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

Understanding logs

If you have written code, you may be familiar with software logs. Software developers use logging to write output from applications to a text file to store different events that happen within the software. They then use these logs to help debug any issues that arise. In Python, you have probably implemented code similar to the following code:

import logging
logging.basicConfig(level=0,filename='python-log.log', filemode='w', format='%(levelname)s - %(message)s')
logging.debug('Attempted to divide by zero')
logging.warning('User left field blank in the form')
logging.error('Couldn't find specified file')

The preceding code is a basic logging example that logs different levels – debug, warning, and error – to a file named python-log.log. The code will produce the following output:

DEBUG - Attempted to divide by zero
WARNING - User left field blank in the form
ERROR - Couldn&apos...