import struct

# 裝置設定檔：型號 → 資料型態、位元組順序、換算比例
DEVICE_PROFILES = {
    "STT": {"dtype": "float32_cdab", "scale": 1.0},
    "DTT-P4": {"dtype": "int16_signed", "scale": 10.0},
    "SDPT-3100": {"dtype": "float32_abcd", "scale": 1.0},
    "THT-S81": {"dtype": "uint16", "scale": 10.0},
}

def parse_by_profile(device_model: str, raw_hex: str):
    profile = DEVICE_PROFILES.get(device_model)
    if not profile:
        raise ValueError(f"未知裝置型號：{device_model}")

    raw_bytes = bytes.fromhex(raw_hex)
    dtype = profile["dtype"]

    if dtype == "float32_cdab":
        reordered = raw_bytes[2:4] + raw_bytes[0:2]
        value = struct.unpack('>f', reordered)[0]
    elif dtype == "float32_abcd":
        value = struct.unpack('>f', raw_bytes)[0]
    elif dtype == "int16_signed":
        raw_int = struct.unpack('>h', raw_bytes[:2])[0]
        value = raw_int / profile["scale"]
    elif dtype == "uint16":
        raw_int = struct.unpack('>H', raw_bytes[:2])[0]
        value = raw_int / profile["scale"]
    else:
        raise ValueError(f"不支援的資料型態：{dtype}")

    return round(value, 2)

def lambda_handler(event, context):
    device_model = event.get("device_model")
    raw_hex = event.get("raw_hex")

    try:
        parsed_value = parse_by_profile(device_model, raw_hex)
        print(f"型號 {device_model} 解析結果：{parsed_value}")
        return {"statusCode": 200, "parsed_value": parsed_value}
    except ValueError as e:
        print(f"解析失敗：{e}")
        return {"statusCode": 500, "error": str(e)}