#
# Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
# or more contributor license agreements. Licensed under the Elastic License 2.0;
# you may not use this file except in compliance with the Elastic License 2.0.
#
import multiprocessing
from multiprocessing.queues import Queue

BATCH_SIZE = 100


class ConnectorQueue(Queue):
    """Class to support additional queue operations specific to the connector"""

    def __init__(self, logger):
        ctx = multiprocessing.get_context()
        self.logger = logger
        super(ConnectorQueue, self).__init__(ctx=ctx)

    def end_signal(self):
        """Send an terminate signal to indicate the queue can be closed"""

        signal_close = {"type": "signal_close"}
        self.put(signal_close)

    def put_checkpoint(self, key, checkpoint_time, indexing_type):
        """Put the checkpoint object in the queue which will be used by the consumer to update the checkpoint file

        :param key: The key of the checkpoint dictionary
        :param checkpoint_time: The end time that will be stored in the checkpoint as {'key': 'checkpoint_time'}
        :param indexing_type: The type of the indexing i.e. Full or Incremental
        """

        checkpoint = {
            "type": "checkpoint",
            "data": (key, checkpoint_time, indexing_type),
        }
        self.put(checkpoint)