Guide for building reliable, fault-tolerant Python applications with DBOS durable workflows. Use when adding DBOS to existing Python code, creating workflows and steps, or using queues for concurrency control.
Guide for building reliable, fault-tolerant Python applications with DBOS durable workflows.
Reference these guidelines when:
| Priority | Category | Impact | Prefix |
|---|---|---|---|
| 1 | Lifecycle | CRITICAL | lifecycle- |
| 2 | Workflow | CRITICAL | workflow- |
| 3 | Step | HIGH | step- |
| 4 | Queue | HIGH | queue- |
| 5 | Communication | MEDIUM | comm- |
| 6 | Pattern | MEDIUM | pattern- |
| 7 | Testing | LOW-MEDIUM | test- |
| 8 | Client | MEDIUM | client- |
| 9 | Advanced | LOW | advanced- |
A DBOS application MUST configure and launch DBOS inside its main function:
import os
from dbos import DBOS, DBOSConfig
@DBOS.workflow()
def my_workflow():
pass
if __name__ == "__main__":
config: DBOSConfig = {
"name": "my-app",
"system_database_url": os.environ.get("DBOS_SYSTEM_DATABASE_URL"),
}
DBOS(config=config)
DBOS.launch()Workflows are comprised of steps. Any function performing complex operations or accessing external services must be a step:
@DBOS.step()
def call_external_api():
return requests.get("https://api.example.com").json()
@DBOS.workflow()
def my_workflow():
result = call_external_api()
return resultDBOS.start_workflow or DBOS.recv from a stepDBOS.start_workflow or queuesRead individual rule files for detailed explanations and examples:
references/lifecycle-config.md
references/workflow-determinism.md
references/queue-concurrency.mda5a6601
Also appears in
since Sep 26, 2026
since Sep 26, 2026
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.