dbos-python
Helps your agent develop robust Python applications using DBOS. It makes creating reliable workflows and managing tasks easier.
What it does
This guide helps you build Python programs that are less likely to fail, using a tool called DBOS. It shows how to structure your code so it runs reliably, even if something goes wrong.
When to use it
- ✓When adding DBOS to existing Python code.
- ✓When creating new program parts (workflows and steps).
- ✓When using queues to manage how many tasks run at the same time.
Example of what to ask your AI
“How do I set up DBOS in my Python program?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
DBOS works by organizing your code into 'workflows' and 'steps'. Steps handle tasks that might fail or take time, while workflows reliably orchestrate these steps.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill dbos-pythonOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/dbos-python/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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:
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:
@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_workfloworDBOS.recvfrom a step - Do NOT use threads to start workflows - use
DBOS.start_workflowor 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
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ
What are workflows and steps?
Workflows are sequences of actions your program performs. Steps are smaller parts within a workflow that do specific tasks, like calling an external service.
Why does my code need to be reliable?
Reliable programs keep running even if errors or failures occur, ensuring tasks are completed without interruption.
What are queues for concurrency control?
Queues help manage how many tasks your program runs simultaneously, preventing overload and ensuring everything runs in an organized manner.
Details
Original description by the author
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.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2729
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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