||||
),
|
||||
telegram=telegram,
|
||||
market=market,
|
||||
stock_code=stock_code,
|
||||
scan_candidates={},
|
||||
)
|
||||
|
||||
ghost_close_calls = [
|
||||
c
|
||||
for c in mock_log_trade.call_args_list
|
||||
if c.kwargs.get("action") == "SELL"
|
||||
and "[ghost-close]" in (c.kwargs.get("rationale") or "")
|
||||
]
|
||||
assert not ghost_close_calls, "Ghost-close must NOT be triggered for non-잔고없음 errors"
|
||||
|
||||
@@ -124,7 +124,7 @@ class TestFetchOverseasRankings:
|
||||
assert "/uapi/overseas-stock/v1/ranking/updown-rate" in url
|
||||
assert params["EXCD"] == "NAS"
|
||||
assert params["NDAY"] == "0"
|
||||
assert params["GUBN"] == "0" # 0=전체(상승+하락), 변동성 스캐너에 필요
|
||||
assert params["GUBN"] == "1"
|
||||
assert params["VOL_RANG"] == "0"
|
||||
|
||||
overseas_broker._broker._auth_headers.assert_called_with("HHDFS76290000")
|
||||
|
||||
@@ -124,10 +124,6 @@ class TestPromptOptimizer:
|
||||
assert len(prompt) < 300
|
||||
assert "005930" in prompt
|
||||
assert "75000" in prompt
|
||||
# Keys must match parse_response expectations (#242)
|
||||
assert '"action"' in prompt
|
||||
assert '"confidence"' in prompt
|
||||
assert '"rationale"' in prompt
|
||||
|
||||
def test_build_compressed_prompt_no_instructions(self):
|
||||
"""Test compressed prompt without instructions."""
|
||||
|
||||
Reference in New Issue
Block a user