import traceback
from temporalio import workflow, activity

with workflow.unsafe.imports_passed_through():
    from sqlalchemy import create_engine
    from sqlalchemy.orm import sessionmaker
    from sqlalchemy.pool import QueuePool
    from pandas import DataFrame
    from logging import Logger
    from sientia_do.notifications.handlers import NotificationHandler
    from sientia_do.notifications.models import NotificationLevel
    from scouter.activities.base import BaseActivity
    from typing import Any


class Postgres(BaseActivity):
    def __init__(self, host: str, port: int,
                 user: str, password: str, dbname: str,
                 min_connections: int, max_connections: int,
                 logger: Logger, notification_handler: NotificationHandler):
        self.host = host
        self.port = port
        self.user = user
        self.password = password
        self.dbname = dbname

        # Create SQLAlchemy engine with connection pooling
        self.engine = create_engine(
            f'postgresql://{user}:{password}@{host}:{port}/{dbname}',
            poolclass=QueuePool,
            pool_size=min_connections,
            max_overflow=max_connections - min_connections,
            pool_pre_ping=True
        )
        self.session_factory = sessionmaker(bind=self.engine)

        BaseActivity.__init__(self, logger, notification_handler)

    def close(self):
        self.engine.dispose()

    def __del__(self):
        self.close()

    @activity.defn(name="export_data_to_postgres")
    async def export_data_to_postgres(self, input_data: dict[str, Any]):
        """
        Exports data to a postgres table.

        Args:
            input_data (dict[str, Any]): The data to export. Contains:
                schema (str): The schema of the table.
                table_name (str): The name of the table.
                data (DataFrame): The data to export.
        """

        self.logger.debug(
            f"Exporting data to postgres: {input_data['data']}")

        schema = input_data["schema"]
        table_name = input_data["table_name"]
        data = DataFrame(input_data["data"])

        with self.session_factory() as session:
            try:
                data.to_sql(table_name, self.engine, schema=schema,
                            if_exists="append", index=False)
                session.commit()

            except Exception as e:
                trace = traceback.format_exc()
                self.notification_handler.build_and_send_notification(
                    notification_id="ERROR_EXPORTING_DATA_TO_POSTGRES",
                    message=f"Error exporting data to postgres: {e}",
                    block="export_data_to_postgres",
                    level=NotificationLevel.ERROR,
                    attachment_content=trace
                )

                self.logger.error(trace)

            else:
                self.logger.debug("Data exported to postgres")
            finally:
                session.close()