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Скачать или смотреть Mastering Workflow Automation: Using Prefect with Python for Data Pipelines

  • Coding with Ani
  • 2024-07-20
  • 6321
Mastering Workflow Automation: Using Prefect with Python for Data Pipelines
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Описание к видео Mastering Workflow Automation: Using Prefect with Python for Data Pipelines

Prefect Python Tutorial | Build and Manage Data Pipelines with Ease

In this comprehensive tutorial, we dive deep into Prefect, a powerful workflow orchestration tool. Whether you're a beginner or an experienced developer, this video will guide you through the essential aspects of using Prefect for creating and managing data pipelines.

For code and commands used in this tutorial, chech this link

https://www.csestack.org/prefect-pyth...

Timestamps:
00:05 - What is Prefect?
Understand the basics of Prefect and its significance in workflow orchestration.

02:08 - How to install Prefect Python package?
Step-by-step guide to installing the Prefect package in your Python environment.

03:21 - Writing data pipeline workflow in Python code by creating Prefect task and flow.
Learn how to write data pipeline workflows using Prefect tasks and flows.

06:40 - ETL Workflow in Prefect Python [Real-time example]
A real-time example demonstrating an ETL workflow using Prefect.

09:38 - Retry function in Python Prefect.
Explore the retry function in Prefect and how it enhances the reliability of your workflows.

10:18 - Creating Prefect server dashboard.
Set up and manage your Prefect server dashboard for better workflow monitoring and control.

12:14 - Why Prefect is a game-changing workstation architecture tool?
Discover why Prefect is considered a revolutionary tool in the field of workflow orchestration.

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Why Prefect?

Prefect is an open-source workflow orchestration tool that makes it easy to build, manage, and monitor data pipelines. Its flexible and user-friendly design allows developers to focus on building workflows without worrying about the underlying infrastructure. Prefect supports retries, scheduling, parameterization, and more, making it a versatile tool for various data engineering tasks.

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