"""Takes the full list of requests, and prepares the parameter list."""
from sys import stdout

import config  # noqa

from concurrency.mapper import map_processes
import util.db_utils as db_utils
from util.logic_utils import slice_off_request_code

from constants.database import RELEASE_LOG_TABLE
from integration_scripts import logger as log
from integration_scripts.connectors import sentry


def _generate_process_params(label_id, label_request_list, session_id):
    """Generate a list of parameters to be fed to the multiprocessor."""
    # full_response_dict = dict()
    multiprocess_param_list = list()

    # Transform label data to requests.
    if len(label_request_list):
        for num, label_request in enumerate(label_request_list, start=1):
            # Assemble curl / requests
            if len(label_request) and 'data' in label_request:
                multiprocess_param_list.append(
                    (num,  # Process number
                     session_id,  # Session_id for entire run
                     'Request #{} for label {}'.format(  # Process Name (msg)
                         num, label_id),
                     label_request,  # Request body
                     label_id  # Label ID tied to request
                     ))
    else:
        params = dict()
        params['action_type'] = 'skipped'
        params['session_id'] = session_id
        params['orchard_vendor_id'] = label_id
        params['request'] = 'NO DATA'
        params['response'] = 'NO DATA'

        params['log_table'] = RELEASE_LOG_TABLE.upper()

        # comprehension to slice off request_code
        params = slice_off_request_code(params)

        db_utils.insert_mysql_release_log(**params)

        log.info('Skipping {}. No data.'.format(label_id))

    return multiprocess_param_list


@sentry.sentry_wrap
def multiprocess_requests(label_id, label_request_list, session_id, file_name):
    """Create queues and workers to process a label with multiple threads."""

    log.info(
        'Map Multiprocessing beginning for label {} in file {}.'.format(
            label_id, file_name))

    # Initialize the parameters for the list of processes
    multiprocess_param_list = _generate_process_params(
        label_id, label_request_list, session_id)

    # Load the Queues
    results, results_again, failed_again, counts = \
        map_processes(multiprocess_param_list)

    log.info('Map Multiprocessing complete for label {}.'.format(label_id))

    stdout.flush()

    return results, results_again, failed_again, counts