import datetime as dt
import pandas as pd

from app.screener.engine import ScreenContext
from app.screener.nodes.volume_surge import VolumeSurge
from app.screener._test_fixtures import make_master, make_prices, make_flow


def _ctx(master, prices, flow):
    return ScreenContext(master=master, prices=prices, flow=flow,
                         kospi=pd.Series(dtype=float, name="kospi"),
                         asof=dt.date(2026, 5, 12))


def test_recent_volume_surge_gets_higher_score():
    asof = dt.date(2026, 5, 12)
    master = make_master(["A", "B"])
    prices = make_prices(["A", "B"], days=30, asof=asof)
    # A는 최근 3일 거래량 10배로
    mask = (prices["ticker"] == "A") & (prices["date"] >= (asof - dt.timedelta(days=3)).isoformat())
    prices.loc[mask, "volume"] *= 10
    flow = make_flow(["A", "B"], days=30, asof=asof)

    out = VolumeSurge().compute(
        _ctx(master, prices, flow),
        {"baseline_days": 20, "eval_days": 3},
    )
    assert out["A"] > out["B"]
