gahusb
ace0339d33
- git mv stock-lab/ → stock/ - docker-compose.yml: 서비스 키 + container_name + build.context + frontend.depends_on + agent-office STOCK_LAB_URL → STOCK_URL - agent-office/app: config.py, service_proxy.py, agents/stock.py, tests/ STOCK_LAB_URL → STOCK_URL - nginx/default.conf: proxy_pass http://stock-lab → http://stock (3 lines) - CLAUDE.md / README.md / STATUS.md / scripts/ 문구 갱신 - stock/ 내부 자기 참조 갱신 lab 네이밍 정책 (feedback_lab_naming.md) graduation. API URL / Python import / DB 파일명 변경 없음.
121 lines
4.3 KiB
Python
121 lines
4.3 KiB
Python
"""Tests for ai_news validation harness (Spearman IC)."""
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import datetime as dt
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import sqlite3
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import pytest
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from app.screener.ai_news import validation
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from app.screener.schema import ensure_screener_schema
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@pytest.fixture
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def conn():
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c = sqlite3.connect(":memory:")
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c.row_factory = sqlite3.Row
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ensure_screener_schema(c)
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yield c
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c.close()
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def _seed_sentiment(conn, date, ticker, score, news_count=3):
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conn.execute(
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"INSERT INTO news_sentiment (ticker, date, score_raw, reason, news_count, "
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"tokens_input, tokens_output, model) "
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"VALUES (?, ?, ?, 'r', ?, 100, 20, 'm')",
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(ticker, date, score, news_count),
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)
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def _seed_price(conn, ticker, date, close):
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conn.execute(
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"INSERT INTO krx_daily_prices (ticker, date, close) VALUES (?, ?, ?)",
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(ticker, date, close),
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)
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def test_empty_db_returns_skip(conn):
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out = validation.compute_ic(conn, days=30, horizon=1, asof_today=dt.date(2026, 5, 14))
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assert out["ic_count"] == 0
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assert out["verdict"] == "skip"
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assert out["ic_mean"] is None
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def test_strong_positive_ic(conn):
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"""5종목 × 12일 — 점수가 높을수록 다음날 수익률 높게 시드 → IC ≈ +1.
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score 가 변하지 않는 ticker × day-wise close 로 정확한 monotonic 관계 시드.
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"""
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base_date = dt.date(2026, 5, 1)
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# 가격 13일치 시드 (day0..day12). ticker별 base 다르고 (score-기반) day마다 다른 close.
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for i, ticker in enumerate(["A", "B", "C", "D", "E"]):
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score = i * 2.0 - 4.0 # ticker별 score 고정 (-4, -2, 0, +2, +4)
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# day 0 close=100, day n close=100+(score × n)
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for day in range(13):
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d = (base_date + dt.timedelta(days=day)).isoformat()
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_seed_price(conn, ticker, d, 100.0 + score * day)
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if day < 12:
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_seed_sentiment(conn, d, ticker, score)
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conn.commit()
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out = validation.compute_ic(conn, days=30, horizon=1, asof_today=dt.date(2026, 5, 14))
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assert out["ic_count"] >= 10
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assert out["ic_mean"] > 0.5
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assert out["verdict"] == "strong"
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def test_zero_ic_random_data(conn):
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"""점수와 수익률이 무관 → IC ≈ 0."""
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import random
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random.seed(42)
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base_date = dt.date(2026, 5, 1)
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for ticker in ["A", "B", "C", "D", "E", "F", "G"]:
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for day in range(13):
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d = (base_date + dt.timedelta(days=day)).isoformat()
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_seed_price(conn, ticker, d, 100.0 + random.uniform(-5, 5))
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if day < 12:
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_seed_sentiment(conn, d, ticker, random.uniform(-10, 10))
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conn.commit()
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out = validation.compute_ic(conn, days=30, horizon=1, asof_today=dt.date(2026, 5, 14))
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assert out["ic_count"] >= 10
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assert abs(out["ic_mean"]) < 0.3 # 약한 신호 — verdict는 weak 가능
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assert out["verdict"] in ("weak", "strong") # 시드에 따라 약간 흔들림
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def test_min_news_count_filter(conn):
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"""news_count < min_news_count 인 row 는 제외."""
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_seed_sentiment(conn, "2026-05-13", "A", 5.0, news_count=0)
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_seed_sentiment(conn, "2026-05-13", "B", -5.0, news_count=3)
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_seed_price(conn, "A", "2026-05-13", 100.0)
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_seed_price(conn, "A", "2026-05-14", 105.0)
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_seed_price(conn, "B", "2026-05-13", 100.0)
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_seed_price(conn, "B", "2026-05-14", 95.0)
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conn.commit()
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out = validation.compute_ic(
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conn, days=30, horizon=1, min_news_count=1,
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asof_today=dt.date(2026, 5, 14),
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)
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# A 가 필터됨 → 1종목만 남으면 Spearman 계산 불가 (< 5) → skip
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assert out["ic_count"] == 0
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def test_horizon_5_days(conn):
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"""horizon=5 면 close[date+5] / close[date] - 1 사용."""
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base_date = dt.date(2026, 5, 1)
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for day in range(20):
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d = (base_date + dt.timedelta(days=day)).isoformat()
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for i, ticker in enumerate(["A", "B", "C", "D", "E"]):
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_seed_sentiment(conn, d, ticker, i * 2.0 - 4.0)
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# 가격: A=오름, B=오름, C=평, D=내림, E=내림
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for day in range(25):
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d = (base_date + dt.timedelta(days=day)).isoformat()
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for i, ticker in enumerate(["A", "B", "C", "D", "E"]):
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slope = i - 2 # -2 ~ +2
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_seed_price(conn, ticker, d, 100.0 + slope * day)
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conn.commit()
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out = validation.compute_ic(conn, days=30, horizon=5, asof_today=dt.date(2026, 5, 25))
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assert out["horizon_days"] == 5
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assert out["ic_count"] > 0
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