What is DBOS durable execution?

DBOS durable execution ensures your Python programs are resilient to failures by automatically resuming workflows from the last completed step after an interruption or crash.

Is idempotency supported?

Yes, the skill provides patterns for idempotent workflows using SetWorkflowID to prevent duplicate executions of the same logical operation.

Can I use this with FastAPI?

Yes, the skill includes specific patterns for integrating DBOS workflows directly into FastAPI endpoints to create robust, fault-tolerant web APIs.

Which databases does this skill support?

This skill is optimized for use with PostgreSQL or SQLite as the system database for tracking workflow state, and works with SQLAlchemy for application data.

How does it handle external API failures?

It utilizes the @DBOS.step() decorator, which allows for configurable retry logic and ensures that non-deterministic I/O operations are recorded for recovery.

DBOS Python Durable Execution

Name: DBOS Python Durable Execution
Author: zach-source

byzach-source

0•

Cloud Infrastructure

Implements resilient, failure-recoverable Python applications using the DBOS durable execution framework for workflows and transactions.

This skill enables developers to build ultra-reliable Python applications by leveraging the DBOS framework's durable execution capabilities. It provides standardized patterns for creating workflows that automatically resume from their last completed step after an interruption, ensuring consistency and fault tolerance. By integrating PostgreSQL or SQLite as a system database, it manages state, transactions, and background queues seamlessly, making it ideal for complex business logic, long-running processes, and distributed systems where reliability is paramount.

Key Features

01Background queue processing with rate limiting and partitioning

02Built-in idempotency and workflow communication via messages and events

03Scheduled cron jobs for automated, recurring workflow execution

04Durable workflows that automatically resume after system failure

05Database-optimized transactions using SQLAlchemy and PostgreSQL

060 GitHub stars

Use Cases

01Developing fault-tolerant microservices that integrate with external APIs via retriable steps

02Orchestrating complex data pipelines that require intermediate state persistence and recovery

03Building resilient payment processing systems using the Saga pattern for multi-step transactions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zach-source/claude-plugins dbos-python

For use in Claude.ai and ChatGPT

Download Skill