Celery docs and debug (#1328)

* added script to import process instance and updated some docs for redis and celery w/ burnettk

* pyl and removed bad gitignore w/ burnettk

---------

Co-authored-by: jasquat <jasquat@users.noreply.github.com>

docs/DevOps_installation_integration/redis_celery_broker.md

@@ -0,0 +1,41 @@
+# Redis Celery Broker
+
+SpiffWorkflow can be configured to use celery for efficient processing.
+Redis can be used as both a broker and backend for celery.
+
+If configured in this way, there will be a queue called "celery" and you can inspect it from redis-cli like this:
+
+```sh
+redis-cli LLEN celery # how many queued entries
+redis-cli LRANGE celery 0 -1 # get all queued entries. Be careful if you have a lot.
+```
+
+If you want to purge all entries from the queue:
+
+```sh
+poetry run celery -A src.spiffworkflow_backend.background_processing.celery_worker purge
+```
+
+If you want to inspect jobs that are currently being processed by workers:
+
+```sh
+poetry run celery -A src.spiffworkflow_backend.background_processing.celery_worker inspect active
+```
+
+When we publish a message to the queue, we log a message like this at the log level info:
+
+```sh
+Queueing process instance (3) for celery (9622ff55-9f23-4a94-b4a0-4e0a615a8d14)
+```
+
+If you want to get the results of this job after the worker processes it, you would run a query like this:
+
+```sh
+redis-cli get celery-task-meta-9622ff55-9f23-4a94-b4a0-4e0a615a8d14
+```
+
+As such, if you wanted to get ALL of the results, you could use a hilarious command like:
+
+```sh
+echo 'keys celery-task-meta-\*' | redis-cli | sed 's/^/get /' | redis-cli
+```

docs/index.md

@@ -6,7 +6,6 @@
 Getting_Started/quick_start.md
 ```
 
-
 ```{toctree}
 :maxdepth: 1
 :caption: Building Diagrams
@@ -48,6 +47,7 @@ DevOps_installation_integration/permission_url.md
 DevOps_installation_integration/configure_connector_proxy.md
 DevOps_installation_integration/deploy_aws_lambda.md
 DevOps_installation_integration/Secrets.md
+DevOps_installation_integration/redis_celery_broker.md
 ```
 
 ```{toctree}
@@ -71,6 +71,6 @@ wish_list/wish_list.md
 
 ## Indices and tables
 
-* [](genindex)
-* [](modindex)
-* [](search)
+- [](genindex)
+- [](modindex)
+- [](search)

spiffworkflow-backend/bin/import_process_instance_from_bpmn_json.py

@@ -0,0 +1,28 @@
+import json
+import sys
+
+from spiffworkflow_backend import create_app
+from spiffworkflow_backend.services.process_instance_processor import ProcessInstanceProcessor
+from spiffworkflow_backend.services.process_instance_service import ProcessInstanceService
+from spiffworkflow_backend.services.process_model_service import ProcessModelService
+from spiffworkflow_backend.services.user_service import UserService
+
+
+def main(process_model_identifier: str, filepath: str) -> None:
+    app = create_app()
+    with app.app_context():
+        user = UserService.find_or_create_system_user()
+        process_model = ProcessModelService.get_process_model(process_model_identifier.replace(":", "/"))
+        process_instance, _ = ProcessInstanceService.create_process_instance(process_model, user)
+        with open(filepath) as f:
+            bpmn_process_json = f.read()
+        bpmn_process_dict = json.loads(bpmn_process_json)
+        ProcessInstanceProcessor.persist_bpmn_process_dict(
+            bpmn_process_dict, bpmn_definition_to_task_definitions_mappings={}, process_instance_model=process_instance
+        )
+
+
+if len(sys.argv) < 3:
+    raise Exception("usage: [script] [process_model_identifier] [bpmn_json_file_path]")
+
+main(sys.argv[1], sys.argv[2])

spiffworkflow-backend/src/spiffworkflow_backend/background_processing/celery_tasks/process_instance_task.py

@@ -36,6 +36,9 @@ def celery_task_process_instance_run(process_instance_id: int, task_guid: str |
                 execution_strategy_name="queue_instructions_for_end_user",
                 additional_processing_identifier=proc_index,
             )
+            # currently, whenever we get a task_guid, that means that that task, which was a future task, is ready to run.
+            # there is an assumption that it was successfully processed by run_process_instance_with_processor above.
+            # we might want to check that assumption.
             if task_guid is not None:
                 future_task = FutureTaskModel.query.filter_by(completed=False, guid=task_guid).first()
                 if future_task is not None:

spiffworkflow-backend/src/spiffworkflow_backend/background_processing/celery_tasks/process_instance_task_producer.py

@@ -49,7 +49,8 @@ def queue_future_task_if_appropriate(process_instance: ProcessInstanceModel, eta
         # (maybe due to subsecond stuff, maybe because of clock skew within the cluster of computers running spiff)
         # celery_task_process_instance_run.apply_async(kwargs=args_to_celery, countdown=countdown + 1)  # type: ignore
 
-        celery.current_app.send_task(CELERY_TASK_PROCESS_INSTANCE_RUN, kwargs=args_to_celery, countdown=countdown)
+        async_result = celery.current_app.send_task(CELERY_TASK_PROCESS_INSTANCE_RUN, kwargs=args_to_celery, countdown=countdown)
+        current_app.logger.info(f"Queueing process instance ({process_instance.id}) for celery ({async_result.task_id})")
         return True
 
     return False
@@ -70,6 +71,7 @@ def queue_process_instance_if_appropriate(process_instance: ProcessInstanceModel
     #     )
 
     if should_queue_process_instance(process_instance, execution_mode):
-        celery.current_app.send_task(CELERY_TASK_PROCESS_INSTANCE_RUN, (process_instance.id,))
+        async_result = celery.current_app.send_task(CELERY_TASK_PROCESS_INSTANCE_RUN, (process_instance.id,))
+        current_app.logger.info(f"Queueing process instance ({process_instance.id}) for celery ({async_result.task_id})")
         return True
     return False

spiffworkflow-backend/src/spiffworkflow_backend/routes/process_api_blueprint.py

@@ -21,6 +21,9 @@ from sqlalchemy import or_
 from spiffworkflow_backend.background_processing.celery_tasks.process_instance_task_producer import (
     queue_enabled_for_process_model,
 )
+from spiffworkflow_backend.background_processing.celery_tasks.process_instance_task_producer import (
+    queue_process_instance_if_appropriate,
+)
 from spiffworkflow_backend.data_migrations.process_instance_migrator import ProcessInstanceMigrator
 from spiffworkflow_backend.exceptions.api_error import ApiError
 from spiffworkflow_backend.exceptions.error import HumanTaskAlreadyCompletedError
@@ -487,6 +490,7 @@ def _task_submit_shared(
     )
 
     with sentry_sdk.start_span(op="task", description="complete_form_task"):
+        with ProcessInstanceQueueService.dequeued(processor.process_instance_model, max_attempts=3):
             ProcessInstanceService.complete_form_task(
                 processor=processor,
                 spiff_task=spiff_task,
@@ -495,6 +499,7 @@ def _task_submit_shared(
                 human_task=human_task,
                 execution_mode=execution_mode,
             )
+        queue_process_instance_if_appropriate(process_instance, execution_mode)
 
     # currently task_model has the potential to be None. This should be removable once
     # we backfill the human_task table for task_guid and make that column not nullable

spiffworkflow-backend/src/spiffworkflow_backend/services/process_instance_service.py

@@ -19,9 +19,7 @@ from SpiffWorkflow.task import Task as SpiffTask  # type: ignore
 from SpiffWorkflow.util.deep_merge import DeepMerge  # type: ignore
 from SpiffWorkflow.util.task import TaskState  # type: ignore
 
-from spiffworkflow_backend.background_processing.celery_tasks.process_instance_task_producer import (
-    queue_process_instance_if_appropriate,
-)
+from spiffworkflow_backend.background_processing.celery_tasks.process_instance_task_producer import should_queue_process_instance
 from spiffworkflow_backend.data_migrations.process_instance_migrator import ProcessInstanceMigrator
 from spiffworkflow_backend.exceptions.api_error import ApiError
 from spiffworkflow_backend.exceptions.error import HumanTaskAlreadyCompletedError
@@ -477,14 +475,11 @@ class ProcessInstanceService:
         Abstracted here because we need to do it multiple times when completing all tasks in
         a multi-instance task.
         """
-        with ProcessInstanceQueueService.dequeued(processor.process_instance_model, max_attempts=3):
         ProcessInstanceService.update_form_task_data(processor.process_instance_model, spiff_task, data, user)
         processor.complete_task(spiff_task, human_task, user=user)
 
-        if queue_process_instance_if_appropriate(processor.process_instance_model, execution_mode):
-            return
-        else:
-            with ProcessInstanceQueueService.dequeued(processor.process_instance_model, max_attempts=3):
+        # the caller needs to handle the actual queueing of the process instance for better dequeueing ability
+        if not should_queue_process_instance(processor.process_instance_model, execution_mode):
             if not ProcessInstanceQueueService.is_enqueued_to_run_in_the_future(processor.process_instance_model):
                 with sentry_sdk.start_span(op="task", description="backend_do_engine_steps"):
                     execution_strategy_name = None