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Tutorial Overview

Prefect orchestrates workflows — it simplifies the creation, scheduling, and monitoring of complex data pipelines. You define workflows as Python code and Prefect handles the rest.

Prefect also provides error handling, retry mechanisms, and a user-friendly dashboard for monitoring. It's the easiest way to transform any Python function into a unit of work that can be observed and orchestrated.

This tutorial provides a guided walk-through of Prefect's core concepts and instructions on how to use them.

By the end of this tutorial you will have:

  1. Created a flow
  2. Added tasks to it
  3. Deployed and run the flow locally
  4. Created a work pool and run the flow remotely

These four topics will get most users to their first production deployment.

Advanced users that need more governance and control of their workflow infrastructure can go one step further by:

  1. Using a worker-based deployment

If you're looking for examples of more advanced operations (like deploying on Kubernetes), check out Prefect's guides.


Before you start, make sure you have Python installed, then install Prefect: pip install -U prefect

See the install guide for more detailed instructions.

To get the most out of Prefect, you need to connect to a forever-free Prefect Cloud account. 1. Create a new account or sign in at 1. Use the prefect cloud login CLI command to authenticate to Prefect Cloud from your environment.

prefect cloud login

Choose Log in with a web browser and click the Authorize button in the browser window that opens.

As an alternative to using Prefect Cloud, you can self-host a Prefect server instance. If you choose this option, run prefect server start to start a local Prefect server instance.

First steps: Flows

Let's begin by learning how to create your first Prefect flow - click here to get started.