from __future__ import annotations

from typing import Any
import pandas as pd

from models.batter_zone_store import load_batter_zone_store_metrics

PITCH_FAMILY_MAP = {
    "4-seam fastball": "fastball",
    "four-seam fastball": "fastball",
    "fastball": "fastball",
    "sinker": "fastball",
    "cutter": "fastball",
    "slider": "breaking",
    "sweeper": "breaking",
    "curveball": "breaking",
    "knuckle curve": "breaking",
    "slurve": "breaking",
    "changeup": "offspeed",
    "splitter": "offspeed",
    "forkball": "offspeed",
    "split-finger": "offspeed",
    "circle change": "offspeed",
}


def normalize_pitch_family(pitch_name: Any) -> str:
    text = str(pitch_name or "").strip().lower()
    if text in {"", "nan", "none"}:
        return "unknown"
    return PITCH_FAMILY_MAP.get(text, "unknown")


def classify_zone_bucket(plate_x: Any, plate_z: Any) -> str:
    try:
        x = float(plate_x)
        z = float(plate_z)
    except Exception:
        return "unknown"

    zone_left = -0.83
    zone_right = 0.83
    zone_bottom = 1.50
    zone_top = 3.50

    if zone_left <= x <= zone_right and zone_bottom <= z <= zone_top:
        inner_left = -0.45
        inner_right = 0.45
        inner_bottom = 1.90
        inner_top = 3.10

        if inner_left <= x <= inner_right and inner_bottom <= z <= inner_top:
            return "heart"
        return "shadow"

    chase_left = -1.20
    chase_right = 1.20
    chase_bottom = 1.10
    chase_top = 3.90

    if chase_left <= x <= chase_right and chase_bottom <= z <= chase_top:
        return "chase"

    return "waste"

def build_batter_zone_feature_row(
    statcast_df: pd.DataFrame,
    player_name: str,
) -> dict[str, Any]:

    store_metrics = load_batter_zone_store_metrics(player_name)

    row: dict[str, Any] = {
        "player_name": player_name,
        "zone_sample_size": store_metrics.get("stored_zone_sample_size", 0),
    }

    pitch_families = ["fastball", "breaking", "offspeed"]
    zones = ["heart", "shadow", "chase", "waste"]

    for family in pitch_families:
        for zone in zones:

            row[f"hr_prob_{family}_{zone}"] = store_metrics.get(
                f"stored_hr_prob_{family}_{zone}"
            )

            row[f"hit_prob_{family}_{zone}"] = store_metrics.get(
                f"stored_hit_prob_{family}_{zone}"
            )

            row[f"tb2p_prob_{family}_{zone}"] = store_metrics.get(
                f"stored_tb2p_prob_{family}_{zone}"
            )

            row[f"whiff_prob_{family}_{zone}"] = store_metrics.get(
                f"stored_whiff_prob_{family}_{zone}"
            )

            row[f"damage_prob_{family}_{zone}"] = store_metrics.get(
                f"stored_damage_prob_{family}_{zone}"
            )

            row[f"sample_size_{family}_{zone}"] = store_metrics.get(
                f"stored_sample_size_{family}_{zone}"
            )

    return row