Python framework for Cadence Workflow Service
Project description
Intro: Fault-Oblivious Stateful Python Code
cadence-python allows you to create Python functions that have their state (local variables etc..) implicitly saved such that if the process/machine fails the state of the function is not lost and can resume from where it left off.
This programming model is useful whenever you need to ensure that a function runs to completion. For example:
- Business logic involving multiple micro services
- CI/CD pipelines
- Data pipelines
- RPA
- ETL
- Marketing automation / Customer journeys / Customer engagement
- Zapier/IFTTT like end user automation.
- Chat bots
- Multi-step forms
- Scheduler/Cron jobs
Behind the scenes, cadence-python uses Cadence as its backend.
For more information about the fault-oblivious programming model refer to the Cadence documentation here
Install Cadencce
wget https://raw.githubusercontent.com/uber/cadence/master/docker/docker-compose.yml
docker-compose up
Register sample
domain
docker run --network=host --rm ubercadence/cli:master --do sample domain register -rd 1
Installation cadence-python
pip install cadence-client==1.0.1
Hello World Sample
import sys
import logging
from cadence.activity_method import activity_method
from cadence.workerfactory import WorkerFactory
from cadence.workflow import workflow_method, Workflow, WorkflowClient
logging.basicConfig(level=logging.DEBUG)
TASK_LIST = "HelloActivity-python-tasklist"
DOMAIN = "sample"
# Activities Interface
class GreetingActivities:
@activity_method(task_list=TASK_LIST, schedule_to_close_timeout_seconds=2)
def compose_greeting(self, greeting: str, name: str) -> str:
raise NotImplementedError
# Activities Implementation
class GreetingActivitiesImpl:
def compose_greeting(self, greeting: str, name: str):
return f"{greeting} {name}!"
# Workflow Interface
class GreetingWorkflow:
@workflow_method(execution_start_to_close_timeout_seconds=10, task_list=TASK_LIST)
async def get_greeting(self, name: str) -> str:
raise NotImplementedError
# Workflow Implementation
class GreetingWorkflowImpl(GreetingWorkflow):
def __init__(self):
self.greeting_activities: GreetingActivities = Workflow.new_activity_stub(GreetingActivities)
async def get_greeting(self, name):
# Place any Python code here that you want to ensure is executed to completion.
# Note: code in workflow functions must be deterministic so that the same code paths
# are ran during replay.
return await self.greeting_activities.compose_greeting("Hello", name)
if __name__ == '__main__':
factory = WorkerFactory("localhost", 7933, DOMAIN)
worker = factory.new_worker(TASK_LIST)
worker.register_activities_implementation(GreetingActivitiesImpl(), "GreetingActivities")
worker.register_workflow_implementation_type(GreetingWorkflowImpl)
factory.start()
client = WorkflowClient.new_client(domain=DOMAIN)
greeting_workflow: GreetingWorkflow = client.new_workflow_stub(GreetingWorkflow)
result = greeting_workflow.get_greeting("Python")
print(result)
print("Stopping workers....")
worker.stop()
print("Workers stopped...")
sys.exit(0)
Status / TODO
cadence-python is still under going heavy development. It should be considered EXPERIMENTAL at the moment. A production
version is targeted to be released in September of 2019 January 2020 March 2020 April 2020.
1.0
- Tchannel implementation
- Python-friendly wrapper around Cadence's Thrift API
- Author activities in Python
- Start workflows (synchronously)
- Create workflows
- Workflow execution in coroutines
- Invoke activities from workflows
- ActivityCompletionClient heartbeat, complete, complete_exceptionally
- Activity heartbeat, getHeartbeatDetails and doNotCompleteOnReturn
- Activity retry
- Activity getDomain(), getTaskToken(), getWorkflowExecution()
- Signals
- Queries
- Async workflow execution
- await
- now (currentTimeMillis)
- Sleep
- Loggers
- newRandom
- UUID
- Workflow Versioning
- WorkflowClient.newWorkflowStub(Class workflowInterface, String workflowId);
1.1
- ActivityStub and Workflow.newUntypedActivityStub
- Classes as arguments and return values to/from activity and workflow methods
- WorkflowStub and WorkflowClient.newUntypedWorkflowStub
- Custom workflow ids through start() and new_workflow_stub()
- ContinueAsNew
- Compatibility with Java client
- Compatibility with Golang client
2.0
- Sticky workflows
Post 2.0:
- sideEffect/mutableSideEffect
- Local activity
- Parallel activity execution
- Timers
- Cancellation Scopes
- Child Workflows
- Explicit activity ids for activity invocations
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