7e5abd504f
Add three DBOS SDK skills with reference documentation for building reliable, fault-tolerant applications with durable workflows. Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
54 lines
1.3 KiB
Markdown
54 lines
1.3 KiB
Markdown
---
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title: Keep Workflows Deterministic
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impact: CRITICAL
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impactDescription: Non-deterministic workflows cannot recover correctly
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tags: workflow, determinism, recovery, reliability
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---
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## Keep Workflows Deterministic
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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.
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**Incorrect (non-deterministic workflow):**
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```python
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import random
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@DBOS.workflow()
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def example_workflow():
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# Random number in workflow breaks recovery!
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choice = random.randint(0, 1)
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if choice == 0:
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step_one()
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else:
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step_two()
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```
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**Correct (non-determinism in step):**
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```python
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import random
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@DBOS.step()
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def generate_choice():
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return random.randint(0, 1)
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@DBOS.workflow()
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def example_workflow():
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# Random number generated in step - result is saved
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choice = generate_choice()
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if choice == 0:
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step_one()
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else:
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step_two()
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```
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Non-deterministic operations that must be in steps:
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- Random number generation
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- Getting current time
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- Accessing external APIs
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- Reading files
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- Database queries (use transactions or steps)
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Reference: [Workflow Determinism](https://docs.dbos.dev/python/tutorials/workflow-tutorial#determinism)
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