Gain comprehensive insights into programming practices, and code portability and reuse to build flexible and maintainable apps using object-oriented principles
Extend core OOP techniques to increase integration of classes created with Python
Explore various Python libraries for handling persistence and object serialization
Learn alternative approaches for solving programming problems, with different attributes to address your problem domain
Object-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language's unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you'll be shown how to effectively implement OOP
in Python, and even explore Python 3.x.
Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design
offers the best performance. Next, you'll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you'll discover how essential it is to locate the best algorithms and optimal data structures for
developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs.
By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python.
What you will learn
Explore a variety of different design patterns for the __init__() method
Learn to use Flask to build a RESTful web service
Discover SOLID design patterns and principles
Use the features of Python 3's abstract base
Create classes for your own applications
Design testable code using pytest and fixtures
Understand how to design context managers that leverage the 'with' statement
Create a new type of collection using standard library and design techniques
Develop new number types above and beyond the built-in classes of numbers
Who this book is for
This book is for developers who want to use Python to create efficient programs. A good understanding of Python programming is required to make the most out of this book. Knowledge of concepts related to object-oriented design patterns will also be useful.
Create, deploy, and manage applications at scale using SRE principles
Build and run highly available, scalable, and secure software
Explore abstract SRE in a simplified and streamlined way
Enhance the reliability of cloud environments through SRE enhancements
Site reliability engineering (SRE) is being touted as the most competent paradigm in establishing and ensuring next-generation high-quality software solutions.
This book starts by introducing you to the SRE paradigm and covers the need for highly reliable IT platforms and infrastructures. As you make your way through the next set of chapters, you will learn to develop microservices using Spring Boot and make use of RESTful frameworks. You will also learn
about GitHub for deployment, containerization, and Docker containers. Practical Site Reliability Engineering teaches you to set up and sustain containerized cloud environments, and also covers architectural and design patterns and reliability implementation techniques such as reactive programming,
and languages such as Ballerina and Rust. In the concluding chapters, you will get well-versed with service mesh solutions such as Istio and Linkerd, and understand service resilience test practices, API gateways, and edge/fog computing.
By the end of this book, you will have gained experience on working with SRE concepts and be able to deliver highly reliable apps and services.
What you will learn
Understand how to achieve your SRE goals
Grasp Docker-enabled containerization concepts
Leverage enterprise DevOps capabilities and Microservices architecture (MSA)
Get to grips with the service mesh concept and frameworks such as Istio and Linkerd
Discover best practices for performance and resiliency
Follow software reliability prediction approaches and enable patterns
Understand Kubernetes for container and cloud orchestration
Explore the end-to-end software engineering process for the containerized world
Who this book is for
Practical Site Reliability Engineering helps software developers, IT professionals, DevOps engineers, performance specialists, and system engineers understand how the emerging domain of SRE comes handy in automating and accelerating the process of designing, developing, debugging, and deploying
highly reliable applications and services.