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dbos-python

DBOS Python SDK for building reliable, fault-tolerant applications with durable workflows.

Skill by dbos

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About

DBOS Python SDK for building reliable, fault-tolerant applications with durable workflows. Use this skill when writing Python code with DBOS, creating workflows and steps, using queues, using DBOSClient from external applications, or building applications that need to be resilient to failures.

Use cases: writing

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

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  • ~/.claude/skills/dbos-python

What's inside

Skill name
dbos-python
Description
DBOS Python SDK for building reliable, fault-tolerant applications with durable workflows. Use this skill when writing Python code with DBOS, creating workflows and steps, using queues, using DBOSClient from external applications, or building applications that need to be resilient to failures.
License
MIT
Metadata
date: January 2026 · author: dbos · version: 1.0.0 · abstract: Comprehensive guide for building fault-tolerant Python applications with DBOS. Covers workflows, steps, queues, communication patterns, and best practices for durable execution. · organization: DBOS
Instructions
90 lines in SKILL.md · view on GitHub

Before installing

  • Instructions call the network

Files (37)

  • AGENTS.md
  • CLAUDE.md
  • SKILL.md
  • _sections.md · references/
  • advanced-async.md · references/
  • advanced-patching.md · references/
  • advanced-serialization.md · references/
  • advanced-versioning.md · references/
  • client-enqueue.md · references/
  • client-setup.md · references/
  • comm-events.md · references/
  • comm-messages.md · references/
  • comm-streaming.md · references/
  • lifecycle-config.md · references/
  • lifecycle-fastapi.md · references/
  • pattern-classes.md · references/
  • pattern-debouncing.md · references/
  • pattern-idempotency.md · references/
  • pattern-scheduled.md · references/
  • pattern-sleep.md · references/
  • queue-basics.md · references/
  • queue-concurrency.md · references/
  • queue-deduplication.md · references/
  • queue-listening.md · references/
  • queue-partitioning.md · references/
  • queue-priority.md · references/
  • queue-rate-limiting.md · references/
  • step-basics.md · references/
  • step-retries.md · references/
  • step-transactions.md · references/
  • test-fixtures.md · references/
  • workflow-background.md · references/
  • workflow-constraints.md · references/
  • workflow-control.md · references/
  • workflow-determinism.md · references/
  • workflow-introspection.md · references/
  • workflow-timeout.md · references/

SKILL.md (first lines)

# DBOS Python Best Practices

Guide for building reliable, fault-tolerant Python applications with DBOS durable workflows.

## When to Apply

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 services must be a step:

```python
@DBOS.step()
def call_external_api():
    return requests.get("https://api.example.com").json()

@DBOS.workflow()
def my_workflow():
    result = call_external_api()
    return result
```

### Key Constraints

- Do NOT call `DBOS.start_workflow` or `DBOS.recv` from a step
- Do NOT use threads to start workflows - use `DBOS.start_workflow` or queues
- Workflows MUST be deterministic - non-deterministic operations go in steps
- Do NOT create/update global variables from workflows or steps

## How to Use

Read individual rule files for detailed explanations and examples:

```
references/lifecycle-config.md
references/workflow-determinism.md
references/queue-concurrency.md
```

## References

- https://docs.dbos.dev/
- https://github.com/dbos-inc/dbos-transact-py

From datasciencemonkey/maestro-decisioning-demo, MIT.

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Last commit (this folder)
May 10, 2026 (5 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
1.0.0
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Cite this page

dbos-python skill. Agent Mart. https://agentmart.dev/skills/datasciencemonkey-dbos-python (last updated 2026-10-24)