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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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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

Technical requirements

You can find the code for this chapter in the GitHub repository here: https://github.com/PacktPublishing/Data-Ingestion-with-Python-Cookbook.

Installing and running Airflow

This chapter requires that Airflow is installed on your local machine. You can install it directly on your operating system (OS) or by using a Docker image. For more information, refer to the Configuring Docker for Airflow recipe in Chapter 1.

After following the steps described in Chapter 1, ensure your Airflow runs correctly. You can do that by checking the Airflow UI here: http://localhost:8080.

If you are using a Docker container (as I am) to host your Airflow application, you can check its status on the terminal by running the following command:

$ docker ps

You can see the command running here:

Figure 10.1 – Airflow containers running

Figure 10.1 – Airflow containers running

For Docker, check the container status on Docker Desktop, as shown in the following screenshot:

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