Book Image

Data Engineering with Python

By : Paul Crickard
Book Image

Data Engineering with Python

By: Paul Crickard

Overview of this book

Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.
Table of Contents (21 chapters)
Section 1: Building Data Pipelines – Extract Transform, and Load
Section 2:Deploying Data Pipelines in Production
Section 3:Beyond Batch – Building Real-Time Data Pipelines

Installing and configuring Apache Airflow

Apache Airflow performs the same role as Apache NiFi; however, it allows you to create your data flows using pure Python. If you are a strong Python developer, this is probably an ideal tool for you. It is currently one of the most popular open source data pipeline tools. What it lacks in a polished GUI – compared to NiFi – it more than makes up for in the power and freedom to create tasks.

Installing Apache Airflow can be accomplished using pip. But, before installing Apache Airflow, you can change the location of the Airflow install by exporting AIRFLOW_HOME. If you want Airflow to install to opt/airflow, export the AIRLFOW_HOME variable, as shown:

export AIRFLOW_HOME=/opt/airflow

The default location for Airflow is ~/airflow, and for this book, this is the location I will use. The next consideration before installing Airflow is to determine which sub-packages you want to install. If you do not specify any, Airflow...