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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
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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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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

Reading a JSON file

JavaScript Object Notation (JSON) is a semi-structured data format. Some articles also define JSON as an unstructured data format, but the truth is this format can be used for multiple purposes.

JSON structure uses nested objects and arrays and, due to its flexibility, many applications and APIs use it to export or share data. That is why describing this file format in this chapter is essential.

This recipe will explore how to read a JSON file using a built-in Python library and explain how the process works.

Note

JSON is an alternative to XML files, which are very verbose and require more coding to manipulate their data.

Getting ready

This recipe is going to use the GitHub Events JSON data, which can be found in the GitHub repository of this book at https://github.com/jdorfman/awesome-json-datasets with other free JSON data.

To retrieve the data, click on GitHub API | Events, copy the content from the page, and save it as a .json file...

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