antigravity-skills-reference/web-app/public/skills/dbos-python/references/workflow-determinism.md

title, impact, impactDescription, tags

title	impact	impactDescription	tags
Keep Workflows Deterministic	CRITICAL	Non-deterministic workflows cannot recover correctly	workflow, determinism, recovery, reliability

Keep Workflows Deterministic

Workflow functions must be deterministic: given the same inputs and step return values, they must invoke the same steps in the same order. Non-deterministic operations must be moved to steps.

Incorrect (non-deterministic workflow):

import random

@DBOS.workflow()
def example_workflow():
    # Random number in workflow breaks recovery!
    choice = random.randint(0, 1)
    if choice == 0:
        step_one()
    else:
        step_two()

Correct (non-determinism in step):

import random

@DBOS.step()
def generate_choice():
    return random.randint(0, 1)

@DBOS.workflow()
def example_workflow():
    # Random number generated in step - result is saved
    choice = generate_choice()
    if choice == 0:
        step_one()
    else:
        step_two()

Non-deterministic operations that must be in steps:

• Random number generation
• Getting current time
• Accessing external APIs
• Reading files
• Database queries (use transactions or steps)

Reference: Workflow Determinism