Скачать или смотреть How to build and automate your Python ETL pipeline with Airflow | Data pipeline | Python

In this video, we will cover how to automate your Python ETL (Extract, Transform, Load) with Apache Airflow. In this session, we will use the TaskFlow API introduced in Airflow 2.0. TaskFlow API makes it much easier to author clean ETL code without extra boilerplate, by using the @task decorator. Airflow organizes your workflows as Directed Acyclic Graphs (DAGs) composed of tasks.


In this tutorial, we will see how to design a ETL Pipeline with Python. We will use SQL Server’s AdventureWorks database as a source and load data in PostgreSQL with Python. We will focus on Product's hierarchy and enhance our initial data pipeline to give you a complete overview of the extract, load and transform process.

Link to medium article on this topic:   / how-to-automate-etl-pipelines-with-airflow  

Link to previous video:    • How to build an ETL pipeline with Python |...  

Link to Pandas video:    • Python Pandas Data Science Tutorial (Read ...  

Link to GitHub repo: https://github.com/hnawaz007/pythonda...

Link to Cron Expressions: https://docs.oracle.com/cd/E12058_01/...

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#ETL #Python #Airflow

Topics covered in this video:
0:00 - Introduction to Airflow
2:49 - The Setup
3:40 - Script ETL pipeline: Extract
5:52 - Transform
7:39 - Load
8:00 - Define Direct Acyclic Graph (DAG)
9:36 - Airflow UI: Dag enable & run
10:09 - DAG Overview
10:29 - Test ETL Pipeline