import aiomysql, decimal, datetime
import asyncio
from typing import Literal, Any
from data.schemas import Connection, SelectResultData

# Database configuration
DB_CONFIG = {
    "host": "localhost",
    "user": "me",  # Replace with your MySQL username
    "password": "Passwd3.14",  # Replace with your MySQL password
    "db": "testing",  # Replace with your database name
    "port": 3306,  # Default MySQL port
}

pools: None | dict[str, aiomysql.Pool] = {}


async def pool_creator(connection: Connection, minsize=5, maxsize=10):

    return await aiomysql.create_pool(
        # **DB_CONFIG,
        host=connection.host,
        user=connection.username,
        password=connection.password,
        db=connection.db_name,
        port=connection.port,
        minsize=minsize,
        maxsize=maxsize,
    )


async def execute_select_query(pool: aiomysql.Pool, query: str, params: list, fetch_num:int = 100):
    """
    Executes a SELECT query on the MySQL database asynchronously and returns the results.

    Args:
        pool (aiomysql.Pool): Connection pool to use.
        query (str): The SELECT query to execute.

    Returns:
        list: A list of rows (as dictionaries) returned by the query.
    """
    try:
        async with pool.acquire() as connection:
            async with connection.cursor(aiomysql.DictCursor) as cursor:
                await cursor.execute(query, params)
                result = await cursor.fetchmany(fetch_num)

        return result, cursor.rowcount

    except Exception as e:
        print(f"Error executing query: {e}")
        return []


def construct_select_query(
    table_name,
    columns: Literal["*"] | list[str] = "*",
    filters=None,
    sort_by=None,
    limit=None,
    offset=None,
):
    """
    Constructs a dynamic SELECT query based on the provided parameters.

    Args:
        table_name (str): The name of the table to query.
        columns (str or list): The columns to select. Default is "*" (all columns).
        filters (dict): A dictionary of filters (e.g., {"column": "value"}).
        sort_by (str): The column to sort by (e.g., "column_name ASC").
        limit (int): The maximum number of rows to return.
        offset (int): The number of rows to skip (for pagination).

    Returns:
        str: The constructed SELECT query.
    """
    # Handle columns
    if isinstance(columns, list):
        columns = ", ".join(columns)
    elif columns != "*":
        raise ValueError("Columns must be a list or '*'.")

    # Base query
    query = f"SELECT {columns}\n    FROM {table_name}"

    # Add filters
    if filters:
        filter_conditions = [
            f"{column} = '{value}'" for column, value in filters.items()
        ]
        query += "\n    WHERE " + " AND ".join(filter_conditions)

    # Add sorting
    if sort_by:
        query += f"\n    ORDER BY {sort_by}"

    # Add pagination
    if limit is not None:
        query += f"\n    LIMIT {limit}"
        if offset is not None:
            query += f"\n    OFFSET {offset}"

    return query


async def get_tables_and_datatypes(pool: aiomysql.Pool):
    """
    Retrieves all table names and their column data types from a MySQL database.

    Args:
        db_config (dict): MySQL database configuration (host, user, password, db, port).

    Returns:
        dict: A dictionary where keys are table names and values are lists of (column_name, data_type) tuples.
    """
    try:
        # Connect to the MySQL database
        # connection = await aiomysql.connect(**db_config)
        async with pool.acquire() as connection:
            async with connection.cursor() as cursor:
                # Get all table names
                await cursor.execute("SHOW TABLES")
                tables = await cursor.fetchall()

                result = {}
                for table in tables:
                    table_name = table[0]
                    result[table_name] = {}

                    # Get column names and data types for the current table
                    await cursor.execute(f"DESCRIBE {table_name}")
                    columns = await cursor.fetchall()
                    # Store column names and data types
                    for col in columns:
                        result[table_name][col[0]] = col[1]

        # Close the connection
        # connection.close()
        # await connection.wait_closed()

        return result
    except Exception as e:
        print(f"Error: {e}")
        return {}


def serializer(raw_result: list[dict[str, Any]]):
    serialized = []
    while raw_result:
        re = raw_result.pop()
        serialized_re = {}
        for key, value in re.items():
            if isinstance(value, str | int | None | float):
                serialized_re[key] = str(value)
            elif isinstance(value, decimal.Decimal):
                serialized_re[key] = float(value)
            elif isinstance(value, datetime.date):
                serialized_re[key] = value.strftime("%Y-%m-%d")
            else:
                serialized_re[key] = str(value)
                print(key, type(value))

        serialized.append(serialized_re)
    return serialized


def dict_result_to_list(result: list[dict[str, Any]]) -> None | SelectResultData:
    if len(result) == 0:
        return None

    columns = list(result[0].keys())
    data = []
    for row in result:
        data.append(list(row.values()))

    return SelectResultData(columns=columns, data=data)