#
# 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

from .constant import CHECKPOINT, SIGNAL_CLOSE


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

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

    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)

    def append_to_queue(self, type, documents):
        """Append documents to the shared queue
        :param type: Type of documents
        :param documents: Documents fetched from sharepoint
        """
        if documents:
            documents_map = {"type": type, "data": documents}
            self.logger.debug(
                f"Added list of {len(documents)} documents into the queue"
            )
            self.put(documents_map)