"""Dms delivery spec model."""

import sqlalchemy

from src.connectors import direct_delivery
from src.constants import fields
from src.models import sql_queries


def get_dms_delivery_spec_bulk(order_types_store_ids):
    """Get dms_delivery_spec fields values by (store_id, order_type) pairs.

    Args:
        order_types_store_ids (iterable): Pairs of integers as an iterable:
            (vector order type, store_id). Example:
            [('ringtone', 1), ('release', 286)]

    Returns:
        dict: A two-level dict with (order_type, store_id) tuple as a key
        and a subset records as nested dicts. Example:
        {
            ('ringtone', 1): {'encoding': 'N', 'delivery': 'N'},
            ('release', 286): {'encoding': 'Y', 'delivery': 'N'},
        }

    """
    # There are just about 550 possible records (as of 2018) in this table but
    # we can receive an input just for a few records, so we're simply
    # concatenating all the conditions. This works well for up to 8K items.
    # Another option could be just always returning all the table records.
    conditions = []
    for order_type, store_id in order_types_store_ids:
        conditions.append(
            sql_queries.DD_SELECT_DDS_BULK_CONDITION_TEMPLATE.format(
                order_type=order_type, store_id=store_id))
    if not conditions:
        return {}

    query_conditions = '\nOR'.join(conditions)
    query = '{} {}'.format(
        sql_queries.DD_SELECT_DDS_BULK_NO_CONDITION, query_conditions)

    result_dict = {}
    with direct_delivery.session_scope() as session:
        result = session.execute(sqlalchemy.text(query))
        key_fields = (fields.ORDER_TYPE, fields.DMS_MASTER_MASTER_ID)
        for row in result.mappings().all():
            row_dict = dict(row)
            key = tuple(row_dict[f] for f in key_fields)
            # Remove fields that form the key.
            for f in key_fields:
                del row_dict[f]
            result_dict[key] = row_dict

    return result_dict