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Python for Geeks

Python for Geeks

By : Asif
4.5 (20)
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Python for Geeks

Python for Geeks

4.5 (20)
By: Asif

Overview of this book

Python is a multipurpose language that can be used for multiple use cases. Python for Geeks will teach you how to advance in your career with the help of expert tips and tricks. You'll start by exploring the different ways of using Python optimally, both from the design and implementation point of view. Next, you'll understand the life cycle of a large-scale Python project. As you advance, you'll focus on different ways of creating an elegant design by modularizing a Python project and learn best practices and design patterns for using Python. You'll also discover how to scale out Python beyond a single thread and how to implement multiprocessing and multithreading in Python. In addition to this, you'll understand how you can not only use Python to deploy on a single machine but also use clusters in private as well as in public cloud computing environments. You'll then explore data processing techniques, focus on reusable, scalable data pipelines, and learn how to use these advanced techniques for network automation, serverless functions, and machine learning. Finally, you'll focus on strategizing web development design using the techniques and best practices covered in the book. By the end of this Python book, you'll be able to do some serious Python programming for large-scale complex projects.
Table of Contents (20 chapters)
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1
Section 1: Python, beyond the Basics
5
Section 2: Advanced Programming Concepts
9
Section 3: Scaling beyond a Single Thread
13
Section 4: Using Python for Web, Cloud, and Network Use Cases

Chapter 9: Python Programming for the Cloud

Cloud computing is a broad term that is used for a wide variety of use cases. These use cases include an offering of physical or virtual compute platforms, software development platforms, big data processing platforms, storage, network functions, software services, and many more. In this chapter, we will explore Python for cloud computing from two correlated aspects. First, we will investigate the options of using Python for building applications for cloud runtimes. Then, we will extend our discussion of data-intensive processing, which we started in Chapter 8, Scaling Out Python using Clusters, from clusters to cloud environments. The focus of the discussion in this chapter will largely center on the three public cloud platforms; that is, Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure.

We will cover the following topics in this chapter:

  • Learning about the cloud options for Python applications
  • ...

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