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Workflows

Workflows provide durable execution so you can write programs that are resilient to any failure. Workflows are comprised of steps, which are ordinary Python functions annotated with @DBOS.step(). If a workflow is interrupted for any reason (e.g., an executor restarts or crashes), when your program restarts the workflow automatically resumes execution from the last completed step.

Here's an example workflow that sends a confirmation email, sleeps for a while, then sends a reminder email. Using a workflow guarantees that even if the sleep duration is weeks or months, even if your program crashes or restarts many times, the reminder email is always sent on schedule (and the confirmation email is never re-sent).

@DBOS.workflow()
def reminder_workflow(email: str, time_to_sleep: int):
    send_confirmation_email(email)
    DBOS.sleep(time_to_sleep)
    send_reminder_email(email)

Here are some example apps demonstrating what workflows can do:

Reliability Guarantees​

Workflows provide the following reliability guarantees. These guarantees assume that the application and database may crash and go offline at any point in time, but are always restarted and return online.

  1. Workflows always run to completion. If a DBOS process is interrupted while executing a workflow and restarts, it resumes the workflow from the last completed step.
  2. Steps are tried at least once but are never re-executed after they complete. If a failure occurs inside a step, the step may be retried, but once a step has completed, it will never be re-executed.
  3. Transactions commit exactly once. Once a workflow commits a transaction, it will never retry that transaction.

If an exception is thrown from a workflow, the workflow terminates—DBOS records the exception, sets the workflow status to ERROR, and does not recover the workflow. This is because uncaught exceptions are assumed to be nonrecoverable. If your workflow performs operations that may transiently fail (for example, sending HTTP requests to unreliable services), those should be performed in steps with configured retries. DBOS provides tooling to help you identify failed workflows and examine the specific uncaught exceptions.

Determinism​

Workflows are in most respects normal Python functions. They can have loops, branches, conditionals, and so on. However, a workflow function must be deterministic: if called multiple times with the same inputs, it should invoke the same steps with the same inputs in the same order (given the same return values from those steps). If you need to perform a non-deterministic operation like accessing the database, calling a third-party API, generating a random number, or getting the local time, you shouldn't do it directly in a workflow function. Instead, you should do all database operations in transactions and all other non-deterministic operations in steps.

For example, don't do this:

@DBOS.workflow()
def example_workflow(friend: str):
    body = requests.get("https://example.com").text
    return example_transaction(body)

Do this instead:

@DBOS.step()
def example_step():
    return requests.get("https://example.com").text

@DBOS.workflow()
def example_workflow(friend: str):
    body = example_step()
    return example_transaction(body)

Workflow IDs and Idempotency​

Every time you execute a workflow, that execution is assigned a unique ID, by default a UUID. You can access this ID through the DBOS.workflow_id context variable. Workflow IDs are useful for communicating with workflows and developing interactive workflows.

You can set the workflow ID of a workflow with SetWorkflowID. Workflow IDs must be globally unique for your application. An assigned workflow ID acts as an idempotency key: if a workflow is called multiple times with the same ID, it executes only once. This is useful if your operations have side effects like making a payment or sending an email. For example:

@DBOS.workflow()
def example_workflow():
    DBOS.logger.info(f"I am a workflow with ID {DBOS.workflow_id}")

with SetWorkflowID("very-unique-id"):
    example_workflow()

Starting Workflows In The Background​

You can use start_workflow to start a workflow in the background without waiting for it to complete. This is useful for long-running or interactive workflows.

start_workflow returns a workflow handle, from which you can access information about the workflow or wait for it to complete and retrieve its result. The start_workflow method resolves after the handle is durably created; at this point the workflow is guaranteed to run to completion even if the app is interrupted.

Here's an example:

@DBOS.workflow()
def example_workflow(var1: str, var2: str):
    DBOS.sleep(10) # Sleep for 10 seconds
    return var1 + var2

# Start example_workflow in the background
handle: WorkflowHandle = DBOS.start_workflow(example_workflow, "var1", "var2")
# Wait for the workflow to complete and retrieve its result.
result = handle.get_result()

You can also use DBOS.retrieve_workflow to retrieve a workflow's handle from its ID.

Workflow Events​

Workflows can emit events, which are key-value pairs associated with the workflow's ID. They are useful for publishing information about the state of an active workflow, for example to transmit information to the workflow's caller.

set_event​

Any workflow can call DBOS.set_event to publish a key-value pair, or update its value if has already been published.

DBOS.set_event(
    key: str,
    value: Any,
) -> None

get_event​

You can call DBOS.get_event to retrieve the value published by a particular workflow identity for a particular key. If the event does not yet exist, this call waits for it to be published, returning None if the wait times out.

DBOS.get_event(
    workflow_id: str,
    key: str,
    timeout_seconds: float = 60,
) -> None

Events Example​

Events are especially useful for writing interactive workflows that communicate information to their caller. For example, in the widget store demo, the checkout workflow, after validating an order, needs to send the customer a unique payment ID. To communicate the payment ID to the customer, it uses events.

The payments workflow emits the payment ID using set_event():

@DBOS.workflow()
def checkout_workflow():
    ...
    payment_id = ...
    dbos.set_event(PAYMENT_ID, payment_id)
    ...

The FastAPI handler that originally started the workflow uses get_event() to await this payment ID, then returns it:

@app.post("/checkout/{idempotency_key}")
def checkout_endpoint(idempotency_key: str) -> Response:
    # Idempotently start the checkout workflow in the background.
    with SetWorkflowID(idempotency_key):
        handle = DBOS.start_workflow(checkout_workflow)
    # Wait for the checkout workflow to send a payment ID, then return it.
    payment_id = DBOS.get_event(handle.workflow_id, PAYMENT_ID)
    if payment_id is None:
        raise HTTPException(status_code=404, detail="Checkout failed to start")
    return Response(payment_id)

Reliability Guarantees​

All events are persisted to the database, so the latest version of an event is always retrievable. Additionally, if get_event is called in a workflow, the retrieved value is persisted in the database so workflow recovery can use that value, even if the event is later updated.

Workflow Messaging and Notifications​

You can send messages to a specific workflow ID. This is useful for sending notifications to an active workflow.

Send​

You can call DBOS.send() to send a message to a workflow. Messages can optionally be associated with a topic and are queued on the receiver per topic.

DBOS.send(
    destination_id: str,
    message: Any,
    topic: Optional[str] = None
) -> None

Recv​

Workflows can call DBOS.recv() to receive messages sent to them, optionally for a particular topic. Each call to recv() waits for and consumes the next message to arrive in the queue for the specified topic, returning None if the wait times out. If the topic is not specified, this method only receives messages sent without a topic.

DBOS.recv(
    topic: Optional[str] = None,
    timeout_seconds: float = 60,
) -> Any

Messages Example​

Messages are especially useful for sending notifications to a workflow. For example, in the widget store demo, the checkout workflow, after redirecting customers to a payments page, must wait for a notification that the user has paid.

To wait for this notification, the payments workflow uses recv(), executing failure-handling code if the notification doesn't arrive in time:

@DBOS.workflow()
def checkout_workflow():
  ... # Validate the order, then redirect customers to a payments service.
  payment_status = DBOS.recv(PAYMENT_STATUS)
  if payment_status is not None and payment_status == "paid":
      ... # Handle a successful payment.
  else:
      ... # Handle a failed payment or timeout.

An endpoint waits for the payment processor to send the notification, then uses send() to forward it to the workflow:

@app.post("/payment_webhook/{workflow_id}/{payment_status}")
def payment_endpoint(payment_id: str, payment_status: str) -> Response:
    # Send the payment status to the checkout workflow.
    DBOS.send(payment_id, payment_status, PAYMENT_STATUS)

Reliability Guarantees​

All messages are persisted to the database, so if send completes successfully, the destination workflow is guaranteed to be able to recv it. If you're sending a message from a workflow, DBOS guarantees exactly-once delivery. If you're sending a message from normal Python code, you can use SetWorkflowID with an idempotency key to guarantee exactly-once execution.

Coroutine (Async) Workflows​

Coroutinues (functions defined with async def, also known as async functions) can also be DBOS workflows. Asynchronous workflows provide the same reliability guarantees as synchronous workflow functions. Coroutine workflows may invoke coroutine steps via await expressions. You should start coroutine workflows in the background using DBOS.start_workflow_async and enqueue them using enqueue_async. Additionally, coroutine workflows should use the asynchronous versions of the workflow event and messaging and notification context methods.

tip

At this time, DBOS does not support coroutine transactions. To execute transaction functions without blocking the event loop, use asyncio.to_thread.

@DBOS.step()
async def example_step():
    async with aiohttp.ClientSession() as session:
        async with session.get("https://example.com") as response:
            return await response.text()

@DBOS.workflow()
async def example_workflow(friend: str):
    await DBOS.sleep_async(10)
    body = await example_step()
    result = await asyncio.to_thread(example_transaction, body)
    return result

Workflow Versioning and Recovery​

Because DBOS recovers workflows by re-executing them using information saved in the database, a workflow cannot safely be recovered if its code has changed since the workflow was started. To guard against this, DBOS versions applications and their workflows. When DBOS is launched, it computes an application version from a hash of the source code of its workflows (this can be overridden by setting the DBOS__APPVERSION environment variable). All workflows are tagged with the application version on which they started.

When DBOS tries to recover workflows, it only recovers workflows whose version matches the current application version. This prevents unsafe recovery of workflows that depend on different code. You can also manually recover a workflow on your current version with:

dbos workflow resume <workflow-id>

For more information on managing workflow recovery when self-hosting production DBOS applications, check out the guide.

Workflow Management​

You can view and manage your workflow executions via a web UI (self-hosted, DBOS Cloud) or via command line.

Listing Workflows​

You can list your application's workflows from the command line (you can parameterize this command for advanced search, see full documentation here):

dbos workflow list

Alternatively, navigate to the workflows tab of your application's page on the DBOS Console (either self-hosted or on DBOS Cloud) to see a searchable and expandable list of its workflows:

Workflow List

Cancelling Workflows​

You can cancel the execution of a workflow from the web UI or with:

dbos workflow cancel <workflow-id>

If the workflow is currently executing, cancelling it preempts its execution (interrupting it at the beginning of its next step). If the workflow is enqueued, cancelling removes it from the queue.

Resuming Workflows​

You can resume a workflow from its last completed step from the web UI or with:

dbos workflow resume <workflow-id>

You can use this to resume workflows that are cancelled or that have exceeded their maximum recovery attempts. You can also use this to start an enqueued workflow immediately, bypassing its queue.

Restarting Workflows​

You can start a new execution of a workflow from the web UI or with:

dbos workflow restart <workflow-id>

The new workflow has the same inputs as the original, but a new workflow ID.