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Modern Data Architectures with Python

You're reading from   Modern Data Architectures with Python A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781801070492
Length 318 pages
Edition 1st Edition
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Author (1):
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Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1:Fundamental Data Knowledge
2. Chapter 1: Modern Data Processing Architecture FREE CHAPTER 3. Chapter 2: Understanding Data Analytics 4. Part 2: Data Engineering Toolset
5. Chapter 3: Apache Spark Deep Dive 6. Chapter 4: Batch and Stream Data Processing Using PySpark 7. Chapter 5: Streaming Data with Kafka 8. Part 3:Modernizing the Data Platform
9. Chapter 6: MLOps 10. Chapter 7: Data and Information Visualization 11. Chapter 8: Integrating Continous Integration into Your Workflow 12. Chapter 9: Orchestrating Your Data Workflows 13. Part 4:Hands-on Project
14. Chapter 10: Data Governance 15. Chapter 11: Building out the Groundwork 16. Chapter 12: Completing Our Project 17. Index 18. Other Books You May Enjoy

Terraform setup

We will be using the infrastructure repo to store our infrastructure as code. I will go through the Terraform code in a little bit, but keep in mind we are using pre-commit on this repo also. It will reformat, lint, and syntax check your Terraform code. I can’t stress enough how useful this is, and I wish more teams followed this approach.

Initial file setup

I’m going to shy away from repeating the exact same setup for each Python repo given, in this chapter, we will only have the base template created. Instead, I will walk through one repo and the infrastructure repo and explain the key files.

I create a visible tree of the folder structure I used in Windows. The majority of the work is done in Linux but here and there, I am switching to Windows:

tree /f

Schema repository

Here, we can see the basic folder structure. I have removed anything not committed or not useful to explain. One example might be pytest cache folders. I will show...

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