dbos-python
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
Runtime boundaries
Examples are version-sensitive fragments with omitted app setup/imports/handlers; verify installed DBOS APIs. Durable workflow identity does not make arbitrary external side effects exactly-once: steps may repeat after a crash before checkpointing. Use provider idempotency keys plus reconciliation for payments/messages. Authorize database targets and writes, protect serialized inputs/results, and never deserialize untrusted pickle data. API routes need authentication, tenant ownership, webhook signature/replay validation and bounded waits. Destructive test reset must use a dedicated disposable system database; a variable name alone is not target proof.