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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

Producing and consuming with Python

You can create producers and consumers for Kafka using Python. There are multiple Kafka Python libraries – Kafka-Python, PyKafka, and Confluent Python Kafka. In this section, I will use Confluent Python Kafka, but if you want to use an open source, community-based library, you can use Kafka-Python. The principles and structure of the Python programs will be the same no matter which library you choose.

To install the library, you can use pip. The following command will install it:

pip3 install confluent-kafka

Once the library has finished installing, you can use it by importing it into your applications. The following sections will walk through writing a producer and consumer.

Writing a Kafka producer in Python

To write a producer in Python, you will create a producer, send data, and listen for acknowledgements. In the previous examples, you used Faker to create fake data about people. You will use it again to generate the data...

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