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# -*- coding: utf-8 -*-
# Copyright 2014-2016 OpenMarket Ltd
# Copyright 2018,2019 New Vector Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
The storage layer is split up into multiple parts to allow Synapse to run
against different configurations of databases (e.g. single or multiple
databases). The `data_stores` are classes that talk directly to a single
database and have associated schemas, background updates, etc. On top of those
there are (or will be) classes that provide high level interfaces that combine
calls to multiple `data_stores`.

There are also schemas that get applied to every database, regardless of the
data stores associated with them (e.g. the schema version tables), which are
stored in `synapse.storage.schema`.
"""

from synapse.storage.data_stores import DataStores
from synapse.storage.data_stores.main import DataStore
from synapse.storage.persist_events import EventsPersistenceStorage

__all__ = ["DataStores", "DataStore"]


class Storage(object):
    """The high level interfaces for talking to various storage layers.
    """

    def __init__(self, hs, stores: DataStores):
        # We include the main data store here mainly so that we don't have to
        # rewrite all the existing code to split it into high vs low level
        # interfaces.
        self.main = stores.main

        self.persistence = EventsPersistenceStorage(hs, stores)


def are_all_users_on_domain(txn, database_engine, domain):
    sql = database_engine.convert_param_style(
        "SELECT COUNT(*) FROM users WHERE name NOT LIKE ?"
    )
    pat = "%:" + domain
    txn.execute(sql, (pat,))
    num_not_matching = txn.fetchall()[0][0]
    if num_not_matching == 0:
        return True
    return False