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path: root/python-discovery-client/discovery_client/__init__.py
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# org.onap.dcae
# ================================================================================
# Copyright (c) 2017 AT&T Intellectual Property. All rights reserved.
# ================================================================================
# 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.
# ============LICENSE_END=========================================================
#
# ECOMP is a trademark and service mark of AT&T Intellectual Property.

from .discovery import get_service_name, get_configuration, \
    register_for_discovery, resolve_name
v class="highlight">
{
  "name": "de4f04e3-0a65-470b-9d07-8ea6c2fb3e10",
  "files": {},
  "timeout": 1200,
  "num_solution": "100",
  "template": {
    "homing_template_version": "2017-10-10",
    "parameters": {
      "REQUIRED_MEM": "",
      "REQUIRED_DISK": "",
      "customer_lat": 1.1,
      "customer_long": 2.2,
      "service_name": "vFW_TD",
      "service_id": "3e8d118c-10ca-4b4b-b3db-089b5e9e6a1c",
      "chosen_region": "RegionOne"
    },
    "locations": {
      "customer_loc": {
        "latitude": {
          "get_param": "customer_lat"
        },
        "longitude": {
          "get_param": "customer_long"
        }
      }
    },
    "demands": {
      "vFW-SINK": [
        {
          "inventory_provider": "aai",
          "inventory_type": "vfmodule",
          "service_type": "vFW-SINK-XX",
          "service_resource_id": "vFW-SINK-XX",
          "filtering_attributes": {
            "global-customer-id": {
              "get_param": "chosen_customer_id"
            },
            "model-invariant-id": "e7227847-dea6-4374-abca-4561b070fe7d",
            "model-version-id": "763731df-84fd-494b-b824-01fc59a5ff2d",
            "orchestration-status": [
              "active"
            ],
            "prov-status": "ACTIVE",
            "cloud-region-id": {
              "get_param": "chosen_region"
            },
            "service_instance_id": {
              "get_param": "service_id"
            }
          },
          "passthrough_attributes": {
            "td-role": "destination"
          },
          "excluded_candidates": [
            {
              "inventory_type": "vfmodule",
              "candidate_id": [
                "e765d576-8755-4145-8536-0bb6d9b1dc9a"
              ]
            }
          ]
        }
      ],
      "vPGN": [
        {
          "inventory_provider": "aai",
          "inventory_type": "vfmodule",
          "service_type": "vPGN-XX",
          "service_resource_id": "vPGN-XX",
          "unique": "False",
          "filtering_attributes": {
            "global-customer-id": {
              "get_param": "chosen_customer_id"
            },
            "model-invariant-id": "762472ef-5284-4daa-ab32-3e7bee2ec355",
            "model-version-id": "e02a7e5c-9d27-4360-ab7c-73bb83b07e3b",
            "orchestration-status": [
              "active"
            ],
            "prov-status": "ACTIVE",
            "cloud-region-id": {
              "get_param": "chosen_region"
            },
            "service_instance_id": {
              "get_param": "service_id"
            }
          },
          "passthrough_attributes": {
            "td-role": "anchor"
          }
        }
      ]
    },
    "constraints": {
      "affinity_vFW_TD": {
        "type": "zone",
        "demands": [
          "vFW-SINK",
          "vPGN"
        ],
        "properties": {
          "category": "region",
          "qualifier": "same"
        }
      }
    },
    "optimization": {
      "minimize": {
        "sum": []
      }
    }
  }
}