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Data Engineering with Python

You're reading from   Data Engineering with Python Work with massive datasets to design data models and automate data pipelines using Python

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781839214189
Length 356 pages
Edition 1st Edition
Languages
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Author (1):
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Paul Crickard Paul Crickard
Author Profile Icon Paul Crickard
Paul Crickard
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Toc

Table of Contents (21) Chapters Close

Preface 1. Section 1: Building Data Pipelines – Extract Transform, and Load
2. Chapter 1: What is Data Engineering? FREE CHAPTER 3. Chapter 2: Building Our Data Engineering Infrastructure 4. Chapter 3: Reading and Writing Files 5. Chapter 4: Working with Databases 6. Chapter 5: Cleaning, Transforming, and Enriching Data 7. Chapter 6: Building a 311 Data Pipeline 8. Section 2:Deploying Data Pipelines in Production
9. Chapter 7: Features of a Production Pipeline 10. Chapter 8: Version Control with the NiFi Registry 11. Chapter 9: Monitoring Data Pipelines 12. Chapter 10: Deploying Data Pipelines 13. Chapter 11: Building a Production Data Pipeline 14. Section 3:Beyond Batch – Building Real-Time Data Pipelines
15. Chapter 12: Building a Kafka Cluster 16. Chapter 13: Streaming Data with Apache Kafka 17. Chapter 14: Data Processing with Apache Spark 18. Chapter 15: Real-Time Edge Data with MiNiFi, Kafka, and Spark 19. Other Books You May Enjoy Appendix

Writing and reading files in Python

The title of this section may sound strange as you are probably used to seeing it written as reading and writing, but in this section, you will write data to files first, then read it. By writing it, you will understand the structure of the data and you will know what it is you are trying to read.

To write data, you will use a library named faker. faker allows you to easily create fake data for common fields. You can generate an address by simply calling address(), or a female name using name_female(). This will simplify the creation of fake data while at the same time making it more realistic.

To install faker, you can use pip:

pip3 install faker

With faker now installed, you are ready to start writing files. The next section will start with CSV files.

Writing and reading CSVs

The most common file type you will encounter is Comma-Separated Values (CSV). A CSV is a file made up of fields separated by commas. Because commas are...

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