Cloudflare has introduced Python Workflows for its Workers platform, allowing developers to create multi-step applications using Python. This expansion addresses a significant gap, as previous support only existed for TypeScript. Python, widely used in data pipelines and machine learning, now enables developers to automate sequences of idempotent steps with built-in error handling and retries. This shift reduces friction for Python developers who previously faced challenges orchestrating applications on Cloudflare. The article highlights practical applications of Python Workflows, such as training large language models (LLMs) and managing data pipelines. Automating these processes can streamline model training by triggering each step based on the completion of the previous one. For instance, a grocery management agent can compile ingredient lists, check leftovers, and place orders seamlessly through defined workflows. Each step can wait for user input or other events, enhancing interactivity and control. The technical implementation of Python Workflows involves integrating Python directly into the Cloudflare runtime, ensuring feature parity with JavaScript. The use of Pyodide enables Python to interact with JavaScript through a foreign function interface. This design not only allows Python to access Cloudflare's durable execution features but also adapts the Workflows SDK to be more Pythonic, accommodating common Python patterns like decorators for callbacks. This makes the transition from JavaScript to Python smoother for developers familiar with both languages.