89 lines
2.7 KiB
Python
89 lines
2.7 KiB
Python
# Copyright 2016 AT&T Corp
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# All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import random
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from oslo_log import log as logging
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from tempest import config
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from tempest.lib.common.utils import data_utils
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LOG = logging.getLogger(__name__)
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CONF = config.CONF
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def rand_region_status(exclude=[]):
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statuses = {'functional', 'maintenance', 'down', 'building'}.difference(
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exclude)
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return random.choice(list(statuses))
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def rand_region_metadata():
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metadata = {}
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for i in range(random.randint(2, 10)):
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metadata[data_utils.rand_name()] = [data_utils.arbitrary_string()]
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return metadata
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def rand_region(id=None):
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if id is None:
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id = data_utils.rand_name()
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region_dict = {
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'status': rand_region_status(),
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'id': id,
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'name': id,
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'designType': data_utils.arbitrary_string(),
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'locationType': data_utils.arbitrary_string(),
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'vlcpName': data_utils.arbitrary_string(),
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'description': data_utils.arbitrary_string(),
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'rangerAgentVersion': data_utils.arbitrary_string(),
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'OSVersion': data_utils.arbitrary_string(),
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'CLLI': data_utils.arbitrary_string(),
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'address': {
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'country': data_utils.arbitrary_string(),
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'state': data_utils.arbitrary_string(),
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'city': data_utils.arbitrary_string(),
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'street': data_utils.arbitrary_string(),
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'zip': str(data_utils.rand_int_id(start=10000, end=99999))
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},
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'metadata': {
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data_utils.rand_name(): [data_utils.arbitrary_string()],
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data_utils.rand_name(): [data_utils.arbitrary_string()]
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},
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'endpoints': [{
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'publicURL': data_utils.rand_url(),
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'type': 'dashboard'
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}, {
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'publicURL': data_utils.rand_url(),
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'type': 'identity'
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}, {
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'publicURL': data_utils.rand_url(),
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'type': 'ord'
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}]
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}
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return region_dict
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def rand_region_group(region_ids, id=None):
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if id is None:
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id = data_utils.rand_name()
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group_dict = {
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'name': id,
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'id': id,
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'description': data_utils.arbitrary_string(),
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'regions': region_ids
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}
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return group_dict
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