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

Building data pipelines in Apache Airflow

Apache Airflow uses Python functions, as well as Bash or other operators, to create tasks that can be combined into a Directed Acyclic Graph (DAG) – meaning each task moves in one direction when completed. Airflow allows you to combine Python functions to create tasks. You can specify the order in which the tasks will run, and which tasks depend on others. This order and dependency are what make it a DAG. Then, you can schedule your DAG in Airflow to specify when, and how frequently, your DAG should run. Using the Airflow GUI, you can monitor and manage your DAG. By using what you learned in the preceding sections, you will now make a data pipeline in Airflow.

Building a CSV to a JSON data pipeline

Starting with a simple DAG will help you understand how Airflow works and will help you to add more functions to build a better data pipeline. The DAG you build will print out a message using Bash, then read the CSV and print a list...