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Data Ingestion with Python Cookbook

You're reading from   Data Ingestion with Python Cookbook A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781837632602
Length 414 pages
Edition 1st Edition
Languages
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Author (1):
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Gláucia Esppenchutz Gláucia Esppenchutz
Author Profile Icon Gláucia Esppenchutz
Gláucia Esppenchutz
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Fundamentals of Data Ingestion
2. Chapter 1: Introduction to Data Ingestion FREE CHAPTER 3. Chapter 2: Principals of Data Access – Accessing Your Data 4. Chapter 3: Data Discovery – Understanding Our Data before Ingesting It 5. Chapter 4: Reading CSV and JSON Files and Solving Problems 6. Chapter 5: Ingesting Data from Structured and Unstructured Databases 7. Chapter 6: Using PySpark with Defined and Non-Defined Schemas 8. Chapter 7: Ingesting Analytical Data 9. Part 2: Structuring the Ingestion Pipeline
10. Chapter 8: Designing Monitored Data Workflows 11. Chapter 9: Putting Everything Together with Airflow 12. Chapter 10: Logging and Monitoring Your Data Ingest in Airflow 13. Chapter 11: Automating Your Data Ingestion Pipelines 14. Chapter 12: Using Data Observability for Debugging, Error Handling, and Preventing Downtime 15. Index 16. Other Books You May Enjoy

To get the most out of this book

To execute the code in this book, you must have at least a basic knowledge of Python. We will use Python as the core language to execute the code. The code examples have been tested using Python 3.8. However, it is expected to still work with future language versions.

Along with Python, this book uses Docker to emulate data systems and applications in our local machine, such as PostgreSQL, MongoDB, and Airflow. Therefore, a basic knowledge of Docker is recommended to edit container image files and run and stop containers.

Please, remember that some command-line commands may need adjustments depending on your local settings or operating system. The commands in the code examples are based on the Linux command-line syntax and might need some adaptations to run on Windows PowerShell.

Software/Hardware covered in the book

OS Requirements

Python 3.8 or higher

Windows, Mac OS X, and Linux (any)

Docker Engine 24.0 / Docker Desktop 4.19

Windows, Mac OS X, and Linux (any)

For almost all recipes in this book, you can use a Jupyter Notebook to execute the code. Even though it is not mandatory to install it, this tool can help you to test the code and try new things on the code due to the friendly interface.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Download the example code files

You can download the example code files for this book from GitHub at https://github.com/PacktPublishing/Data-Ingestion-with-Python-Cookbook. In case there’s an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

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