Files
stock_chart_site/backend/app/api/symbols.py
claude-owner ae4f07d675 feat(home+search): KOSPI/KOSDAQ 인덱스 카드 + 검색결과 미니 sparkline
- Sparkline 컴포넌트를 PriceHero 내부에서 web/components/Sparkline.tsx 로 분리·재사용
- /api/markets/indices: macro_daily 의 kospi/kosdaq N일 시계열 + 최신값/전일대비
- 홈 IndicesPanel: 두 인덱스 카드(현재값/등락/우측 sparkline)
- /api/symbols/search?with_sparkline=true: 결과 한 번에 최근 30 종가 batch 조회
- SearchBox 결과 행에 mini sparkline + 현재가/등락률 인라인 표시

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-28 14:46:13 +09:00

143 lines
4.7 KiB
Python

"""종목 검색 / 메타 API."""
from __future__ import annotations
from fastapi import APIRouter, HTTPException, Query
from sqlalchemy import text
from app.db.connection import get_engine
router = APIRouter(prefix="/api/symbols", tags=["symbols"])
@router.get("/search")
def search_symbols(
q: str = Query(..., min_length=1, max_length=40, description="종목명 또는 코드 prefix/부분 일치"),
limit: int = Query(default=20, ge=1, le=100),
seed_only: bool = Query(default=False, description="true 면 학습/배치 대상 10종목만"),
with_sparkline: bool = Query(
default=False,
description="true 면 각 결과에 최근 30 종가 + 전일대비 동봉 (검색 결과 미니차트용)",
),
) -> dict:
"""이름은 trigram + ILIKE, 코드는 prefix 매치.
우선순위:
1) 코드가 정확히 같으면 가장 위
2) 이름 prefix 매치
3) 이름 부분 매치 (trigram similarity)
with_sparkline=true 시:
- 매치된 코드들에 대해 ohlcv_daily 최근 30 거래일 종가 한 번에 조회
- items[*].sparkline (list[float]) + items[*].close + items[*].pct_change 채움
- 데이터 없는 종목은 sparkline=[], close=None
"""
q_norm = q.strip()
if not q_norm:
raise HTTPException(status_code=400, detail="empty query")
eng = get_engine()
where_seed = "AND is_seed = TRUE" if seed_only else ""
sql = text(
f"""
WITH ranked AS (
SELECT code, name, market, sector, is_seed,
CASE
WHEN code = :q THEN 0
WHEN code LIKE :prefix THEN 1
WHEN name LIKE :prefix THEN 2
WHEN name ILIKE :contains THEN 3
ELSE 4
END AS rank,
similarity(name, :q) AS sim
FROM symbols
WHERE active = TRUE
{where_seed}
AND (code LIKE :prefix OR name ILIKE :contains OR similarity(name, :q) > 0.2)
)
SELECT code, name, market, sector, is_seed
FROM ranked
ORDER BY rank ASC, sim DESC, name ASC
LIMIT :lim
"""
)
with eng.connect() as conn:
rows = conn.execute(
sql,
{
"q": q_norm,
"prefix": f"{q_norm}%",
"contains": f"%{q_norm}%",
"lim": limit,
},
).all()
codes = [r[0] for r in rows]
spark_by_code: dict[str, list[float]] = {c: [] for c in codes}
if with_sparkline and codes:
# 최근 30 거래일 종가 — 종목별로 ORDER BY date ASC.
spark_rows = conn.execute(
text(
"""
SELECT code, date, close FROM (
SELECT code, date, close,
ROW_NUMBER() OVER (PARTITION BY code ORDER BY date DESC) AS rn
FROM ohlcv_daily
WHERE code = ANY(:codes) AND close IS NOT NULL
) t
WHERE rn <= 30
ORDER BY code, date ASC
"""
),
{"codes": codes},
).all()
for code, _d, close in spark_rows:
spark_by_code.setdefault(code, []).append(float(close))
def _item(r) -> dict:
code = r[0]
pts = spark_by_code.get(code, []) if with_sparkline else None
out: dict[str, object] = {
"code": code,
"name": r[1],
"market": r[2],
"sector": r[3],
"is_seed": bool(r[4]),
}
if with_sparkline:
out["sparkline"] = pts or []
out["close"] = pts[-1] if pts else None
out["pct_change"] = (
(pts[-1] - pts[-2]) / pts[-2] * 100 if (pts and len(pts) >= 2 and pts[-2]) else None
)
return out
return {
"q": q_norm,
"count": len(rows),
"items": [_item(r) for r in rows],
}
@router.get("/{code}")
def get_symbol(code: str) -> dict:
eng = get_engine()
with eng.connect() as conn:
row = conn.execute(
text(
"SELECT code, name, market, sector, is_seed, active, created_at "
"FROM symbols WHERE code = :c"
),
{"c": code},
).first()
if not row:
raise HTTPException(status_code=404, detail=f"unknown code: {code}")
return {
"code": row[0],
"name": row[1],
"market": row[2],
"sector": row[3],
"is_seed": bool(row[4]),
"active": bool(row[5]),
"created_at": str(row[6]) if row[6] else None,
}