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

Inserting and extracting NoSQL database data in Python

Relational databases may be what you think of when you hear the term database, but there are several other types of databases, such as columnar, key-value, and time-series. In this section, you will learn how to work with Elasticsearch, which is a NoSQL database. NoSQL is a generic term referring to databases that do not store data in rows and columns. NoSQL databases often store their data as JSON documents and use a query language other than SQL. The next section will teach you how to load data into Elasticsearch.

Installing Elasticsearch

To install the elasticsearch library, you can use pip3, as shown:

pip3 install elasticsearch

Using pip will install the newest version, which, if you installed Elasticsearch according to the instructions in Chapter 2, Building Our Data Engineering Infrastructure, is what you will need. You can get the library for Elasticsearch versions 2, 5, 6, and 7. To verify the installation and...