dbos-pythonlisted

# DBOS Python Best Practices Guide for building reliable, fault-tolerant Python applications with DBOS durable workflows. ## When to Use Reference these guidelines when: - Adding DBOS to existing Python code - Creating workflows and steps - Using queues for concurrency control - Implementing workflow communication (events, messages, streams) - Configuring and launching DBOS applications - Using DBOSClient from external applications - Testing DBOS applications ## Rule Categories by Priority | 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-` | ## Critical Rules ### DBOS Configuration and Launch A DBOS application MUST configure and launch DBOS inside its main function: ```python 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() ``` ### Workflow and Step Structure Workflows are comprised of steps. Any function performing complex operations or accessing external serv