from __future__ import annotations

import sqlite3
from typing import Dict, List, cast
import pandas as pd


def load_sqlite_to_dataframe(db_path:str, query:str) -> pd.DataFrame:
    df: pd.DataFrame = pd.DataFrame()
    import os
    if not os.path.exists(db_path):
        print(f"WARNING: database file {db_path} does not exist")
        return df

    try:
        conn = sqlite3.connect(db_path)

        df = pd.read_sql_query(query, conn)
        return df
    except sqlite3.Error as excpt:
        print(f"SQLite error: {excpt}")
        raise
    except Exception as excpt:
        print(f"Error: {excpt}")
        raise Exception() from excpt
    finally:
        if "conn" in locals():
            conn.close()


def convert_time_to_UTC(value: str, timezone: str, extra_minutes: int = 0) -> str:

    from zoneinfo import ZoneInfo
    from datetime import datetime, timedelta

    # Parse it to naive datetime object
    local_dt = datetime.strptime(value, "%Y-%m-%d %H:%M:%S")
    local_dt = local_dt + timedelta(minutes=extra_minutes)

    zinfo = ZoneInfo(timezone)
    result: datetime = local_dt.replace(tzinfo=zinfo).astimezone(ZoneInfo("UTC"))

    return result.strftime("%Y-%m-%d %H:%M:%S")


def load_market_data(
    datafile: str,
    instruments: List[Dict[str, str]],
    db_table_name: str,
    trading_hours: Dict = {},
) -> pd.DataFrame:

    insts = [
        '"' + instrument["instrument_id_pfx"] + instrument["symbol"] + '"'
        for instrument in instruments
    ]
    instrument_ids = list(set(insts))
    exchange_ids = list(
        set(['"' + instrument["exchange_id"] + '"' for instrument in instruments])
    )

    query = "select"
    query += " tstamp"
    query += ", tstamp_ns as time_ns"

    query += f", substr(instrument_id, instr(instrument_id, '-') + 1) as symbol"
    query += ", open"
    query += ", high"
    query += ", low"
    query += ", close"
    query += ", volume"
    query += ", num_trades"
    query += ", vwap"

    query += f" from {db_table_name}"
    query += f" where exchange_id in ({','.join(exchange_ids)})"
    query += f" and instrument_id in ({','.join(instrument_ids)})"

    df = load_sqlite_to_dataframe(db_path=datafile, query=query)

    # Trading Hours
    if len(df) > 0 and len(trading_hours) > 0:
        date_str = df["tstamp"][0][0:10]

        start_time = convert_time_to_UTC(
            f"{date_str} {trading_hours['begin_session']}", trading_hours["timezone"]
        )
        end_time = convert_time_to_UTC(
            f"{date_str} {trading_hours['end_session']}", trading_hours["timezone"], extra_minutes=2 # to get execution price
        )

        # Perform boolean selection
        df = df[(df["tstamp"] >= start_time) & (df["tstamp"] <= end_time)]
        df["tstamp"] = pd.to_datetime(df["tstamp"])

    return cast(pd.DataFrame, df)


# def get_available_instruments_from_db(datafile: str, config: Dict) -> List[str]:
#     """
#     Auto-detect available instruments from the database by querying distinct instrument_id values.
#     Returns instruments without the configured prefix.
#     """
#     try:
#         conn = sqlite3.connect(datafile)

#         # Build exclusion list with full instrument_ids
#         exclude_instruments = config.get("exclude_instruments", [])
#         prefix = config.get("instrument_id_pfx", "")
#         exclude_instrument_ids = [f"{prefix}{inst}" for inst in exclude_instruments]

#         # Query to get distinct instrument_ids
#         query = f"""
#         SELECT DISTINCT instrument_id
#         FROM {config['db_table_name']}
#         WHERE exchange_id = ?
#         """

#         # Add exclusion clause if there are instruments to exclude
#         if exclude_instrument_ids:
#             placeholders = ",".join(["?" for _ in exclude_instrument_ids])
#             query += f" AND instrument_id NOT IN ({placeholders})"
#             cursor = conn.execute(
#                 query, (config["exchange_id"],) + tuple(exclude_instrument_ids)
#             )
#         else:
#             cursor = conn.execute(query, (config["exchange_id"],))
#         instrument_ids = [row[0] for row in cursor.fetchall()]
#         conn.close()

#         # Remove the configured prefix to get instrument symbols
#         instruments = []
#         for instrument_id in instrument_ids:
#             if instrument_id.startswith(prefix):
#                 symbol = instrument_id[len(prefix) :]
#                 instruments.append(symbol)
#             else:
#                 instruments.append(instrument_id)

#         return sorted(instruments)

#     except Exception as e:
#         print(f"Error auto-detecting instruments from {datafile}: {str(e)}")
#         return []


# if __name__ == "__main__":
#     df1 = load_sqlite_to_dataframe(sys.argv[1], table_name="md_1min_bars")

#     print(df1)