from __future__ import annotations

from typing import Any

import pandas as pd

_SLOT_LINEUP = {
    "On Deck": "on_deck",   "on_deck": "on_deck",
    "In Hole": "in_hole",   "in_hole": "in_hole",
    "3 Away":  "three_away","three_away": "three_away",
}


def build_recommendation_log_rows(
    recommendations: list[dict[str, Any]],
    game_row: dict[str, Any],
    created_at: str,
) -> pd.DataFrame:
    rows: list[dict[str, Any]] = []

    away_team = str(game_row.get("away_team", "") or "").strip()
    home_team = str(game_row.get("home_team", "") or "").strip()
    status = str(game_row.get("status", "") or "").strip()
    game_pk = str(game_row.get("game_pk", "") or "").strip()

    for rec in recommendations:
        rows.append(
            {
                "created_at": created_at,
                "game_pk": game_pk,
                "away_team": away_team,
                "home_team": home_team,
                "status": status,
                "slot": rec.get("slot"),
                "batter_name": rec.get("batter_name"),
                "pitcher_name": rec.get("pitcher_name"),
                "ev90": rec.get("ev90"),
                "hit_prob": rec.get("hit_prob"),
                "hr_prob": rec.get("hr_prob"),
                "tb2p_prob": rec.get("tb2p_prob"),
                "fair_hit_odds": rec.get("fair_hit_odds"),
                "fair_hr_odds": rec.get("fair_hr_odds"),
                "fair_tb2p_odds": rec.get("fair_tb2p_odds"),
                "book_hit_odds": rec.get("book_hit_odds"),
                "book_hr_odds": rec.get("book_hr_odds"),
                "book_tb2p_odds": rec.get("book_tb2p_odds"),
                "hit_edge": rec.get("hit_edge"),
                "hr_edge": rec.get("hr_edge"),
                "tb2p_edge": rec.get("tb2p_edge"),
                "adjusted_edge": rec.get("adjusted_edge"),
                "hit_bet_ev": rec.get("hit_bet_ev"),
                "hr_bet_ev": rec.get("hr_bet_ev"),
                "tb2p_bet_ev": rec.get("tb2p_bet_ev"),
                "confidence": rec.get("confidence"),
                "confidence_bucket": rec.get("confidence_bucket"),
                "recommendation_tier": rec.get("recommendation_tier"),
                "priority_score": rec.get("priority_score"),
                "reason_tags": " | ".join(rec.get("reason_tags", []) or []),
                "starter_stays_next_batter_prob": rec.get("starter_stays_next_batter_prob"),
                "starter_stays_next_inning_prob": rec.get("starter_stays_next_inning_prob"),
                "bullpen_entry_prob": rec.get("bullpen_entry_prob"),
                "xgb_hr_delta":      rec.get("xgb_hr_delta"),
                "xgb_hr_adjusted":   rec.get("xgb_hr_adjusted"),
                "xgb_shadow_active": rec.get("xgb_shadow_active", False),
                "lineup_slot": _SLOT_LINEUP.get(rec.get("slot", ""), rec.get("slot")),
            }
        )

    return pd.DataFrame(rows)

def build_recommendation_outcome_rows(
    game_row: dict[str, Any],
    graded_at: str,
) -> pd.DataFrame:
    """
    Placeholder outcome scaffold.
    Realized fields are left null until a later grading source is connected.
    """
    away_team = str(game_row.get("away_team", "") or "").strip()
    home_team = str(game_row.get("home_team", "") or "").strip()
    game_pk = str(game_row.get("game_pk", "") or "").strip()

    rows = []

    for slot_key, slot_label in [
        ("on_deck_name", "On Deck"),
        ("in_hole_name", "In Hole"),
        ("three_away_name", "3 Away"),
    ]:
        batter_name = str(game_row.get(slot_key, "") or "").strip()
        if not batter_name:
            continue

        rows.append(
            {
                "created_at": None,
                "game_pk": game_pk,
                "away_team": away_team,
                "home_team": home_team,
                "batter_name": batter_name,
                "slot": slot_label,
                "market": "hr",
                "realized_hit": None,
                "realized_hr": None,
                "realized_tb2p": None,
                "graded_at": graded_at,
                "outcome_source": "placeholder",
                "lineup_slot": slot_key.replace("_name", ""),
            }
        )

    return pd.DataFrame(rows)