54 lines
1.3 KiB
Markdown
54 lines
1.3 KiB
Markdown
---
|
|
title: Keep Workflows Deterministic
|
|
impact: CRITICAL
|
|
impactDescription: Non-deterministic workflows cannot recover correctly
|
|
tags: 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):**
|
|
|
|
```python
|
|
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):**
|
|
|
|
```python
|
|
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](https://docs.dbos.dev/python/tutorials/workflow-tutorial#determinism)
|