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# Copyright 2021-2023 H2020 TeraFlow (https://www.teraflow-h2020.eu/)
#
# 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.
Carlos Natalino Da Silva
committed
from email.policy import default
from common.Settings import get_log_level, get_setting
from common.tools.client.RetryDecorator import retry, delay_exponential
Carlos Natalino Da Silva
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from common.proto.dbscanserving_pb2 import DetectionRequest, DetectionResponse
from common.proto.dbscanserving_pb2_grpc import DetectorStub
log_level = get_log_level()
logging.basicConfig(level=log_level)
LOGGER = logging.getLogger(__name__)
MAX_RETRIES = 15
DELAY_FUNCTION = delay_exponential(initial=0.01, increment=2.0, maximum=5.0)
RETRY_DECORATOR = retry(max_retries=MAX_RETRIES, delay_function=DELAY_FUNCTION, prepare_method_name='connect')
class DbscanServingClient:
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def __init__(self, host=None, port=None):
if not host: host = get_setting('DBSCANSERVINGSERVICE_SERVICE_HOST')
if not port: port = get_setting('DBSCANSERVINGSERVICE_SERVICE_PORT_GRPC')
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self.endpoint = '{:s}:{:s}'.format(str(host), str(port))
LOGGER.debug('Creating channel to {:s}...'.format(str(self.endpoint)))
self.channel = None
self.stub = None
self.connect()
LOGGER.debug('Channel created')
def connect(self):
self.channel = grpc.insecure_channel(self.endpoint)
self.stub = DetectorStub(self.channel)
def close(self):
if(self.channel is not None): self.channel.close()
self.channel = None
self.stub = None
def Detect(self, request : DetectionRequest) -> DetectionResponse:
LOGGER.debug('Detect request with {} samples and {} features'.format(
request.num_samples,
request.num_features
))
response = self.stub.Detect(request)
LOGGER.debug('Detect result with {} cluster indices'.format(len(response.cluster_indices)))