Initial temporal client
An initial attempt at defining a temporal workflow client that
can be used from any module
Change-Id: I6095793617acbc7bd2438a28c07eb1d854f3ff1c
Signed-off-by: Mark Beierl <mark.beierl@canonical.com>
diff --git a/osm_common/wftemporal.py b/osm_common/wftemporal.py
new file mode 100644
index 0000000..0f7d421
--- /dev/null
+++ b/osm_common/wftemporal.py
@@ -0,0 +1,67 @@
+#######################################################################################
+# Copyright ETSI Contributors and Others.
+#
+# 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.
+#######################################################################################
+
+import logging
+import uuid
+
+from temporalio.client import Client
+
+
+class WFTemporal(object):
+ clients = {}
+
+ def __init__(self, temporal_api=None, logger_name="temporal.client"):
+ self.logger = logging.getLogger(logger_name)
+ self.temporal_api = temporal_api
+
+ async def execute_workflow(
+ self, task_queue: str, workflow_name: str, workflow_data: any, id: str = None
+ ):
+ handle = await self.start_workflow(
+ task_queue=task_queue,
+ workflow_name=workflow_name,
+ workflow_data=workflow_data,
+ id=id,
+ )
+ result = await handle.result()
+ self.logger.info(f"Completed workflow {workflow_name}, id {id}")
+ return result
+
+ async def start_workflow(
+ self, task_queue: str, workflow_name: str, workflow_data: any, id: str = None
+ ):
+ client = await self.get_client()
+ if id is None:
+ id = str(uuid.uuid4())
+ self.logger.info(f"Starting workflow {workflow_name}, id {id}")
+ handle = await client.start_workflow(
+ workflow=workflow_name, arg=workflow_data, id=id, task_queue=task_queue
+ )
+ return handle
+
+ async def get_client(self):
+ if self.temporal_api in WFTemporal.clients:
+ client = WFTemporal.clients[self.temporal_api]
+ else:
+ self.logger.debug(
+ f"No cached client found, connecting to {self.temporal_api}"
+ )
+ client = await Client.connect(self.temporal_api)
+ WFTemporal.clients[self.temporal_api] = client
+
+ self.logger.debug(f"Using client {client} for {self.temporal_api}")
+ return client