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Python for Geeks

You're reading from   Python for Geeks Build production-ready applications using advanced Python concepts and industry best practices

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801070119
Length 546 pages
Edition 1st Edition
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Author (1):
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Muhammad Asif Muhammad Asif
Author Profile Icon Muhammad Asif
Muhammad Asif
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Python, beyond the Basics
2. Chapter 1: Optimal Python Development Life Cycle FREE CHAPTER 3. Chapter 2: Using Modularization to Handle Complex Projects 4. Chapter 3: Advanced Object-Oriented Python Programming 5. Section 2: Advanced Programming Concepts
6. Chapter 4: Python Libraries for Advanced Programming 7. Chapter 5: Testing and Automation with Python 8. Chapter 6: Advanced Tips and Tricks in Python 9. Section 3: Scaling beyond a Single Thread
10. Chapter 7: Multiprocessing, Multithreading, and Asynchronous Programming 11. Chapter 8: Scaling out Python Using Clusters 12. Chapter 9: Python Programming for the Cloud 13. Section 4: Using Python for Web, Cloud, and Network Use Cases
14. Chapter 10: Using Python for Web Development and REST API 15. Chapter 11: Using Python for Microservices Development 16. Chapter 12: Building Serverless Functions using Python 17. Chapter 13: Python and Machine Learning 18. Chapter 14: Using Python for Network Automation 19. Other Books You May Enjoy

Using Google Cloud Platform for data processing

Google Cloud Platform offers Cloud Dataflow as a data processing service to serve both batch and real-time data streaming applications. This service is meant for data scientists and analytics application developers so that they can set up a processing pipeline for data analysis and data processing. Cloud Dataflow uses Apache Beam under the hood. Apache Beam originated from Google, but it is now an open source project under Apache. This project offers a programming model for building data processing using pipelines. Such pipelines can be created using Apache Beam and then executed using the Cloud Dataflow service.

The Google Cloud Dataflow service is similar to Amazon Kinesis, Apache Storm, Apache Spark, and Facebook Flux. Before we discuss how to use Google Dataflow with Python, we will introduce Apache Beam and its pipeline concepts.

Learning the fundamentals of Apache Beam

In the current era, data is like a cash cow...

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